Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 91 appraisals
Journal of critical care
Artificial intelligence and computerized decision support in adult intensive care: A systematic review of randomized controlled trials
BACKGROUND: Artificial intelligence (AI) and computerized clinical decision support systems (CDSS) are increasingly applied in intensive care, yet their clinical impact remains uncertain, as most studies focus on model development rather than prospective evaluation. OBJECTIVES: To identify randomized controlled trials (RCTs) evaluating AI-based or CDSS interventions intended to influence real-time decision-making in adult intensive care units (ICUs) and to assess their effects on process and patient-centered outcomes. METHODS: We conducted a systematic review of randomized controlled trials (RCTs). PubMed, Embase, Cochrane CENTRAL, ScienceDirect, and IEEE Xplore were searched from inception to November 2025. Eligible studies evaluated AI-based or CDSS interventions in adult ICU patients. Study quality was assessed using RoB 2 and CONSORT-AI criteria. RESULTS: Ten RCTs were included, enrolling approximately 100,000 adult ICU patients. Five trials evaluated AI-based interventions and five evaluated CDSS. Eight trials showed improvements in at least one process measure, including earlier recognition of deterioration, improved protocol adherence, and physiological stability. However, patient-centered benefits were uncommon. Two trials reported reductions in mortality (a sepsis prediction model and a machine-learning-based early-warning system), while most studies showed no consistent effects on clinical outcomes. Reporting of AI-specific elements-dataset provenance, algorithm versioning, and human-AI interaction-was frequently incomplete. CONCLUSIONS: AI and CDSS interventions in adult ICUs are associated with improvements in process-related outcomes but show limited and inconsistent effects on patient-centered endpoints. These findings highlight a persistent gap between algorithmic innovation and clinical validation and underscore the need for pragmatic randomized trials with improved reporting and integration into clinical workflows.
3 Aug 2026
Read appraisal →Current opinion in critical care
Smart feeding: the role of artificial intelligence and integrated nutrition platforms in the ICU
PURPOSE OF REVIEW: Tremendous improvement in the use of artificial intelligence has opened new opportunities to analyze the data obtained from electronic health records and imaging. New technologies have tried to overcome obstacles to implement guidelines and recommendations. This review aims to describe the recent progress in the use of machine learning and new technologies in the field of nutrition of the critically ill. RECENT FINDINGS: Increase in data availability, ability to extract these data and analyze them using machine learning has allowed data scientists together with ICU specialists to improve nutritional screening and assessment and to predict occurrence of obstacles like enteral feeding intolerance or refeeding hypophosphatemia. In addition, new technologies can ensure nasogastric tube positioning and enteral feeding efficacy. Integrated platforms can integrate nutritional needs with most adequate prescriptions and modulate the nutritional administration according to the patient's tolerance and requirements. Analysis of continuous recording of imaging obtained from ultrasound can also predict gastric intolerance. SUMMARY: Using machine learning, numerous algorithms and nomograms have been suggested to predict enteral feeding intolerance but validation of these predictions is still required. New technologies integrating energy requirements and delivery of the optimal enteral feeding are very promising.
2 Aug 2026
Read appraisal →Brain and behavior
Machine Learning-Based Prediction of Poor Outcomes in Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is associated with high risks of mortality and disability, yet early and accurate outcome prediction remains challenging. This study systematically evaluated the performance of machine learning (ML) models in predicting key adverse outcomes (hematoma expansion [HE], poor functional outcome, mortality) in ICH, aiming to provide consolidated evidence for future research and clinical translation. METHODS: We systematically searched PubMed, Embase, Web of Science, and Cochrane Library up to September 2025. Studies developing and validating ML models for predicting HE, poor functional outcome (modified Rankin Scale 3-6), or mortality in adults with spontaneous ICH were included. Pooled concordance index (C-index), sensitivity, and specificity were calculated using a random-effects or bivariate model. RESULTS: Eighty-three studies (involving at least 136,840 patients) were included. Meta-analysis of model performance, derived predominantly from internal validation set, demonstrated that models integrating both clinical and radiomics features achieved the highest discriminative performance across key prognostic prediction tasks: predicting HE (pooled C-index 0.822, 95% confidence interval [CI] 0.789-0.855), poor functional outcome (C-index 0.850, 95% CI 0.830-0.869), and mortality (C-index 0.860, 95% CI 0.809-0.911). These findings should be interpreted with caution, as true external validation remains sparse. Logistic regression exhibited performance comparable to more complex ML algorithms. CONCLUSIONS: ML models, particularly integrated clinical-radiomics models, demonstrate strong performance for the prediction of outcomes in ICH. They hold significant potential to enhance risk stratification and guide personalized management, pending further validation in diverse cohorts.
1 Aug 2026
Read appraisal →International urology and nephrology
Acute kidney injury prediction and prognostication using machine learning
Acute Kidney Injury (AKI) is a major health concern with high costs and poor outcomes, partly due to late diagnosis. This paper reviews the application of artificial intelligence (AI) and machine learning (ML) to overcome these limitations by enabling earlier and more accurate prediction and prognostication of AKI. Many studies on AI and ML models used to predict and prognosticate AKI were included in the review. The focus was on models that analyze complex datasets, including real-time data streams like novel biomarkers and continuous vital signs, to achieve earlier and more accurate predictions than conventional methods. ML models show high predictive accuracy for AKI onset and outcomes across various clinical settings, including intensive care units, sepsis, and postoperative and postcontrast situations, with key findings like the successful integration of real-time data to reflect the evolving nature of kidney injury. AI and ML offer a powerful, proactive solution for AKI management. By leveraging diverse data, these technologies can significantly improve patient outcomes and reduce healthcare costs. While their promising performance warrants further exploration, successful clinical integration will require user-friendly platforms and continued validation.
1 Aug 2026
Read appraisal →Biomedical physics & engineering express
Automated ventricular and midline segmentation in cranial ultrasound with metrology
Ultrasound imaging through sonolucent cranial implants is an emerging modality for post-neurosurgical monitoring of the adult brain, but quantitative interpretation remains challenging due to speckle, attenuation, shadowing, and the difficulty of consistently delineating thin anatomical landmarks. We present a deep learning system developed atLongeviti Neuro Solutionsfor segmenting key intracranial structures-the ipsilateral and contralateral lateral ventricles and the cranial midline-in coronal-plane adult cranial ultrasound images from patients withLongeviti ClearFit®Acoustic Brain Interface (ABI)TMimplants. The dataset comprises 457 proprietary, de-identified ultrasound frames with known pixel spacing, annotated in CVAT with ventricle and midline labels. We benchmark multiple encoder-decoder segmentation architectures and address severe class imbalance using class-weighted optimization with Dice and midline-focused focal-Tversky terms, followed by horizontal-flip test-time averaging. The best-performing configuration achieved a foreground macro Dice of 0.856 on a held-out test set, with Dice values of 0.926, 0.921, and 0.720 for the contralateral ventricle, ipsilateral ventricle, and midline, respectively. Finally, predicted masks are converted into geometry-based metrology overlays by estimating maximal perpendicular ventricle spans and ventricle-to-midline distances. These outputs provide standardized, millimeter-calibrated measurement visualizations for downstream review and future clinical validation.
28 July 2026
Read appraisal →Medicine
Comparative safety and effectiveness of stents in drainage of pancreatic fluid collections guided by endoscopic ultrasonography: A systematic review and network meta-analysis
BACKGROUND: Endoscopic ultrasonography-guided drainage is an effective treatment for pancreatic fluid collections (PFCs). However, the optimal stent strategy for endoscopic ultrasonography-guided drainage of PFCs is still unclear. This study aims to compare the clinical outcomes of different stent types to identify the best option. METHODS: Databases including PubMed, EMBASE, and Cochrane were searched up to August 2024. The analysis focused on comparisons between bi-flanged metal stents (BFMS), double-pigtail plastic stents (DPPS), fully covered self-expanding metal stents (FCSEMS), lumen-apposing metal stents (LAMS), and the combination of LAMS and DPPS (LAMS + DPPS). RESULTS: A total of 38 studies, involving 4265 patients with PFCs, were analyzed. In all of these patients, LAMS (risk ratio [RR]: 1.07, 95% confidence interval [CI]: 1.02-1.13) and BFMS (RR: 1.08, 95% CI: 1.01-1.15) showed higher clinical success rates compared with DPPS. LAMS + DPPS reduced infection rates compared with BFMS (RR: 0.32, 95% CI: 0.10-0.99), DPPS (RR: 0.19, 95% CI: 0.06-0.62), and FCSEMS (RR: 0.23, 95% CI: 0.07-0.76). Within the pancreatic pseudocysts subgroup, LAMS (RR: 1.08, 95% CI: 1.01-1.16) and LAMS + DPPS (RR: 1.24, 95% CI: 1.03-1.48) demonstrated higher clinical success rates compared with DPPS. Similarly, in the walled-off necrosis subgroup, LAMS (RR: 1.10, 95% CI: 1.02-1.17), LAMS + DPPS (RR: 1.19, 95% CI: 1.01-1.41), FCSEMS (RR: 1.14, 95% CI: 1.03-1.26), and BFMS (RR: 1.11, 95% CI: 1.03-1.20) all showed higher success rates compared with DPPS, with BFMS exhibiting a lower bleeding rate than DPPS (RR: 0.32, 95% CI: 0.18-0.99). CONCLUSION: Newer metal stents, including BFMS, LAMS, and LAMS + DPPS, offer advantages over plastic stents like DPPS alone. BFMS is preferable when bleeding risk is a concern, while LAMS + DPPS is more effective in reducing infection rates in PFCs.
26 July 2026
Read appraisal →Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Utility of Repeating Blood Cultures in Candidemia: Insights From 2 Large Clinical Data Repositories
We evaluated utility of repeating blood culture for candidemia using 2 electronic health record datasets. Among 1386 candidemia episodes, repeated blood culture detected 23% of episodes at Houston Methodist Hospital and 45% in Medical Information Mart for Intensive Care IV after the initial negative cultures. These findings support repeating blood cultures when candidemia is highly suspected.
24 July 2026
Read appraisal →Neurosurgical review
Prognostic value of automated pupillometry in traumatic brain injury: a systematic review and meta-analysis
Traumatic brain injury (TBI) remains a major global cause of mortality and long-term disability. Early prognostication is critical for guiding management decisions. Quantitative pupillometry (QP), using automated devices such as the NeurOptics NPi-200/300, enables bedside measurement of pupillary reactivity through indices like the Neurological Pupil Index (NPi), constriction velocity (CV), and dilation velocity (DV). We conducted a PRISMA-compliant systematic review and meta-analysis to evaluate the prognostic value of QP in adults with TBI. Observational studies of quantitative pupillometry within 72 h of traumatic brain injury in adult ICU patients were included. Studies limited to mild TBI were excluded, although mixed-severity cohorts were eligible. Primary outcomes were mortality and poor functional outcome at 3-6 months (GOS ≤ 3 or mRS ≥ 3). Secondary analyses assessed differences in pupillometry metrics according to intracranial hypertension defined by direct ICP measurements (> 20-25 mmHg) or proxy markers reflecting ICP-directed interventions. Odds ratios were pooled for dichotomous outcomes and mean differences for continuous outcomes using random-effects models, with heterogeneity quantified by I². Four studies (n = 354) reported mortality data. Abnormal quantitative pupillary metrics (most commonly NPi < 3 or absent reflexes) were associated with increased odds of in-hospital death (OR 1.84, 95% CI 1.01-3.35; I² = 84%). Five studies (n = 384) assessed functional outcomes, showing significantly greater odds of poor outcome among patients with abnormal pupillary metrics (OR 3.64, 95% CI 1.63-8.10; I² = 39%). Three studies (n = 190) evaluated intracranial pressure, demonstrating lower NPi values in patients with intracranial hypertension compared with those without elevated ICP, though this difference did not reach statistical significance (MD - 1.05, 95% CI - 2.65 to 0.54). Early quantitative pupillometry is associated with increased mortality and worse functional outcomes in TBI in observational studies. Lower quantitative pupillary metrics were also observed in the presence of intracranial hypertension. Despite substantial heterogeneity, these findings support its potential as a prognostic tool. Further standardization, validation and controlled studies are needed to refine its clinical application.
21 July 2026
Read appraisal →Renal failure
Effects on mortality of different blood purification techniques in sepsis patients: an umbrella review of systematic reviews and meta-analyses
Sepsis remains a leading cause of mortality worldwide, and extracorporeal blood purification has been widely implemented despite ongoing uncertainty regarding its survival benefit. We conducted an umbrella review of 42 systematic reviews and meta-analyses evaluating mortality across major extracorporeal blood purification modalities. Mortality estimates generally favored extracorporeal blood purification over conventional care, but effect sizes and consistency varied substantially by modality, and the overall certainty of evidence for mortality was low. At the review level, polymyxin B hemoperfusion showed a relatively consistent direction toward lower mortality, whereas renal replacement therapy-based strategies were typically closer to the null. However, most included reviews were of low or critically low methodological quality, with downgrading driven by risk of bias, inconsistency, and potential publication bias. Therefore, these findings should be interpreted cautiously and should not be considered definitive evidence of survival benefit. They highlight persistent evidentiary fragility and underscore the need for rigorously designed, phenotype-informed trials to clarify modality-specific effects in sepsis. What is known: Extracorporeal blood purification has been widely used as an adjunctive therapy for sepsis, but its mortality benefit remains uncertain across different modalities.What this study adds: This umbrella review synthesizes evidence from 42 systematic reviews and meta-analyses and shows that mortality estimates generally favor extracorporeal blood purification, although effects vary substantially by modality and the overall certainty of evidence remains low.Potential impact: These findings support cautious, modality- and phenotype-informed interpretation of extracorporeal blood purification in sepsis and highlight the need for rigorously designed trials with standardized protocols.
19 July 2026
Read appraisal →Pulmonology
Systematic review of prognostic scores and individual predictor variables for short-term mortality after acute pulmonary embolism.
BACKGROUND: For patients with acute pulmonary embolism (PE), assessment of prognosis helps with risk stratification, triage for level of care, management strategy, and communication among healthcare workers and patients. We sought to identify prognostic models and individual factors associated with short-term outcomes after acute symptomatic PE. METHODS: We performed a systematic review of prognostic factors for PE, searching MEDLINE, Embase, and Web of Science for records up to 1 June 2024. Studies of any design evaluating potential prognostic models or individual variables (not contained in the models) associated with short-term mortality after acute PE were included. RESULTS: We identified 314 studies that included 2,495,115 patients. Of these, 225 studies included 2,267,952 patients and evaluated 24 prognostic models for patients with acute PE. The most frequently used validated models were the simplified Pulmonary Embolism Severity Index (sPESI) (127 studies), the original PESI (79 studies), and the European Society of Cardiology risk schema (34 studies). Each model-development study had a c-index ≥ 0.7. Individual factors associated with prognosis included older age, presence of coexisting conditions, abnormal clinical signs and symptoms, clot burden, markers of right‑ventricle dilatation/dysfunction and myocardial injury, altered laboratory results indicating impaired haemodynamics, and tests that assess for systemic inflammation. Pooled odds ratios for variables not contained in any eligible prognostic model ranged from 1.43 (for D-dimer) to 2.65 (for right heart thrombi). CONCLUSIONS: This systematic review identified 24 prognostic models and 18 individual variables distinct from the prognostic models associated with short-term mortality after acute PE.
17 July 2026
Read appraisal →Critical care explorations
Drug Clearance and Dosing During CytoSorb Hemoadsorption: A Systematic Review
OBJECTIVE: CytoSorb (CS) hemoadsorption is increasingly used in critical care and cardiac surgery to remove inflammatory mediators and select drugs. This systematic review aimed to summarize available evidence on intentional drug removal as well as unintentional drug removal during CS therapy. DATA SOURCES: PubMed, congress abstracts, and CytoSorbents online literature database. STUDY SELECTION: Eligible studies included benchtop, animal, and human pharmacokinetic investigations of drug removal during CS therapy as well as clinical reports describing CS use for drug overdose. DATA EXTRACTION: Data from the eligible studies were extracted independently by two authors into Microsoft Excel. DATA SYNTHESIS: Data were identified for drugs across multiple therapeutic classes, including analgesics, antiarrhythmics, anticonvulsants, antidepressants, antihypertensives, anti-infectives, antithrombotics, anxiolytics, and immunosuppressants. Drugs were categorized into low (< 30%), moderate (30-60%), or high (> 60%) removal rate, or by the relative increase in clearance attributable to CS: negligible (< 25%), low (25-100%), moderate (100-400%), or high (> 400%). Based on the assembled data and considering drug-, patient-, and circuit-specific factors, general dosing recommendations for concomitant medications were developed. CONCLUSIONS: CS therapy can alter drug concentrations for select agents with variable clinical relevance. CS can reduce perioperative bleeding risk through antithrombotic removal and treat certain drug overdoses. Unintentional drug removal during CS therapy may occur and practical guidance is provided for drugs with known susceptibility to removal.
16 July 2026
Read appraisal →European journal of clinical pharmacology
Impact of carvedilol versus metoprolol on ventricular arrhythmia burden and ICD therapies: a systematic review and meta-analysis
BACKGROUND: Ventricular arrhythmias (VA) are major causes of morbidity and mortality in patients with cardiovascular disease. Implantable cardioverter-defibrillators (ICDs) are commonly used to prevent sudden cardiac death. However, patients with ICDs frequently experience recurrent arrhythmias and inappropriate shocks, which impact quality of life. Beta-blockers, specifically carvedilol and metoprolol, are commonly prescribed in this context. This meta-analysis aims to compare the impact of both medications in this patient population. METHODS: Comprehensive literature search was conducted to identify relevant studies comparing carvedilol to metoprolol in patients with VA or ICDs. Study outcomes included all-cause mortality, recurrent VA, and inappropriate ICD shocks. Effect estimates are presented as hazard ratios (HR) with 95% confidence intervals (CI). RESULTS: Five independent study populations, reported across six publications, including 7,777 patients (5,138 on carvedilol, 2,639 on metoprolol) were analyzed. Carvedilol was associated with a significantly lower risk of inappropriate ICD shocks (HR = 0.66, 95% CI: 0.48-0.90, P = 0.009) and inappropriate anti-tachycardia pacing (HR = 0.67, 95% CI: 0.49-0.91, P = 0.01) compared with metoprolol. There were no significant differences between the two beta-blockers in recurrent ventricular tachyarrhythmias or all-cause mortality. CONCLUSION: Carvedilol may provide additional benefit over metoprolol in reducing inappropriate ICD therapies and anti-tachycardia pacing, while no significant differences were found in recurrent ventricular arrhythmias or all-cause mortality. These findings support consideration of carvedilol in patients with ICDs, but further research is warranted to guide optimal beta-blocker selection.
15 July 2026
Read appraisal →Metabolomics : Official journal of the Metabolomic Society
Clinical lipidomics in bacterial sepsis: a systematic review of serum and plasma evaluations
BACKGROUND: Lipid metabolism plays a central role in host-pathogen interactions and immune regulation during bacterial sepsis, with its dysregulation contributing to organ failure and mortality. Blood-based lipidomics has emerged as a promising approach for identifying diagnostic and prognostic biomarkers in sepsis. However, discrepancies in lipid profiles between serum and plasma remain a major challenge for clinical translation. This systematic review synthesizes lipidomic evidence from serum and plasma in bacterial sepsis patients to identify reproducible lipid biomarkers, evaluate methodological heterogeneity and assess associations with clinical outcomes. METHODS: A systematic search of five databases (Scopus, Pubmed, Ovid MEDLINE, Web of Science and Google Scholar) identified nine eligible studies published between 2016 and 2025 that applied untargeted or targeted lipidomics on human serum and plasma samples from adult bacterial sepsis patients (PROSPERO: CRD420251086177). RESULTS: Across both matrices, reproducible candidate lipid biomarkers included triacylglycerols (TAG), phosphatidylcholines (PC), lysophosphatidylcholines (LPC), sphingomyelins (SM) and ceramides. Synthesized findings revealed characteristically distinct directional trajectories: consistent elevation of TAG, bidirectional shifts of PC, depletion of LPC, bidirectional shifts of SM and elevation of SM. Preliminary trend within the literature indicates that serum-based studies more frequently captured prognostic alterations, whereas plasma-based studies often focused on diagnostic discrimination. Substantial heterogeneity was observed in sample handling, lipid extraction protocols and analytical platforms. CONCLUSIONS: Overall, both matrices offer valuable clinical insights, though these apparent differences in diagnostic or prognostic utility may reflect primary study designs rather than intrinsic matrix superiorities. Methodological heterogeneity limits reproducibility, highlighting the need for standardized workflows to enable translation of sepsis lipid biomarkers.
9 July 2026
Read appraisal →Nature communications
Empowering clinical trial design with agentic intelligence and real-world data
Clinical trial design (CTD) is a time-consuming process that requires substantial domain expertise. Large-scale real-world data (RWD), such as electronic health records (EHR), encodes practice-based evidence that is of tremendous value to CTD. In recent years, many machine learning methods have been developed to extract such real-world evidence (RWE) from the RWD to inform CTD, but they still need to be communicated with the domain experts extensively in an iterative manner to be further refined and ultimately useful. In this paper, we introduce EmulatRx, an agentic framework that derives RWE for helping with CTD. Through the iterative conversation and analysis across agents with different roles, EmulatRx can autonomously refine trial protocols and finally generate a robust report containing insights that inform better CTD. We applied EmulatRx on the CTD process for both acute diseases (e.g., septic shock, acute heart failure, acute pulmonary edema, and acute kidney injury) using the MIMIC-IV data and chronic diseases (e.g., Alzheimer's disease and Parkinson's disease) using the INSIGHT Network across five New York City health systems. The results demonstrate EmulatRx's capabilities in facilitating and accelerating the CTD process.
9 July 2026
Read appraisal →Journal of the American Medical Informatics Association : JAMIA
Engineering biomarker representations of vital signs data enhances deep learning mortality prediction
OBJECTIVES: We evaluated bidirectional long short-term memory models for predicting inpatient mortality using different approaches to processing vital signs data collected during the initial 24 h of intensive care unit (ICU) admissions. MATERIALS AND METHODS: We compared 3 vital-sign representations: (1) raw data recorded every 5 min, (2) preprocessed data averaged hourly, and (3) preprocessed data using biomarker representations that extends a digital oximetry biomarker toolbox of PhysioZoo software, applied to blood pressure, heart rate, temperature, respiratory rate, and SpO2. RESULTS: Across 2 large ICU datasets, HiRID and eICU, models trained on the frequency-normalized representation achieved higher discrimination and lower Brier scores than those trained on raw 5-min and hourly averaged data. DISCUSSION: The use of biomarker representations of vital signs yielded the largest improvements in discrimination and overall probabilistic performance reflected by lower Brier scores for predicting inpatient mortality by deep learning. CONCLUSION: Thus, we recommend using a similar approach to vital signs preprocessing for time-series predictive models.
3 July 2026
Read appraisal →The Kurume medical journal
Development of Machine Learning Models to Predict Candidemia in Hospitalized Adult Patients
PURPOSE: We aimed to develop a generalizable machine learning model that leverages electronic medical record (EMR) data to predict candidemia using information available on or before the date of blood culture collection. METHODS: This study included adult patients admitted to Shin Koga Hospital (April 2014-March 2022) who underwent blood cultures at least 14 days after admission. We prepared two datasets: a "Complete case dataset" (13 variables, no missing values) and a "Imputed full-variable dataset" (36 variables, single imputation). We evaluated the discriminative performance of four machine learning models, including extreme gradient boosting, random forest, least absolute shrinkage and selection operator (LASSO) logistic regression, and logistic regression using stratified 5-fold cross-validation by comparing their area under the receiver operating characteristic curve (AUROC). The model with the highest mean AUROC was selected, assessed on the entire dataset, and internally validated using 1,000 bootstrap replicates. RESULTS: A total of 919 patients were included, of whom 47 (5.1%) had candidemia. The LASSO logistic regression demonstrated the best performance and was selected as the final model. The AUROC (95% CI) was 0.880 (0.836-0.924) for the Complete case dataset and 0.913 (0.878-0.948) for the Imputed full-variable dataset. The optimism-corrected AUROCs were 0.851 and 0.876, respectively. CONCLUSION: We developed two versions of the LASSO logistic regression model using only information automatically extracted from EMR, considering real-world data availability. These models have the potential to serve as practical tools to support early diagnosis and therapeutic intervention for candidemia.
3 July 2026
Read appraisal →The Cochrane database of systematic reviews
Prognostic models for predicting intensive care unit admission or mortality in critically ill adults not yet been admitted to the intensive care unit
OBJECTIVES: This is a protocol for a Cochrane Review (prognosis). The objectives are as follows: To determine whether prognostic models can be used for predicting the occurrence of ICU admission and mortality within the index hospital admission, and post-discharge survival at reported follow-up time points, up to one year, in critically ill adults not yet admitted to the ICU. The objective in PICOTS format is as follows. POPULATION: critically ill adults not yet admitted to the ICU Index prognostic model: available prognostic models with or without external validation Comparator: not applicable Outcomes: ICU admission, ICU and hospital mortality, and post-discharge survival Timing: for ICU admission or transfer, ICU mortality, and hospital mortality outcomes, the timing will be in hospital. For post-discharge survival, the timing will be up to 28 days, 1 to 3 months, 6 months, and 1 year after hospital discharge. SETTING: acute hospital wards and emergency care departments.
30 June 2026
Read appraisal →Journal of medical Internet research
Vision-Based Artificial Intelligence Technologies for Epilepsy Monitoring: Scoping Review and Taxonomy Development Study
BACKGROUND: Artificial intelligence (AI) technologies for vision-based epilepsy monitoring are advancing rapidly in health care. Despite growing research using various video data sources and analytical approaches, no comprehensive framework exists to classify these technologies. OBJECTIVE: This scoping review aimed to develop and validate a taxonomy for AI technologies in vision-based epilepsy monitoring and to characterize visual AI approaches in epilepsy care. METHODS: Using an extended taxonomy development framework, we developed the taxonomy in 5 iterative cycles, drawing on theory and practice. We conducted a scoping review, market analysis, and applicability evaluation with market-ready solutions. We searched Scopus, Web of Science, and PubMed, including MeSH (Medical Subject Headings) terms; the final search was completed on January 16, 2026. We included primary studies from 2013 onward on AI-based or machine learning-based monitoring or prediction of epileptic seizures in humans using visual data. We excluded reviews, non-English publications, nonepilepsy studies, studies focused only on electroencephalography or wearables, animal studies, and pre-2013 publications. Evidence was charted through narrative and tabular synthesis and descriptive frequency analysis. In line with scoping review guidance, we did not conduct a meta-analysis or critical appraisal. To assess validity and practical relevance, 9 domain experts evaluated the taxonomy using a Delphi technique. RESULTS: We included 40 original studies. Study analysis yielded 16 dimensions, including data acquisition source, tracking target, image processing, classifier type, performance metrics, environment, seizure classification, data privacy, and user interface. Expert feedback added 4 further dimensions, including communication mode and information purpose. The final taxonomy comprises 23 dimensions with 102 characteristics. The review identified structural evidence gaps across settings, evaluation maturity, and reporting practices. Detection and classification in stationary settings predominated, whereas predictive approaches and real-time feedback were limited. Deep learning detection methods were common, but performance reporting was inconsistent, and patient-facing functionalities were limited. Privacy safeguards and standardized metrics were often incompletely reported, reducing comparability and maturity assessment. The taxonomy translates these patterns into guidance for benchmarking, procurement evaluation, user interface, and explainable AI design. We synthesized 5 main findings and 10 implications for research and practice. Key challenges concern standardization, seizure prediction, and real-time applicability. CONCLUSIONS: Vision-based AI technologies for epilepsy monitoring are still dominated by proof-of-concept and pilot evaluations, indicating a gap between technical feasibility and deployment-ready systems. This scoping review presents an implementation-oriented taxonomy integrating application context, system architecture, visual analysis, AI models, performance reporting, and feedback design into a single classification framework. Unlike prior work that mainly maps methods or data sources, the taxonomy provides a shared structure for consistent system-level characterization and comparison across studies and emerging solutions. It may support benchmarking, implementation-focused evaluation, procurement, and translation into clinical and home settings.
25 June 2026
Read appraisal →Journal of medical Internet research
Policy Considerations for National Virtual Hospitals: Global Evidence and the Seha Virtual Hospital Model
Health systems worldwide face growing pressure from population aging, multimorbidity, and rising emergency admissions, prompting reconsideration of traditional inpatient care models. In response, digitally enabled models such as tele-intensive care unit (tele-ICU) programs, hospital-at-home services, virtual wards, and other remote specialist pathways have expanded, particularly after the COVID-19 pandemic accelerated telemedicine adoption and cross-site virtual staffing. However, nationally coordinated, multispecialty virtual hospitals remain uncommon worldwide, and robust evidence on their system-level effects is still limited. As a result, policy discussions about national virtual hospitals must often draw on evidence from related virtual-care models rather than from mature national implementations. This viewpoint synthesizes representative international evidence from tele-ICU systems, hospital-at-home programs, virtual wards, telestroke networks, and other condition-specific virtual-care pathways, and examines Saudi Arabia's Seha Virtual Hospital (SVH) as a national case study to identify policy lessons relevant to the design, governance, and evaluation of national virtual hospitals. Across settings, these models suggest that remote and digitally supported care can achieve outcomes comparable to in-person hospital care when patient selection is appropriate, escalation and transfer pathways are explicit, monitoring intensity matches clinical risk, and multidisciplinary teams are integrated into local workflows. Tele-ICU programs have reported reductions in intensive care mortality and length of stay under well-structured organizational models, while hospital-at-home and virtual-ward programs have shown comparable safety, reduced hospital usage, and improved patient experience among selected patient groups. Telestroke networks likewise demonstrate outcomes comparable to specialist in-person care in acute stroke pathways. Nevertheless, the evidence base remains heterogeneous and strongly context-dependent. Much of the literature is short-term, with limited consistent evidence on long-term outcomes, caregiver burden, cost-effectiveness, workforce implications, and digital equity. SVH illustrates the emerging implementation of a centralized national virtual hospital model. Launched in 2022 under Saudi Arabia's Vision 2030 Health Sector Transformation Program, SVH operates as a national telehealth hub embedded within the country's broader digital-health ecosystem and links hospitals across the Kingdom to specialized clinical expertise. Its service portfolio includes urgent and critical care consultations, specialized virtual clinics, multidisciplinary case discussions, and supportive diagnostic services. Early reports indicate rapid operational expansion, broad institutional participation, and national-scale feasibility. However, independent comparative evidence evaluating SVH's effects on mortality, readmissions, length of stay, cost-effectiveness, equity, and workforce sustainability remains limited. National virtual hospitals should therefore be understood as evidence-generating health-system innovations rather than fully validated care models. Sustainable scale-up requires embedding rigorous prospective evaluation within implementation, aligning financing mechanisms with substitution of inpatient care, establishing clear governance and regulatory frameworks, and addressing digital inclusion and workforce sustainability. These considerations can help guide policymakers and health-system leaders in the accountable, equitable, and evidence-informed development of national virtual hospital programs.
25 June 2026
Read appraisal →BMC geriatrics
Components and effects of psychosocial support interventions for relatives of patients with delirium in hospitals, systematic review
BACKGROUND: Relatives of patients with delirium are often confronted with patients' challenging behaviours such as hyperactivity, aggression, or hallucinations. As a result, feelings of anxiety and depression episodes have been described. The aim is to identify psychosocial support intervention for relatives of patients with delirium in hospitals, describe components and effects, and identify research gaps. METHODS: Systematic review based on PRISMA, including psychosocial support intervention studies addressing burden and support needs of adult relatives of hospital patients with delirium. We searched the databases Medline, Web of Sience, CINAHL, Livivo, PsycINFO, and Cochrane Library in 07/2024 and reference lists. We assessed reporting using TIDieR and CReDECI2 and methodological quality using ROB-1 and the JBI tool for quasi-experimental studies. We performed narrative syntheses. RESULTS: We identified eight intervention studies addressing relatives of patients with delirium in different settings. Intervention components included provision of information using flyers, videos, web-sites, or telephone calls, and mentoring in the intensive care unit. Reporting of interventions was mostly poor. No study reported a process evaluation. Four of six studies showed a significant difference in relatives' delirium knowledge. For relatives' psychological outcomes, no clear effects were shown. Overall, study quality was limited. CONCLUSIONS: More effectiveness studies are needed with better reporting of intervention components, ideally addressing psychological aspects. Feasibility and acceptance of new interventions should be described within accompanying process evaluations. TRIAL REGISTRATION: https://osf.io/7jbsk .
13 June 2026
Read appraisal →Journal of tropical pediatrics
A randomized controlled trial to evaluate the efficacy and safety of a double-walled incubator compared to a radiant warmer in the care of extremely low-birth-weight infants
This study compared the safety and efficacy of double-walled incubators versus radiant warmers in extremely low-birth weight (ELBW: birth weight < 1000 g) preterm infants, hypothesizing that incubator care would reduce the time to regain birth weight compared with radiant warmer care. In this single-center, nonblinded, randomized controlled trial, ELBW infants with gestational age ≥25 to ≤32 weeks were randomized shortly after birth to stay in either an incubator or a radiant warmer for the first week of life, followed by radiant warmer care for all infants. The primary outcome was time to regain birth weight. Secondary outcomes included fluid intake, sodium levels, hypernatremia, and other neonatal outcomes. One hundred ELBW infants were enrolled. The median time to regain birth weight did not significantly differ between the incubator and radiant warmer groups: 12.00 (IQR 7.00, 17.75) days versus 11.50 (IQR 7.25, 15.75) days, respectively, with an effect size of median difference 0.0 (95% CI -4.0 to 4.0, P = .89). There were no significant differences in any other secondary outcomes. The study lacked sufficient power to detect differences in these outcomes. Either a double-walled incubator or a radiant warmer can be considered similarly safe and effective for thermoregulation and for achieving time to regain birth weight in ELBW infants. Radiant warmers may be preferable in low- and middle-income countries because they are less costly than double-walled incubators.
12 June 2026
Read appraisal →BMJ open
Prediction of ICU length of stay, hospital discharge outcomes and discharge location among ICU-admitted patients diagnosed with viral hepatitis using machine learning: a retrospective cohort study of the MIMIC-IV database
BACKGROUND: Hepatitis, a disease characterised by inflammation of the liver, is a leading global health challenge that contributes to over 1.3 million deaths annually, with hepatitis B and C accounting for many of these fatalities. Intensive care unit (ICU) management of patients is particularly challenging due to the complex clinical care and resource demands. Despite advancements in ICU predictive analytics, limited research has specifically addressed hepatitis patients, creating a gap in optimising care for this population. METHODS: This study focuses on predicting ICU length of stay (LoS), hospital discharge outcomes and discharge location for ICU-admitted viral hepatitis patients using a comparative assessment of machine learning (ML) models. Leveraging data from the Medical Information Mart for Intensive Care-IV database, which includes around 94 500 ICU patient records, this study uses sociodemographic details, clinical characteristics and resource utilisation metrics to develop predictive models such as Random Forest, Logistic Regression, Gradient Boosting Machines and Generalised Additive Model with Negative Binomial Regression. RESULTS: Among 3875 ICU-admitted hepatitis patients, Random Forest classification outperformed Logistic Regression in predicting discharge outcomes, achieving higher accuracy (0.87 vs 0.82) and greater discriminative ability (area under the receiver operating characteristic curve 0.95 vs 0.89). For ICU LoS prediction, Random Forest regression applied to log-transformed LoS demonstrated strong performance (R² up to 0.82), while the generalised additive model with negative binomial distribution explained approximately 76% of LoS variance. Prediction of discharge location yielded moderate performance across Gradient Boosting and multinomial logistic regression models (accuracy 0.55 and 0.56), reflecting challenges associated with multi-class imbalance. Variable importance analyses across ML models consistently identified medication counts, procedure counts, comorbidity burden, age, race and total LoS as the most influential predictors of discharge outcomes and discharge location. CONCLUSIONS: This study demonstrates the value of ML models for predicting clinical outcomes for hepatitis patients, including ICU LOS and hospital discharge status. The results underscore the influence of factors like race and age, revealing disparities that must be addressed in predictive care strategies. While the models show promise, challenges such as variability in prolonged stays and limited multiclass prediction accuracy point to the need for ongoing refinement and research.
11 June 2026
Read appraisal →Critical care explorations
Artificial Liver Support Effectively Removes Immunosuppressive Bile Acids From Circulation in Patients With Severe Liver Failure: A Proof of Concept Study
OBJECTIVE: Bile acids that induce immunosuppression through activation of the Takeda G protein-coupled receptor 5 (TGR5) have recently been identified in the circulation of patients with liver failure and sepsis. These bile acids are associated with increased susceptibility to infection and a high short-term mortality. Furthermore, TGR5 activation by bile acids has been implicated in the development of pruritus. However, therapies targeting TGR5-activating bile acids in patients have not yet been reported. This study investigates the effects of two artificial liver support systems, the Molecular Adsorbent Recirculating System (MARS) and the open albumin dialysis (OPAL). DESIGN: Proof of concept study, multicenter study. SETTING: University Hospital Jena, University Hospital Ulm, and University Hospital Münster, Germany. PATIENTS: Patients with severe liver failure, as defined by the Sequential Organ Failure Assessment hepatic sub-score (i.e., bilirubin > 12 mg/dL). INTERVENTIONS: Patients with severe liver failure were randomized to receive one session of MARS or OPAL for 8 hours, followed by crossover to the other treatment on the next day. MEASUREMENTS AND MAIN RESULTS: Bilirubin, circulating total and individual bile acids, albumin function, and TGR5 activation induced by circulating bile acids were assessed before and after each treatment session. Both OPAL and MARS significantly removed bilirubin, as well as individual and total bile acids from circulation. OPAL was superior to MARS in removing protein-bound lipophilic bile acids and restoring patients' albumin function (i.e., albumin-binding capacity, detoxification efficiency, and binding efficiency). TGR5 activation induced by circulating bile acids was reduced by 60% with OPAL compared with 39% with MARS (median values, p = 0.051). CONCLUSIONS: Artificial liver support systems effectively remove immunosuppressive bile acids from circulation. The clinical implications of bile acid reduction, however, require further study.
11 June 2026
Read appraisal →JAMA
Fast Antimicrobial Susceptibility Testing for Gram-Negative Bacteremia: The FAST Randomized Clinical Trial
IMPORTANCE: Novel blood culture diagnostics provide rapid antimicrobial susceptibility testing (AST) results for bacteria causing bloodstream infections (BSIs) but have unclear clinical impact. OBJECTIVE: To evaluate clinical outcomes of blood culture testing using a rapid AST method compared with standard AST in patients with BSIs caused by gram-negative bacilli in regions with high prevalence of antimicrobial resistance. DESIGN, SETTING, AND PARTICIPANTS: Open-label randomized clinical trial that enrolled participants from December 2023 to May 2025 (final follow-up, June 18, 2025) at 7 medical centers in Greece (n = 2), India (n = 1), Israel (n = 3), and Spain (n = 1). Hospitalized patients (adults and children) with BSIs caused by gram-negative bacilli were eligible. Statistical analysis was conducted from August 2025 to January 2026. INTERVENTION: Patients were randomized to undergo blood culture evaluation using rapid, phenotypic AST directly from positive blood cultures plus standard susceptibility testing (n = 413) vs standard susceptibility testing alone (n = 437). Local antimicrobial stewardship teams reviewed all patients and provided treatment recommendations. MAIN OUTCOMES AND MEASURES: The primary outcome was a desirability of outcome ranking (DOOR) at day 30, with 3 categories (alive without deleterious events, alive with deleterious events, and death). The difference between rapid and standard testing was summarized as the probability that the DOOR outcomes were more desirable in the rapid testing group. Superiority was concluded if the lower limit of the 95% CI exceeded 50%. Secondary outcomes included 30-day mortality, length of hospitalization, intensive care unit admission, acquisition of hospital-acquired infections, time to effective antibiotic therapy within 3 days, and time to antibiotic escalation or deescalation within 3 days. RESULTS: Of the 899 patients randomized, 850 were included in the primary outcome analysis (median [IQR] age, 72 [21] years; 43% female). The probability that DOOR outcomes were more favorable in the rapid testing group was 48.8% (95% CI, 45.3%-52.4%). Median time to effective antibiotic therapy was not different between the groups in the as-randomized population. Median time to antibiotic escalation or deescalation was faster in the rapid testing group by 14 hours (95% CI, 6-22) in the as-randomized population. There were no differences between the groups in other secondary outcomes. In the prespecified subgroup with carbapenem-resistant infections, median time to effective therapy was 9.5 hours in the rapid testing group vs 28 hours in the standard testing group (difference, -18 hours [95% CI, -42 to 6]). CONCLUSIONS AND RELEVANCE: Among patients with gram-negative bacilli BSIs, rapid blood culture AST was not superior to standard testing by DOOR. When considered with other efficacy and safety outcomes, these findings may help inform the use of rapid susceptibility testing in clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06174649.
29 May 2026
Read appraisal →BMJ open
Does a protocolised oxygenation target impact clinical outcomes in mechanically ventilated patients in the intensive care unit across the 10 academic and community hospitals in the UCHealth system? Protocol and statistical analysis plan for an EHR-embedded pragmatic stepped-wedge randomised controlled trial.
INTRODUCTION: We designed the Optimising Care in Critically Ill at the UCHealth by Liberalising the Target O₂ in Mechanically ventilated intensive care unit (ICU) Patients to determine the effectiveness of a multimodal educational and electronic health record order panel intervention in limiting occult hypoxaemia and hyperoxaemia in patients receiving invasive mechanical ventilation by targeting a prespecified oxygen saturation (SpO₂ 90%-96%) range. METHODS AND ANALYSIS: This trial is a pragmatic electronic health record-embedded, multisite, cluster-randomised, stepped-wedge implementation of a multimodal educational and electronic health record order panel intervention aimed at achieving a standardised intermediate target range of SpO₂ (90%-96%) or partial pressure of oxygen (PaO₂ 60-100 mm Hg) in mechanically ventilated adult patients admitted to the ICU across a 10 hospital health system that includes a large academic centre and smaller community hospitals.The primary endpoint is ventilator-free days to day 30, defined as the number of days alive and not receiving support through invasive mechanical ventilation following the first initiation of invasive mechanical ventilation in a participating ICU during the hospitalisation. Secondary outcomes include a variety of clinical endpoints: hospital-free days to day 30, all-cause mortality to day 90, need for supplemental oxygen at discharge and incidence of occult hypoxaemia and hypoxaemia. We will analyse primary and secondary endpoints using a mixed effects modelling framework, with specific distributions chosen depending on the type of outcome (eg, binary, count, ordinal, time-to-event). ETHICS AND DISSEMINATION: Research is performed under a waiver of informed consent for minimal-risk research, as approved by Colorado Multiple Institutional Review Board (24-0065). Results will be disseminated in peer-reviewed publications and at national and international conferences. TRIAL REGISTRATION NUMBER: NCT06501118.
28 May 2026
Read appraisal →NEJM evidence
Outcomes of Pneumonia in ICUs in Low- and Middle-Income Countries - A Systematic Review
BACKGROUND: Community-acquired pneumonia (CAP) is a leading cause of intensive care unit (ICU) admission and death in low- and middle-income countries (LMICs). We conducted a systematic review and meta-analysis to estimate mortality among patients with CAP admitted to ICUs in LMICs. METHODS: We searched multiple databases using terms related to CAP admitted to the ICU and LMIC. We included both observational studies and clinical trials. The primary outcome was all-cause ICU, 28-day or 30-day mortality. Demographics, comorbidities, clinical characteristics, mechanical ventilation, and length of ICU stay were described. We registered the study in PROSPERO (CRD42022363048). RESULTS: A total of 52 studies from 18 countries met inclusion criteria, encompassing 48,707 patients. Most studies originated in upper-middle-income countries and no studies from low-income countries were identified. The most frequent comorbidities were hypertension, chronic obstructive pulmonary disease, and diabetes. Mechanical ventilation was reported in 36 studies, with median use in 59% (interquartile range, 41.4-77.4) of patients. Pooled mortality was 37% (95% confidence interval [CI], 31-42), rising to 61 (44-75) among patients requiring mechanical ventilation. In a meta-regression, age and mechanical ventilation were the strongest moderators of mortality, explaining 55.2% of heterogeneity in short-term mortality. CONCLUSIONS: Mortality among patients with CAP admitted to ICUs in middle-income countries remains high, especially in older and mechanically ventilated patients. The lack of data from low-income countries is notable.
27 May 2026
Read appraisal →Nature communications
Measuring multi-site pulse transit time with an AI-enabled mmWave radar
Pulse Transit Time (PTT) is a measure of arterial stiffness and a physiological marker associated with cardiovascular function, with an inverse relationship to diastolic blood pressure (DBP). We present an AI-enabled mmWave system for contactless multi-site PTT measurement using a single radar. By leveraging radar beamforming and deep learning algorithms our system simultaneously measures PTT and estimates diastolic blood pressure at multiple sites. The system was evaluated across three physiological pathways - heart-to-radial artery, heart-to-carotid artery, and mastoid area-to-radial artery - achieving correlation coefficients of 0.75-0.86 compared to contact-based reference sensors for measuring PTT. Furthermore, the system demonstrated correlation coefficients of 0.90-0.91 for estimating DBP, and achieved a mean error of -0.62-0.06 mmHg and standard deviation of 4.54-5.20 mmHg, meeting the FDA's AAMI guidelines for non-invasive blood pressure monitors. These results suggest that our proposed system has the potential to provide a non-invasive measure of cardiovascular health across multiple regions of the body.
27 May 2026
Read appraisal →Scientific reports
Impact of a structured case report on self-reported responses to simulated emergency scenarios: a randomized survey-based study
Case reports are a long-standing component of medical research, but their association with self-reported responses to simulated clinical scenarios remains underexplored. This study investigated whether exposure to a structured case report influences simulated emergency medical decisions. This randomized survey-based study was conducted among licensed physicians between March and May 2025. Participants were randomly assigned to an intervention group, which received a structured case report on blunt neck trauma, or a control group, which did not. Both groups subsequently provided self-reported Likert-scale responses to identical simulated emergency scenarios, covering five domains: local trauma consequences, accompanying injuries, diagnostic methods, airway management strategies, and hospital selection. Responses were collected on Likert scales. Group differences were assessed using Mann-Whitney U tests, t-tests, and chi-squared tests; prespecified exploratory subgroup analyses examined the moderating role of clinical experience. Sixty-three participants completed the study. Baseline demographics and qualifications did not differ significantly between groups. Exposure to the case report was associated with statistically significant differences in self-reported responses to simulated scenarios, with the most pronounced associations in airway management strategies (all five items statistically significant, median effect size r = 0.44). Intervention participants assigned higher ratings to maintaining spontaneous breathing and supraglottic airway use, while assigning lower appropriateness to endotracheal intubation and cricothyrotomy. Moderate associations were observed in diagnostic choices (e.g., pathological breath sounds, ultrasound use) and hospital selection (e.g., ECMO availability). No consistent effects were found for local or accompanying injuries. Exploratory stratified analyses revealed that junior physicians (≤ 5 years of practice) appeared more responsive, with significant differences across multiple domains and larger effect sizes (median r > 0.6). In contrast, no statistically significant between-group differences were detected in the senior (> 15 years) subgroup, although this exploratory analysis was limited by small subgroup size. Structured case reports may influence self-reported responses to simulated emergency scenarios, particularly among less experienced clinicians. These findings suggest that the educational impact of case-based learning formats may vary depending on the level of clinical experience, but do not allow conclusions about real-world clinical behavior or patient outcomes. Future work should further investigate adaptive case report formats and their potential integration into emergency medicine training.Trial registration: German Clinical Trials Register (DRKS00038961), registered von 13 January 2026.
27 May 2026
Read appraisal →JMIR formative research
An In-Hospital Mortality Risk Model for Patients Undergoing Coronary Artery Bypass Grafting Based on Machine Learning: Cohort Study
BACKGROUND: Ischemic heart disease remains the leading cause of death worldwide. Coronary artery bypass grafting (CABG) remains the primary surgical treatment for ischemic heart disease. There is currently a lack of highly accurate and widely applicable models for assessing the risk of postoperative mortality following CABG. OBJECTIVE: This study aimed to develop and validate an in-hospital mortality risk prediction system for patients undergoing coronary artery bypass grafting (CABG) by using machine learning algorithms and to compare its performance with the European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) and Sino System for Coronary Operative Risk Evaluation (SinoSCORE). METHODS: Between January 2017 and December 2020, 21,443 patients undergoing CABG in the Chinese Cardiac Surgery Registry were included. Patients were randomly divided into training (n=17,753) and test (n=3690) cohorts. We addressed class imbalance using the synthetic minority oversampling technique (SMOTE) and optimized hyperparameters via grid search. Fifteen machine learning algorithms were developed to predict in-hospital mortality. Performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration metrics (Brier score), and decision curve analysis, and was compared against EuroSCORE II and SinoSCORE. RESULTS: A total of 21,443 patients were included. Overall, in-hospital mortality was 2.1% (n=450). The Extreme Gradient Boosting (XGBoost) model achieved the best performance with an AUC of 0.850 in the training cohort and 0.782 in the independent test cohort (this cohort was independent and not involved in model construction). While EuroSCORE II showed an AUC of 0.722 and SinoSCORE showed an AUC of 0.726 in the test cohort, the XGBoost model demonstrated superior discrimination and calibration (P<.05). CONCLUSIONS: Our study developed and validated a machine learning-based risk prediction model for in-hospital mortality after CABG by using a large-scale Chinese multicenter registry. Among the algorithms tested, the XGBoost model demonstrated superior discrimination and calibration compared with the traditional EuroSCORE II and SinoSCORE, suggesting that locally calibrated models may better capture the risk profile of Chinese patients. The derived 7-variable web calculator may serve as an exploratory auxiliary tool to provide a preliminary reference for bedside risk stratification, though its direct impact on surgical decision-making requires further prospective validation. Future research should focus on independent test cohorts across diverse hospital tiers to ensure broad generalizability.
26 May 2026
Read appraisal →JMIR research protocols
AI-Supported, Integrative Prediction of Postoperative Delirium: Protocol for the CONFUSED Study
BACKGROUND: Postoperative delirium (POD) is a frequent and serious complication in older surgical patients, characterized by acute cognitive dysfunction and fluctuating levels of consciousness. POD is associated with prolonged hospitalization, long-term cognitive decline, reduced quality of life, and increased mortality. Despite its clinical relevance, the underlying pathophysiological mechanisms remain poorly understood, and reliable biomarkers for early prediction and prevention are lacking. OBJECTIVE: The CONFUSED study aims to identify molecular and clinical predictors of POD by integrating clinical data with proteomic, transcriptomic, and epigenetic analyses. The primary objective is to develop predictive models for POD using multimodal data. Secondary objectives include the identification of delirium-associated genes, proteins, and epigenetic signatures, as well as the exploration of patient subgroups at increased risk for POD. METHODS: CONFUSED is a prospective observational cohort study conducted at a German university hospital. Adult patients undergoing major surgery under general anesthesia will be enrolled until 100 cases of POD have been observed, which is expected to require a total sample size of approximately 200 to 300 patients. Blood samples are collected at 4 predefined time points: before premedication, immediately after surgery, and on postoperative days 2 and 5. Samples undergo comprehensive proteomic profiling, transcriptomic analysis using RNA microarrays, DNA methylation analysis, and genotyping of selected polymorphisms. Clinical data, including demographics, comorbidities, perioperative variables, medications, and delirium assessments using the Confusion Assessment Method (CAM) and CAM for the intensive care unit, are systematically recorded. Statistical analyses include univariate and multivariate methods, as well as machine learning approaches such as random forests and support vector machines, to identify relevant biomarkers and develop predictive models. The study protocol follows STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guidelines and was approved by the responsible ethics committees. RESULTS: The study was registered in the German Clinical Trials Register (DRKS00033854) on March 18, 2024. Recruitment started in January 2024 and is ongoing at the time of manuscript submission. As of now, 135 patients have been enrolled. Sample collection and laboratory analyses are ongoing. Data analysis began in January 2026, with first results anticipated in July 2026. Final data lock is anticipated after the completion of recruitment. CONCLUSIONS: By integrating multimodal molecular data with clinical parameters and applying advanced machine learning techniques, the CONFUSED study aims to improve the prediction and understanding of POD. The results are expected to support the development of personalized preventive strategies and contribute to improved perioperative care for patients at risk of POD.
26 May 2026
Read appraisal →Circulation journal : official journal of the Japanese Circulation Society
A Phase 2, Randomized, Clinical Trial of Inhaled Nitric Oxide for Acute Severe Right Heart Failure With Pulmonary Hypertension (PHiNO Study)
BACKGROUND: Acute right heart failure (RHF) is life threatening in patients with pulmonary hypertension (PH). This study investigated the efficacy and safety of inhaled nitric oxide (iNO; INOflo®for inhalation 800 ppm), a rapid pulmonary vasodilator, in patients with acute severe RHF due to PH. METHODS AND RESULTS: In this Phase 2 randomized controlled trial, 30 patients with acute severe RHF due to PH (pulmonary arterial hypertension or chronic thromboembolic PH) were randomized 1 : 1 to either an iNO or control group (which did not receive iNO). The primary endpoint was the change in pulmonary vascular resistance (PVR) from baseline to 30 min after either iNO initiation or patient registration and assignment (control group), which differed significantly between the iNO and control groups (mean [±SD] -2.41±2.47 vs. 0.8±1.03 Wood units, respectively; between group difference -3.21 [95% confidence interval -4.633, -1.785] Wood units). Serum B-type natriuretic peptide (BNP) levels and inferior vena cava diameter (secondary endpoints) decreased significantly in the iNO group over the 7-day study period. No serious adverse events, including methemoglobinemia, were observed. CONCLUSIONS: iNO significantly reduced PVR in patients with acute severe RHF due to PH, without serious adverse events. Serum BNP levels and inferior vena cava diameter improved in the iNO group. These findings suggest that iNO is a promising acute treatment option for RHF due to PH.
25 May 2026
Read appraisal →Annals of medicine
Association between packed red blood cell transfusion and clinical deterioration in neonatal necrotizing enterocolitis: a systematic review and meta-analysis
BACKGROUND: No systematic review has evaluated the existing evidence regarding the association between packed red blood cell (pRBC) transfusion and clinical worsening of necrotizing enterocolitis (NEC) in neonates. This systematic review and meta-analysis was conducted to address this knowledge gap. MATERIALS AND METHODS: We searched the Cochrane Library, EBSCO, Embase, Web of Science, Google Scholar, and PubMed for studies on pRBC transfusion and NEC published before May 10, 2025. Relevant articles were selected through title, abstract, and full-text screening. English-language case-control studies or cohort studies, or randomized controlled trials involving newborns with NEC that compared pRBC transfusion with no transfusion and reported changes in NEC clinical status were included. Review articles, systematic reviews, case reports, editorials, animal studies, duplicate publications, and studies with incomplete data were excluded. RESULTS: Five studies involving 971 neonates with NEC were included. The pooled analysis demonstrated a potential association between pRBC transfusion and clinical deterioration of NEC in neonates (odds ratio: 6.05, 95% confidence interval: 3.02-12.14). CONCLUSIONS: pRBC transfusion was associated with an exacerbation of NEC in neonates. However, these findings should be interpreted cautiously because of the small number of eligible studies included in this meta-analysis, and future large-scale, well-designed studies are needed to confirm the observed association. Published studies have identified an association between pRBC transfusion and NEC progression; however, whether this association is causal remains unclear.Despite consistent evidence from observational studies suggesting a potential association between pRBC transfusion and NEC progression, the overall quality of the evidence is low because of the lack of randomized controlled trials to determine causality.
25 May 2026
Read appraisal →The Cochrane database of systematic reviews
Early erythropoiesis-stimulating agents in preterm or low-birthweight infants
RATIONALE: Preterm and low-birthweight infants are at risk of anemia due to a variety of factors, including low levels of erythropoietin. They may therefore benefit from erythropoiesis-stimulating agents (ESAs). However, controversy remains about their effectiveness and safety, not only in reducing blood transfusions but also in improving clinical outcomes. OBJECTIVES: To assess the benefits and harms of early administration of ESAs in preterm or low-birthweight infants. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, Scopus, DOAJ, and trial registries to 31 March 2025, and checked the reference lists of studies and systematic reviews for potentially relevant studies. ELIGIBILITY CRITERIA: Randomized controlled trials (RCTs) comparing early (initiated before eight days of life) ESAs (erythropoietin or darbepoetin) to placebo or no intervention among preterm (< 37 weeks' gestation) or low-birthweight (< 2500 g) infants. OUTCOMES: Outcomes included mortality during initial hospital stay (all-cause mortality), moderate to severe neurodevelopmental impairment (NDI) at 18 to 26 months' corrected age, proportion of infants exposed to one or more red blood cell (RBC) transfusions, retinopathy of prematurity (ROP), necrotizing enterocolitis (NEC), and severe intraventricular hemorrhage (sIVH). RISK OF BIAS: We used the Cochrane RoB 1 tool to assess risk of bias. SYNTHESIS METHODS: We performed data collection and analyses according to the methods of Cochrane Neonatal (fixed-effect meta-analysis using the inverse-variance method). We analyzed categorical data using risk ratio (RR) and continuous data using mean difference (MD), and reported the 95% confidence interval (CI) on all estimates. We used GRADE to assess the certainty of evidence. INCLUDED STUDIES: We included 37 studies (n = 6724), five (n = 3052) of which are new. Two studies (n = 752) investigated darbepoetin, and 35 studies (n = 5972) investigated erythropoietin. SYNTHESIS OF RESULTS: ESAs compared to placebo or no intervention Mortality: ESAs probably result in little to no difference in mortality during initial hospital stay (RR 0.93, 95% CI 0.80 to 1.09; I² = 0%; 24 studies, 5217 participants; moderate-certainty evidence). Subgroup analysis suggests that early use of erythropoietin probably results in little to no difference in mortality (RR 0.91, 95% CI 0.77 to 1.09; I² = 0%; 23 studies, 4505 participants), and early use of darbepoetin probably results in little to no difference in mortality (RR 1.00, 95% CI 0.71 to 1.43; I² = 0%; 2 studies, 712 participants). NDI: ESAs may reduce moderate to severe NDI at 18 to 26 months' corrected age (RR 0.81, 95% CI 0.68 to 0.95; I² = 86%; 3 studies, 1707 participants; low-certainty evidence). Subgroup analysis suggests that early use of erythropoietin may reduce moderate to severe NDI at 18 to 26 months' corrected age (RR 0.79, 95% CI 0.66 to 0.95; I² = 93%; 2 studies, 1239 participants), while early use of darbepoetin may result in little to no difference in moderate to severe NDI at 18 to 26 months' corrected age (RR 0.87, 95% CI 0.59 to 1.28; I² not applicable; 1 study, 468 participants). Transfusions: ESAs may reduce the proportion of infants exposed to one or more RBC transfusions (RR 0.79, 95% CI 0.76 to 0.83; I² = 56%; 21 studies, 3507 participants; low-certainty evidence). Subgroup analysis suggests that erythropoietin may reduce the proportion of infants exposed to one or more RBC transfusions (RR 0.80, 95% CI 0.76 to 0.84; I² = 56%; 20 studies, 2795 participants); darbepoetin may reduce the proportion of infants exposed to one or more RBC transfusions (RR 0.75, 95% CI 0.68 to 0.84; I² = 0%; 2 studies, 712 participants). ROP (any stage): ESAs result in little to no difference in incidence of ROP (RR 0.91, 95% CI 0.83 to 1.00; I² = 0%; 14 studies, 3844 participants; high-certainty evidence). Subgroup analysis suggests the use of either erythropoietin (RR 0.92, 95% CI 0.84 to 1.02; I² = 0%; 13 studies, 3230 participants) or darbepoetin (RR 0.83, 95% CI 0.58 to 1.17; I² = 0%; 2 studies, 614 participants) results in little to no difference in incidence of ROP. NEC (any stage): ESAs probably reduce the incidence of NEC (RR 0.74, 95% CI 0.62 to 0.87; I² = 0%; 20 studies, 5749 participants; moderate-certainty evidence). Subgroup analysis suggests that early use of erythropoietin probably reduces the incidence of NEC (RR 0.72, 95% CI 0.61 to 0.85; I² = 0%; 19 studies, 5041 participants), while early use of darbepoetin probably results in little to no difference in incidence of NEC (RR 1.08, 95% CI 0.54 to 2.15; I² = 0%; 2 studies, 708 participants). sIVH (grade ≥ 3): ESAs probably reduce the incidence of sIVH (RR 0.70, 95% CI 0.56 to 0.89; I² = 43%; 9 studies, 2458 participants; moderate-certainty evidence). Subgroup analysis suggests that early use of erythropoietin probably reduces the incidence of sIVH (RR 0.72, 95% CI 0.57 to 0.91; I² = 47%; 9 studies, 2396 participants), while early use of darbepoetin probably results in little to no difference in incidence of sIVH (RR 0.40, 95% CI 0.11 to 1.41; I² not applicable; 1 study, 62 participants). Of note, the test for subgroup differences between erythropoietin and darbepoetin revealed no evidence of a difference for the outcomes of mortality, moderate to severe NDI, NEC, sIVH, ROP, and the proportion of infants exposed to RBC transfusion. We downgraded the certainty of evidence for inconsistency, imprecision, and high risk of bias in the included studies. AUTHORS' CONCLUSIONS: Early use of ESAs probably results in little to no difference in mortality (moderate-certainty evidence); may reduce moderate to severe NDI at 18 to 26 months' corrected age (low-certainty evidence); has little to no effect on ROP (high-certainty evidence); may reduce the proportion of infants exposed to one or more RBC transfusions (low-certainty evidence); and probably reduces both NEC and sIVH (moderate-certainty evidence). Given the benefits of ESAs, future research should focus on cost-effectiveness, equity, feasibility of implementation, and acceptability to different stakeholders of the routine use of erythropoietin or darbepoetin among preterm or low-birthweight infants. FUNDING: No funding was received for this review. REGISTRATION: Protocol (and previous versions) available via 10.1002/14651858.CD004863; 10.1002/14651858.CD004863.pub2; 10.1002/14651858.CD004863.pub3; 10.1002/14651858.CD004863.pub4; 10.1002/14651858.cd004863.pub5; 10.1002/14651858.CD004863.pub6.
25 May 2026
Read appraisal →Medicine
Nomogram and machine learning models for predicting the risk of delirium in ICU patients with NSTEMI
Delirium is a frequent and clinically consequential complication among patients admitted to the intensive care unit (ICU). Early risk stratification in patients with non-ST-segment elevation myocardial infarction (NSTEMI) remains challenging. We aimed to develop and validate prediction models for ICU delirium in NSTEMI patients using Boruta-based feature selection and machine learning (ML) approaches, and to compare ML performance with a nomogram model. We retrospectively identified adult ICU patients (≥ 18 years) diagnosed with NSTEMI in the Medical Information Mart for Intensive Care IV database, and included only those with no delirium within the first 24 hours of admission and no prior history of delirium. A total of 392 patients were included (mean age 72.2 ± 12.6 years; 64% male) and categorized into a delirium group (n = 201) and a non-delirium group (n = 191). Clinical characteristics and laboratory indices were extracted. Participants were randomly split into a training cohort (70%) and a validation cohort (30%). The Boruta algorithm was applied in the training cohort for feature selection and identification of relevant predictors. A nomogram was constructed using Boruta-selected variables. In parallel, the same features were incorporated into ML models; model discrimination and clinical utility were evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis. SHapley Additive exPlanations were used to quantify and visualize feature contributions for the best-performing model. Boruta identified 9 key variables: systolic blood pressure, serum calcium, pulse oximetry, serum sodium, creatinine, serum chloride, anion gap, blood urea nitrogen, and body temperature. In the validation cohort, CatBoost achieved the best discrimination among ML models, with an area under the receiver operating characteristic curve of 0.743 (95% CI = 0.653-0.833). The nomogram demonstrated lower discrimination (validation area under the curve = 0.61). SHapley Additive exPlanations analyses indicated that the Boruta-selected variables contributed differentially to delirium prediction, supporting model interpretability. In ICU patients with NSTEMI, a Boruta-informed CatBoost model showed moderate predictive performance and outperformed a nomogram constructed from the same predictors. This interpretable ML approach may facilitate early identification of patients at high risk of delirium and support timely preventive strategies.
24 May 2026
Read appraisal →Studies in health technology and informatics
AI-Integrated EEG Decision Support for Neurocritical Care: A Conceptual and Feasibility Framework
The clinical use of electroencephalography (EEG) for neuro-prognostication in neurocritical care remains limited, despite its ability to provide non-invasive insight into brain activity. This study presents a conceptual framework and early-stage prototype of an AI-assisted EEG decision-support system. Using a literature-informed design and system architecture approach, a web-based prototype was developed to support automated EEG analysis and interpretable brain response reporting. Feasibility testing with four users demonstrated reliable system operation and generation of within-patient decision-support indicators. We highlight the system design and feasibility of operationalizing EEG-based analytics into a clinically interpretable decision-support framework for neurocritical care.
24 May 2026
Read appraisal →Journal of medical economics
A systematic review of acute and long-term outcomes in patients with non-transvenous implantable cardioverter-defibrillators
BACKGROUND: Non-transvenous implantable cardioverter-defibrillator (ICD) systems have been developed to address limitations of transvenous ICDs. This systematic literature review aimed to summarize periprocedural and long-term outcomes of non-transvenous ICD systems in adult patients with guideline-based indications for ICD therapy. METHODS: A systematic review was conducted in accordance with PRISMA guidelines (PROSPERO: CRD420261327618). Eligible studies enrolled adults (≥18 years) receiving a non-transvenous ICD for primary or secondary prevention. Outcomes included periprocedural and long-term endpoints and were summarized descriptively. The Newcastle-Ottawa Scale (NOS) and Joanna Briggs Institute (JBI) checklist for case series were used to assess risk of bias. RESULTS: Twenty-five publications representing 18 unique studies and 4,633 patients were included. Most studies were single-arm (n = 13), while 2 were randomized controlled trials and 3 were nonrandomized comparative studies. Procedural success ranged from 81%-100%, with rates ≥94% of patients in all but one early-phase study; defibrillation threshold testing success ranged from 89%-100% (≥96% in studies with n ≥ 100). Periprocedural complications were reported in 0%-5% of patients in most studies. Long-term complication rates ranged from 0%-8% at 0.5-1.5 years of follow-up and 1%-14% beyond 1.5 years. All-cause mortality ranged from 1%-5% within 6 months and increased to 16%-26% at 4-8 years. Clinical defibrillation success was consistently high (95%-100%). Incidence of inappropriate shock generally ranged from 7%-13% at 1 year and 2%-18% at later timepoints. Appropriate shock incidence ranged from 2% to 9% within 1 year and increased with longer follow-up. Risk of bias was predominantly moderate, with limited variation using NOS and greater discrimination observed with JBI. CONCLUSIONS: Non-transvenous ICD systems demonstrate favorable safety and effectiveness profiles, with high procedural and defibrillation success and acceptable complication and inappropriate shock rates across studies. Overall, the available evidence supports their use in appropriately selected adult patients with standard ICD indications. Non-transvenous implantable cardioverter-defibrillators (ICDs) are devices placed outside the blood vessels and heart, designed to treat life-threatening heart rhythm problems while avoiding complications related to transvenous ICDs.This review summarized results from 25 published studies including 4,600 patients to understand how safe and effective these devices are.Across studies, non-transvenous ICDs showed high implant procedure success, effective therapy delivery, and had generally low rates of short- and long-term complications.
23 May 2026
Read appraisal →BMJ evidence-based medicine
Comparative effects of early physical interventions on preventing intensive care unit-acquired weakness: a systematic review and component network meta-analysis
OBJECTIVE: To compare the effects of early physical interventions on the prevention of intensive care unit-acquired weakness (ICUAW) and the improvement of relevant clinical outcomes in patients with critical illness. METHODS: We systematically searched the Web of Science, PubMed, Embase and the Cochrane Central Register of Controlled Trials from their inception until 20 August 2024, to identify randomised controlled trials (RCTs) enrolling patients ≥18 years old and implementing early physical intervention that commenced at any time point during mechanical ventilation (MV) use or within 7 days after intensive care unit (ICU) admission for review. We synthesised data using a random-effects model and analysed through network meta-analysis (NMA) and component network meta-analysis (CNMA). MAIN OUTCOME MEASURES: Primary outcome is the incidence of ICUAW. Secondary outcomes included Medical Research Council sum score, length of stay in the ICU or hospital, duration of MV and mortality rates in the ICU or hospital. RESULTS: Our analyses included 63 RCTs involving 24 treatments and eight components. The NMA results revealed systematic early mobilisation (SEM) combined with neuromuscular electrical stimulation (NMES), SEM alone and NMES alone may lead to a moderate to large reduction in the incidence of ICUAW (odds ratios [ORs]=0.03, 0.09 and 0.12, 95% confidence intervals [CIs]=0.00 to 0.42, 0.01 to 0.97 and 0.03 to 0.44, respectively) and improved relevant clinical outcomes compared with routine care. The CNMA results further indicated that SEM (OR=0.14, 95% CI=0.02 to 0.83) and NMES (OR=0.22, 95% CI=0.09 to 0.52) effectively mitigated the ICUAW incidence. CONCLUSIONS: SEM and NMES are optimal interventions for preventing ICUAW. Healthcare providers in ICUs should implement early mobilisation with structured protocols and patient assessments or apply NMES to specific muscle groups to prevent ICUAW in critically ill patients and improve relevant clinical outcomes. PROSPERO REGISTRATION NUMBER: CRD42024581173.
23 May 2026
Read appraisal →Circulation
Prehospital Heparin Administration in Patients With STEMI Undergoing Primary PCI: HEPARIN-STEMI Randomized Controlled Trial
BACKGROUND: Primary percutaneous coronary intervention (PCI) is the preferred reperfusion strategy for patients with ST-segment-elevation myocardial infarction (STEMI). We investigated the benefits and safety of pretreatment with unfractionated heparin (UFH) in patients with STEMI referred to primary PCI. METHODS: In HEPARIN-STEMI (Pretreatment With Unfractionated Heparin for ST Elevation Myocardial Infarction)-a single-center, open-label, randomized controlled trial-patients with STEMI with ≤6 hours symptom duration were assigned to receive either a 70- to 100-IE/kg bolus of UFH at first prehospital medical contact plus a supplemental dose before PCI, adjusted to activated clothing time ≥250 seconds, or to a control group receiving standard UFH at the time of PCI. The primary efficacy end point was TIMI (Thrombolysis in Myocardial Infarction) flow grade 2-3 in the infarct-related artery at initial coronary angiography. The primary safety end point was BARC (Bleeding Academic Research Consortium) type 3-5 bleeding during the index hospital stay. RESULTS: From March 2022 to February 2025, 298 patients were randomized to UFH pretreatment and 295 to the control group. The groups were comparable in age, sex, risk factors, previous cardiovascular events, and median delay from symptoms to coronary angiography (145 versus 150 minutes; P=0.814). The median time from UFH pretreatment to coronary angiography was 60 minutes (25th-75th interquartile range, 47-55 minutes). TIMI flow grade 2-3 in the infarct-related artery was documented in 43% of patients with UFH pretreatment and 27% of patients in the control group (relative risk, 1.59 [95% CI, 1.27-1.98]; P<0.001), with no significant difference in BARC type 3-5 bleeding (2.4% versus 2.0%; relative risk, 1.16 [95% CI, 0.39-3.45]; P=0.789). CONCLUSIONS: In patients with STEMI undergoing primary PCI, in a mature STEMI network, pretreatment with UFH at first prehospital medical contact was associated with an absolute 16% increase in infarct-related artery patency without an increased risk of bleeding. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05247424.
19 May 2026
Read appraisal →Journal of neurology
Diagnostic and prognostic value of blood neurofilament light chain in ischemic stroke: an individual patient data meta-analysis
BACKGROUND: We aimed to conduct an individual patient data meta-analysis on blood neurofilament light chain (NfL) in ischemic stroke (IS) to enhance its clinical applicability. METHODS: We performed a systematic literature search of studies on blood NfL measured in adult patients within 30 days after IS onset and derived age- and BMI-adjusted Z-scores based on a previously published reference population of healthy controls. We collected clinical, radiological and biochemical parameters of IS patients and tested associations of NfL at defined timepoints after IS onset (D1: < 24 h; D2: 24-48 h; D3: 48-72 h; D4-5: 72-120 h; D6-7: 120-168 h; D8-30: > 168 h) with baseline characteristics and 3-month follow-up outcomes (modified Rankin Scale, mRS; survival). RESULTS: We included 4081 blood NfL values from 2872 participants (IS n = 1985, transient ischemic attack n = 88, healthy controls n = 799) of 18 published studies and 3 unpublished cohorts. In patients with IS, NfL Z-score progressively increased from D1 [median: 2.0 (IQR: 0.9-2.9)] to D6-7 [median: 3.5 (IQR: 3.0-3.8)], with discriminative ability being high for IS vs. controls (AUC: 0.79-0.97) and fair for IS vs. TIA (AUC: 0.64-0.80). Higher NfL Z-score at D1 was associated with greater risk of symptomatic intracranial hemorrhage (aOR = 1.33, p = 0.014) and, from D2 onwards, with larger infarct lesion volume (highest Spearman's rho: 0.795 at D6-7). NfL independently predicted a mRS > 2 (aOR = 1.31, p < 0.001) and mortality (aOR = 1.67, p < 0.001) at 3 months. CONCLUSIONS: Blood NfL level was progressively elevated after IS, could discriminate IS from healthy controls with high accuracy and had prognostic value for intra-hospital complications and 3-month clinical outcomes in IS.
18 May 2026
Read appraisal →JMIR medical informatics
Development Process of a Clinical Decision Support System for Empiric Antibiotic Therapies in Patients With Sepsis: Case Study
BACKGROUND: Antibiotic therapies are the main treatment for bacterial infections, but growing antibiotic resistance is a major global health threat, severely impacting patients with sepsis. Rapid selection of the most effective antibiotic therapy is critical for survival and for preventing further resistance. Physicians must consider numerous factors for proper empiric treatment selection. A clinical decision support system (CDSS) aims to support physicians in this process, facilitating rapid and targeted therapy. OBJECTIVE: The purpose of this work is to explore the extent to which the realization of a CDSS is possible based on the data available to us and to document insights gained during the development of a foundational model designed to assist physicians in determining empiric treatment options for patients with sepsis. In this regard, rather than aiming to develop a CDSS for clinical application, we highlight the importance of close interprofessional collaboration between scientists from various disciplines and analyze the effects of data quality and quantity on the performance of our statistical models. METHODS: Empirical scientists conducted interviews with medical practitioners to acquire the medical knowledge required to develop sound statistical models. We developed and applied 2-step cross-sectional, as well as time-series classification models, to carefully preprocessed data of patients with sepsis admitted to the intensive care unit of a German hospital. RESULTS: We identified several factors as crucial information for valid decisions on empiric therapy for treating patients with sepsis. These include the patients' core data, especially the infection focus. To prevent further resistance, individual risk factors such as travel history and professional background should be considered. The evaluation of a therapy's effectiveness is mainly based on the patient's general condition and blood values such as procalcitonin and interleukin 6. One key factor in the acceptance of a CDSS is the explainability of the results produced by the applied methods. Our models demonstrated mainly weak predictive ability for all considered empiric antibiotic therapies. However, they are not yet suitable for use in clinical practice, especially as they are based on prescribing habits rather than on optimal treatment decisions. CONCLUSIONS: This work highlights the importance of interprofessional collaboration between medical experts and model developers, ensuring that data quality and clinical relevance are central to the process. It emphasizes the urgent need for high-quality, comprehensive data to overcome challenges such as data discontinuity and improve model performance, particularly through enhanced digitization in health care. This feasibility study will facilitate future efforts to develop a CDSS for treating patients with sepsis and to translate it into clinical use.
15 May 2026
Read appraisal →Journal of clinical microbiology
Diagnostic performance of β-(1→3)-D-glucan, two Candida antigen, and five anti-Candida antibody assays in ICU patients with sepsis and high risk for invasive candidiasis: a secondary endpoint of the CandiSep randomized clinical trial
Invasive Candida infection (ICI) is the most common fungal infection in critically ill patients. This study analyzed the performance of various biomarkers in sera from the CandiSep trial, a randomized, multicenter trial including 342 sepsis patients at high risk for ICI across 18 German intensive care units. ICI and candidemia were diagnosed in 48 (14.0%) and 14 (4.1%) patients, respectively. Sera collected on 2 consecutive days at sepsis onset were analyzed for β-(1→3)-D-glucan (BDG; Fungitell), mannan (Platelia-Candida-Ag-Plus [Platelia-Mn] and Serion-ELISA-antigen-Candida [Serion-Mn]), and anti-Candida antibodies (Platelia-Candida-Ab-Plus, Serion-ELISA-Candida albicans-IgA/IgM/IgG, and Virclia-Candida albicans-germ-tube-antibody-IgG-Monotest). Only antigen levels (BDG, Platelia-Mn, Serion-Mn), but not anti-Candida antibody levels, were significantly elevated in ICI patients. Antigen levels were unaffected by Candida colonization, while antibody levels were significantly increased. Sensitivity and specificity at the manufacturer's cutoffs were unsatisfactory. Performance improved by adjusting cutoffs: BDG required a 3-fold increase, while all others required lowering. At 80% specificity, sensitivities (95% confidence intervals) for the diagnosis of ICI and candidemia were as follows: BDG (cutoff >280 pg/mL), 46% (31.4-60.8) and 64% (35.1-87.2); Platelia-Mn (cutoff >50 pg/mL), 38% (24.0-52.6) and 64% (35.1-87.2); Serion-Mn (cutoff >0.7 U/mL), 38% (24.0-52.6) and 50% (23.0-77.0), and below 28% and 43% for all antibody assays. Area under the receiver operating characteristic curve comparisons showed no significant differences between antigen assays. Combining biomarkers, either simultaneously or sequentially, offered no diagnostic advantage over single-biomarker use. In conclusion, anti-Candida antibody assays are likely influenced by colonization and have limited diagnostic utility. Antigen assays offer similar diagnostic value but require cutoff optimization. Combining biomarkers did not enhance diagnostic yield in our cohort.IMPORTANCEOur main findings based on our specific ICU cohort were as follows: (i) only Candida antigen levels, not anti-Candida antibody levels, were significantly elevated in ICI and candidemia. (ii) In patients without ICI, Candida colonization was not associated with altered antigen levels, but with elevated antibody levels. (iii) Sensitivity and specificity at the manufacturer's cutoffs were unsatisfactory, and cutoffs should be significantly adjusted. Potential optimal cutoff values are proposed by us. (iv) The evaluated antigen assays demonstrated overall comparable diagnostic performance in this study. (v) Anti-Candida antibody assays did not provide a meaningful diagnostic contribution. (vi) The combination of biomarkers offered no diagnostic advantage over the use of individual biomarkers, neither simultaneously nor sequentially. Our results suggest that the use of a single Candida antigen test with a cohort-adapted cutoff value may be sufficient. Furthermore, avoiding biomarker combinations could potentially reduce healthcare costs. The clinical implications of these findings should be interpreted with caution, given the limited data with associated large confidence intervals for candidemia and the cohort-specific nature of the study. Our results should therefore be confirmed in larger studies and additionally with other patient groups.
15 May 2026
Read appraisal →Med (New York, N.Y.)
Evaluation of recombinant human prourokinase for acute pulmonary embolism: A phase 2, randomized clinical trial
BACKGROUND: Recombinant human prourokinase (rhPro-UK) is a novel plasminogen activator under investigation for acute pulmonary embolism (aPE). We aimed to explore the efficacy and safety of rhPro-UK vs. alteplase (recombinant tissue plasminogen activator [rt-PA]) in patients with aPE. METHODS: In this phase 2, randomized, single-blind, multicenter, active-controlled, randomized trial involved eighteen centers from university-affiliated tertiary hospitals across China. Patients aged 18-75 years with high or intermediate-to-high risk aPE were randomized to receive intravenous rhPro-UK (40 mg, n = 37; 50 mg, n = 35) or rt-PA (n = 35) and were followed for 7-30 days. The primary efficacy outcome was the change from baseline in systolic pulmonary artery pressure (sPAP) at 24 h post-treatment. Secondary outcomes include changes in right ventricular function parameters. Safety outcomes include all-cause mortality, recurrent PE, hemodynamic deterioration within 7 days, and bleeding events within 30 days. FINDINGS: All treatment groups showed a reduction in sPAP at 24 h (mean change: 40 mg rhPro-UK, -13.40 mmHg [95% confidence interval (CI): -24.10 to -2.71]; 50 mg rhPro-UK, -15.42 mmHg [95% CI: -25.93 to -4.91], and rt-PA: -16.02 mmHg [95% CI: -25.53 to -6.51]), with improvements sustained through 30 days. The incidence of non-major bleeding events was numerically lower in the rhPro-UK groups (40 mg: 63.9%; 50 mg: 55.6%) compared to the rt-PA group (82.9%; p = 0.04). Two deaths occurred, each in the 40 mg rhPro-UK group and rt-PA group. CONCLUSION: rhPro-UK tended to result in early hemodynamic improvement comparable to rt-PA and seemed to have a numerically lower risk of non-major bleeding events. The ClinicalTrials.gov identifier is NCT03108833. FUNDING: This work was funded by Tasly Biopharmaceuticals Co., Ltd.
12 May 2026
Read appraisal →The New England journal of medicine
Left Ventricular Unloading in High-Risk Percutaneous Coronary Intervention
BACKGROUND: Complex percutaneous coronary intervention (PCI) in patients with severely impaired left ventricular function carries a high risk of death and complications. Whether percutaneous left ventricular unloading improves outcomes remains unclear. METHODS: We randomly assigned 300 patients with severe left ventricular dysfunction and extensive coronary artery disease in a 1:1 ratio to a strategy of elective unloading with a microaxial flow pump or to standard care during planned complex PCI. The primary outcome was a hierarchical composite that included death from any cause, disabling stroke, spontaneous myocardial infarction, hospitalization for cardiovascular causes, or periprocedural myocardial injury at a minimum of 12 months, as analyzed according to a win ratio. RESULTS: A total of 148 patients were assigned to receive a microaxial flow pump and 152 to receive standard care. At a median of 22 months (interquartile range, 16 to 30), 36.6% of pairwise comparisons favored the microaxial flow pump, and 43.0% favored standard care (win ratio, 0.85; 95% confidence interval [CI], 0.63 to 1.15; difference, -6.4 percentage points; P = 0.30). Death from any cause occurred in 47 patients in the microaxial-flow-pump group and 33 in the standard-care group (hazard ratio, 1.54; 95% CI, 0.99 to 2.41). There was no material between-group difference in the risk of bleeding or vascular complications. CONCLUSIONS: Among patients with severely impaired left ventricular function undergoing complex PCI, elective left ventricular unloading with a microaxial flow pump did not reduce the risk of major adverse clinical outcomes at a minimum of 12 months. (Funded by the U.K. National Institute for Health and Care Research; CHIP-BCIS3 ClinicalTrials.gov number, NCT05003817.).
12 May 2026
Read appraisal →European journal of pediatrics
Post-asphyxia acute kidney injury in neonates: a systematic review
UNLABELLED: Perinatal asphyxia is a major cause of neonatal morbidity and mortality globally. It affects multi-systems and has significant renal consequences. Acute kidney injury (AKI) is a frequent complication of perinatal asphyxia; however, its burden, diagnosis, and outcomes remain variably characterized. This study employed a scoping review approach to map and synthesize the existing evidence on post-asphyxia AKI in neonates. A total of 30 studies published between 1995 and 2025 were included, encompassing different geographic regions, study designs, and diagnostic criteria. The review demonstrates a clear growth in scholarly attention to post-asphyxia AKI, particularly in the last 25 years, coinciding with the introduction of neonatal-modified KDIGO definitions and advances in neonatal nephrology. Reported incidence of AKI varied widely, ranging from 20% to over 60%, reflecting non-homogeneity in study populations, differing case definitions of acute kidney injury in neonates, the severities of hypoxic-ischemic encephalopathy, and varied methodological approaches. Findings consistently indicate that AKI is strongly associated with severe forms of perinatal asphyxia, the presence of multi-organ dysfunction, prolonged neonatal intensive care stay, and mortality. CONCLUSION: Despite emerging interest in novel biomarkers and standard definitions, important gaps persist in early detection, long-term renal outcome data, and evidence from low- and middle-income countries. Addressing these gaps through standardized monitoring, biomarker validation, and longitudinal follow-up will improve renal survival in neonates affected by perinatal asphyxia. WHAT IS KNOWN: • The newborn kidneys are susceptible to the hemodynamic changes that follow ischemia/asphyxia due to a poor functioning capacity and oftentimes an inadequate structural potential. • Neonatal AKI is closely linked to severe forms of asphyxia, increased length of hospital stay and increased mortality. its reported incidence is widely varied. WHAT IS NEW: • The emergence of novel biomarkers in the identification and diagnosis of neonatal AKI, and the uptake and application of standard definitions (modified neonatal KDIGO) in the identification of neonatal AKI. • The availabiltiy of specialized kidney support therapy (continuous kidney replacement therapy; the carpadiem) in the management of neonatal AKI.
11 May 2026
Read appraisal →Journal of burn care & research : official publication of the American Burn Association
Metabolic and Immunomodulatory Effects of α-Ketoglutarate in Burn Injuries: A Systematic Review
Severe burns unleash a hyper-catabolic and immunosuppressive state that erodes lean tissue and delays repair. Alpha-ketoglutarate (α-KG), usually delivered enterally as the dipeptide ornithine α-ketoglutarate (OKG), feeds the tricarboxylic-acid cycle, donates nitrogen for amino-acid synthesis, and modulates collagen formation and immunity. We systematically appraised the biological mechanisms, delivery strategies, and clinical outcomes associated with α-KG/OKG in burn care to clarify its therapeutic value and translational readiness. A PRISMA-2020-compliant search of PubMed, EMBASE, Web of Science, Cochrane, and Google Scholar up to May 2025 identified clinical, in vivo, and relevant in vitro studies linking α-KG or OKG with thermal injury. Study quality was assessed using the Newcastle-Ottawa Scale, SYRCLE Risk-of-Bias tool, and Oxford Levels of Evidence. Fifteen studies published between 1984 and 2024 met inclusion criteria, including clinical, animal, and mechanistic work, most conducted in France. Across studies, OKG supplementation replenished glutamine and arginine pools, improved nitrogen balance, preserved muscle mass, and promoted wound healing through enhanced collagen synthesis and immune modulation. Clinical data confirmed improved nitrogen retention, reduced muscle breakdown, and faster wound closure. Preclinical studies further showed that α-KG preconditioning enhances stem cell-driven regeneration and vascularization. Additional effects, such as improved glucose tolerance and hepatic enzyme preservation, suggest some benefits occur independently of glutamine pathways. This review highlights α-KG and OKG as promising adjuncts to enhance metabolic recovery, wound repair, and immune competence after burns. Evidence supports improved nitrogen balance and healing, but findings remain limited by heterogeneity and small cohorts, warranting renewed and well-powered studies.
11 May 2026
Read appraisal →PloS one
Development and evaluation of an ontology for non-invasive respiratory support in acute care
Managing patients with respiratory failure increasingly involves non-invasive respiratory support (NIRS) strategies to support respiration, often preventing the need for invasive mechanical ventilation. However, despite the rapidly expanding use of NIRS, there remains a significant challenge to its optimal use across all medical circumstances. It lacks a unified ontological structure, complicating guidance on NIRS modalities across healthcare systems. In this study, we introduced NIRS ontology to support knowledge representation in acute care settings by providing a unified framework that enhances data clarity and interoperability, laying the groundwork for future clinical decision-making research. We developed NIRS ontology using the Web Ontology Language (OWL) and Protégé to organize clinical concepts and relationships. To enable rule-based clinical reasoning beyond hierarchical structures, we added Semantic Web Rule Language (SWRL) rules. We evaluated logical reasoning using a sample of 6 patient scenarios and used SPARQL queries to retrieve and test targeted inferences. The ontology has 145 classes, 11 object properties, and 18 data properties across 949 axioms that establish concept relationships. To standardize clinical concepts, we added 392 annotations, including descriptive definitions based on controlled vocabularies. SPARQL queries successfully validated all test cases (rules) by retrieving appropriate patients' outcomes: for instance, a patient treated with HFNC (high-flow nasal cannula) for 2 hours due to acute respiratory failure may avoid endotracheal intubation. This NIRS ontology formally represents domain-specific concepts, including ventilation modalities, patient characteristics, therapy parameters, and outcomes. SPARQL query evaluations across clinical scenarios confirmed the ontology's ability to support rule‑based reasoning and therapy recommendations, providing a foundation for consistent documentation practices, integration into clinical data models, and advanced analysis of NIRS outcomes. In conclusion, this proof-of-concept NIRS ontology demonstrates how clinical concepts can be formally represented and queried, offering a foundation for future validation, EHR integration, and evidence-based refinement of NIRS practices.
11 May 2026
Read appraisal →Journal of wound care
Incidence and risk factors of medical adhesive-related skin injury among ICU patients: a systematic review and meta-analysis
OBJECTIVE: To summarise the evidence regarding the incidence and risk factors of medical adhesive-related skin injury (MARSI) among patients in the intensive care unit (ICU). METHOD: A systematic review and meta-analysis was undertaken using articles available in nine databases: PubMed; the Cochrane Library; Web of Science; Embase; CINAHL; Chinese Biomedical Literature Database; China National Knowledge Infrastructure Database; Wanfang Database; and Weipu Database, from inception until 30 June 2024. Additional studies were identified by examining the references of relevant articles. The Stata 16.0 statistical platform (StataCorp LLC, US) was used for analysis. Study quality was assessed using the Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality standards. RESULTS: Of 14,743 titles screened, 19 studies involving 5218 patients were included in the systematic review. The pooled incidence of MARSI was 21% (95% confidence interval (CI): 14%, 28%), and the incidence of MARSI among neonatal ICU, paediatric ICU and adult ICU was 15% (95% CI: 6%, 26%), 48% (95% CI: 35%, 60%) and 16% (95% CI: 11%, 22%), respectively. Significant risk factors in adult ICUs included oedema (odds ratio (OR): 8.144; 95%CI: 3.267, 20.304), Braden scale score (OR: 0.733; 95%CI: 0.641, 0.837), length of ICU stay (OR: 1.072; 95%CI: 1.026, 1.120), mechanical ventilation (OR: 3.698; 95%CI: 1.900, 7.199), sedative use (OR: 6.022; 95%CI: 2.859, 12.687), Nutritional Risk Screening 2002 score (OR: 4.241; 95%CI: 1.984, 9.065) and hypoalbuminaemia (OR: 4.321; 95%CI: 1.967, 9.488). CONCLUSION: This study found that MARSI is prevalent among ICU patients and is associated with multiple risk factors. Improved strategies for identifying and clinically managing MARSI in ICU patients are needed. Nevertheless, large-sample and multicentre studies are still warranted to validate the present study's findings.
10 May 2026
Read appraisal →Diagnostic and interventional radiology (Ankara, Turkey)
Imaging in chronic thromboembolic pulmonary hypertension: review of the current literature
Chronic thromboembolic pulmonary hypertension (CTEPH) is a severe, life-threatening complication of pulmonary embolism with pulmonary hypertension (PH). The combination of insufficient resolution of thrombi following pulmonary emboli and accompanying microvascular disease results in PH. Advances in imaging can offer better insight into CTEPH diagnosis and management, but lack of disease awareness among radiologists has been shown to be a cause of CTEPH misdiagnosis or delayed diagnosis. This review highlights features pertinent to CTEPH diagnosis. The primary focus is on different modalities with their distinctive signs and newly developed technologies employing artificial intelligence systems.
10 May 2026
Read appraisal →Journal of medical systems
Interpretable Machine Learning to Anticipate the Diagnostic Yield of EEG in the Emergency department. The EMINENCE study.
INTRODUCTION: Emergent electroencephalography (emEEG) is increasingly employed in the emergency department (ED) for evaluating altered consciousness and seizure-related conditions, yet standardized criteria guiding its use remain limited. METHODS: We retrospectively analyzed 1,018 patients (mean age 66 ± 20 years; 48.4% female) undergoing emEEG at the ED of the Careggi Teaching Hospital (Florence, Italy) in 2023. Clinical, anamnestic, and neuroimaging data available at admission were used to train supervised machine-learning (ML) models. We evaluated tree-based ensembles (Random Forest and XGBoost) to predict abnormal and epileptiform emEEG, as well as confirmation or refutation of initial diagnosis. Ground-truth labels were derived from a multidisciplinary expert team including neurologists, neurophysiopathologists and intensivists. Model performance was assessed with 5 × 5 nested cross-validation, receiver operating characteristic (ROC) analysis, balanced accuracy, decision-curve analysis, and Shapley Additive Explanations (SHAP) interpretability. RESULTS: Abnormal emEEG occurred in 691 cases (67.9%), epileptiform activity in 192 patients (18.9%). emEEG ruled out the initial diagnostic suspicion in 514 cases (50.5%) and confirmed it in 188 cases (18.5%). Best performance was obtained with Random Forest for abnormal emEEG (AUC 0.79, 95% CI: 0.76-0.82) and diagnosis rule-out (0.84, 0.81-0.86), and with XGBoost for epileptiform emEEG (0.82, 0.78-0.85) and diagnosis confirmation (0.82, 0.79-0.85). Performance varied by initial diagnostic suspicion, but subgroup-stratified analyses showed overall consistent patterns. Key predictive features included altered consciousness, prior brain lesions, antiseizure therapy, and seizure-related presentations. Interpretability analyses revealed seizure-centric features drove confirmation, while systemic or nonspecific features favored refutation. CONCLUSIONS: Interpretable ML models using only admission data can predict emEEG outcomes and anticipate their diagnostic contribution, supporting triage and decision-making in emergency neurology without replacing clinical judgment. Models and explanations were easily usable on a freely-accessible website ( www.emergencyeeg.com ), where tools return probabilistic outputs for all four prediction tasks together with per-patient explanation plots, enabling transparent and reproducible use. CLINICAL TRIAL NUMBER: Not applicable.
9 May 2026
Read appraisal →Journal of medical systems
Prognostic Modeling Based on Post-Endovascular Thrombectomy Systolic Blood Pressure Trajectories Using Explainable Artificial Intelligence: A Secondary Analysis of the OPTIMAL-BP Trial
Blood pressure (BP) management following successful reperfusion after endovascular thrombectomy (EVT) is critical in achieving favorable clinical outcomes. Individualized BP management using predictive modeling by machine learning may further improve prediction of functional outcomes. This study was a retrospective analysis of data from the Outcome in Patients Treated with Intra-Arterial Thrombectomy-Optimal Blood Pressure Control (OPTIMAL-BP) trial, a randomized controlled trial comparing between intensive and conventional BP management during the 24 h after successful recanalization by EVT from June 18, 2020, to November 28, 2022. The trial was conducted across 19 centers in South Korea. Machine learning models were developed to predict functional independence (90-day modified Rankin Scale 0 to 2). Model performance was compared between clinical variables only and systolic blood pressure (SBP) metrics in addition to clinical variables. In addition, the Shapley additive explanations (SHAP) analysis was performed to provide model explanation and understand the importance of SBP metrics. A total of 288 patients (61.1% men, median age 75 years [interquartile range, 65-81]) were included. Among the six algorithms, the deep neural network model incorporating SBP metrics performed best on validation, achieving an area under the curve of 0.86 (95% confidence interval, 0.76-0.92) which was significantly better than the model using only clinical variables (area under the curve 0.80 [95% confidence interval, 0.69-0.88], P = .037). Among SBP metrics, SHAP analysis identified time rate of SBP and minimum SBP as important features, with time rate showing greater influence in the intensive group and minimum SBP in the conventional group. Integrating SBP metrics with clinical variables significantly improved machine learning performance in predicting functional outcomes after successful EVT. Explainable artificial intelligence (AI) identified time rate and minimum SBP as key predictors of outcome. Trial Registration Information: ClinicalTrials.gov (NCT04205305; registered December 17, 2019).
9 May 2026
Read appraisal →Resuscitation
Deep learning-based ROSC prediction and ECG phenotyping in out-of-hospital cardiac arrest
INTRODUCTION: Electrocardiogram (ECG) signals during cardiac arrest contain detailed information on cardiac rhythm characteristics and have been associated with resuscitation outcomes. We aimed to develop a convolutional neural network (CNN) model to predict return of spontaneous circulation (ROSC) and identify novel ECG phenotypes in patients with out-of-hospital cardiac arrest (OHCA). METHODS: This retrospective cohort study used Korean OHCA Registry and ECG data from Seoul emergency medical services between July 2021 and December 2023. Adult patients with nontraumatic OHCA who had prehospital ECG signals were included. Five-second ECG segments obtained during resuscitation were analyzed. A one-dimensional CNN was developed to simultaneously predict the probability of ROSC within 2 min and to classify the concurrent ECG rhythm as shockable or non-shockable. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). ECG phenotypes were identified by applying K-means clustering to feature representations extracted from the trained CNN. RESULTS: 3452 patients (median age, 73 years [interquartile range, 61-81]; 34.4% female) were included. The AUCs for predicting ROSC within 2 min and shockable rhythm in the test set were 0.921 (95% confidence interval [CI], 0.897-0.945) and 0.983 (95% CI, 0.979-0.988), respectively. Five ECG phenotype categories with varying morphologies and ROSC probabilities were identified. Phenotype 1 consisted of shockable rhythms with high ROSC probability (30.4%), whereas Phenotype 2 showed shockable rhythms with low ROSC probability (4.8%). Phenotypes 3 and 4 included pulseless electrical activities with relatively high (5.2%) and lower (0.5%) ROSC probabilities, respectively. Phenotype 5 primarily consisted of asystole or near-asystole rhythms. Transitions between ECG phenotypes were associated with CPR quality. CONCLUSIONS: The CNN-based model accurately predicted ROSC and shockable rhythm from ECG signals and identified five novel ECG phenotypes in OHCA. These findings can enable accurate ROSC prediction and individualized prehospital resuscitation for patients with OHCA.
4 May 2026
Read appraisal →Journal of medical Internet research
Digital Health Interventions for Family Members of ICU Patients: Current Evidence and Future Directions
A recent systematic review and meta-analysis of randomized trials evaluating digital health interventions for family members of intensive care unit (ICU) patients found no significant improvements in anxiety, depression, posttraumatic stress, quality of life, or communication quality. Rather than concluding that digital approaches are inherently ineffective, we argue that these null findings reflect identifiable and remediable limitations in intervention design, outcome measurement, and trial methodology. In this commentary, we examine four structural barriers that currently constrain the evidence base and outline the conditions that next-generation trials must meet to adequately address the questions raised by this review.
4 May 2026
Read appraisal →Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Bacterial quantitation in clinical infection: a systematic review
Pivotal clinical studies of new anti-infective drugs enrol patients with strictly defined clinical syndromes, with clinical and laboratory endpoints used to define treatment success. Assessing bacterial killing in the host by serial quantitation has potential as a more efficient pharmacometric approach to assess antibiotic efficacy. We conducted a systematic review of the use of bacterial quantitation in clinical infection. The main syndromes studied in the 222 included articles were bacteraemia, chronic respiratory disease, diarrhoea, pneumonia and sexually transmitted infections. Most reports (135 articles, 61%) quantified bacterial load in different specimen types using quantitative polymerase chain reaction (qPCR). For bacteraemias, bacterial DNA load measured in whole blood by qPCR at clinical presentation was typically 2-3 log10 copies ml-1, usually substantially higher than the estimates from quantitative culture. Higher bacterial loads were associated with increased mortality in 28 of 35 studies. Faster bacterial clearance was correlated with appropriate antibiotic therapy and improved outcome in the majority of studies. Most studies sampled too infrequently for accurate characterization of bacterial clearance rates. The rate of bacterial clearance from blood or other compartments is an informative pharmacodynamic endpoint in the assessment of antibacterial therapeutic effects, but standardized approaches to assessment are needed based on optimal study design. This article is part of the Theo Murphy meeting issue 'Evaluating anti-infective drugs'.
3 May 2026
Read appraisal →Biomedizinische Technik. Biomedical engineering
Blood pressure estimation using single photoplethysmography signal based on ResNet-BiGRU
OBJECTIVES: Conventional cuff-based blood pressure (BP) measurement provides only intermittent readings, whereas photoplethysmography (PPG)-based methods enable continuous and noninvasive monitoring. This study aims to develop a deep learning framework for accurate, cuffless BP estimation using a single PPG signal. METHODS: A hybrid deep neural network, termed ResNet-BiGRU, was developed by integrating residual convolutional blocks with bidirectional gated recurrent units to jointly capture morphological and temporal features. The UCI Cuff-Less Blood Pressure Estimation Dataset (a subset of MIMIC-II), which contains synchronized PPG and arterial blood pressure (ABP) signals from 942 subjects, was used for model training and validation. After applying a 0.5-8 Hz bandpass filter and segmenting into 5 s windows, the data were split 80/20 for training and validation. External evaluation was conducted using the VitalDB dataset, which provides synchronized PPG and ABP recordings from surgical patients under diverse physiological conditions. RESULTS: The model achieved mean absolute errors (MAE) of 4.78 mmHg for systolic BP (SBP) and 2.98 mmHg for diastolic BP (DBP) on UCI, and 8.15 mmHg for SBP and 4.59 mmHg for DBP on VitalDB. CONCLUSIONS: The ResNet-BiGRU model demonstrates accurate, robust, and generalizable cuffless BP estimation, showing strong potential for wearable health monitoring applications.
28 Apr 2026
Read appraisal →Nutricion hospitalaria
Refeeding syndrome ‒ What we know and what remains to be explored.
Background: refeeding syndrome (RS) is a serious metabolic complication that occurs upon reintroducing nutrition to malnourished individuals. Although formally recognized for more than 70 years, significant gaps in its understanding remain. Objective: to conduct a narrative review on the current state of knowledge regarding RS, its recent advances, existing gaps, and future perspectives. Methods: an integrative review was conducted using articles published between 2000 and 2024 from international databases, following a systematic methodology of literature search, selection, and analysis. Results: the main pathophysiological mechanisms of RS, its multisystemic clinical manifestations, current diagnostic criteria, and risk-based therapeutic strategies were identified. Despite advances in biomarkers and personalized nutrition, challenges remain in early diagnosis, prevention, and treatment, especially in vulnerable populations. Conclusions: RS continues to pose a complex clinical challenge that requires standardized protocols, identification of reliable biomarkers, and increased clinical research, particularly in underrepresented regions such as Latin America. Prevention, based on a multidisciplinary approach, is important to reducing its impact. Introducción: el síndrome de realimentación (SR) es una complicación metabólica grave que ocurre tras reintroducir la nutrición en personas desnutridas. Aunque formalmente reconocido desde hace más de 70 años, aún existen importantes lagunas en su comprensión. Objetivo: realizar una revisión narrativa sobre el estado actual del conocimiento del SR, sus avances recientes, las brechas existentes y las perspectivas futuras. Métodos: se realizó una revisión integrativa de artículos publicados entre 2000 y 2024 en bases de datos internacionales, siguiendo una metodología sistemática de búsqueda, selección y análisis de la literatura. Resultados: se identificaron los principales mecanismos fisiopatológicos del SR, sus manifestaciones clínicas multisistémicas, los criterios diagnósticos actuales y las estrategias terapéuticas basadas en el riesgo. A pesar de los avances en términos de biomarcadores y nutrición personalizada, persisten desafíos en el diagnóstico precoz, la prevención y el tratamiento, especialmente en las poblaciones vulnerables. Conclusiones: el SR sigue siendo un reto clínico complejo que exige protocolos estandarizados, identificación de biomarcadores fiables y una mayor investigación clínica, especialmente en regiones poco estudiadas como América Latina. La prevención basada en un enfoque multidisciplinario es clave para reducir su impacto.
25 Apr 2026
Read appraisal →The New England journal of medicine
Ketamine or Etomidate for Tracheal Intubation of Critically Ill Adults
BACKGROUND: For critically ill adults undergoing tracheal intubation, observational studies suggest that the use of etomidate to induce anesthesia may increase the risk of death. Whether the use of ketamine rather than etomidate decreases the risk of death is uncertain. METHODS: In a randomized trial conducted in 14 emergency departments and intensive care units in the United States, we randomly assigned critically ill adults who were undergoing tracheal intubation to receive ketamine or etomidate for the induction of anesthesia. The primary outcome was in-hospital death from any cause by day 28. The secondary outcome was cardiovascular collapse during intubation, defined by the occurrence of a systolic blood pressure below 65 mm Hg, receipt of a new or increased dose of vasopressors, or cardiac arrest. RESULTS: A total of 2365 patients underwent randomization and were included in the trial population; 1176 were assigned to the ketamine group and 1189 to the etomidate group. In-hospital death by day 28 occurred in 330 of 1173 patients (28.1%) in the ketamine group and in 345 of 1186 patients (29.1%) in the etomidate group (risk difference adjusted for trial site, -0.8 percentage points; 95% confidence interval [CI], -4.5 to 2.9; P = 0.65). Cardiovascular collapse during intubation occurred in 260 of 1176 patients (22.1%) in the ketamine group and in 202 of 1189 patients (17.0%) in the etomidate group (risk difference, 5.1 percentage points; 95% CI, 1.9 to 8.3). Prespecified safety outcomes were similar in the two groups. CONCLUSIONS: Among critically ill adults undergoing tracheal intubation, the use of ketamine to induce anesthesia did not result in a significantly lower incidence of in-hospital death by day 28 than etomidate. (Funded by the Patient-Centered Outcomes Research Institute and others; RSI ClinicalTrials.gov number, NCT05277896.).
24 Apr 2026
Read appraisal →BMJ open
Effect of early antiplatelet therapy on 30-day mortality after coronary artery bypass grafting: a retrospective target trial emulation using the MIMIC-IV database
OBJECTIVES: The effect of early antiplatelet therapy on 30-day mortality after coronary artery bypass grafting (CABG) remains uncertain. This study aimed to evaluate the association between early antiplatelet therapy initiation and clinical outcomes in post-CABG patients. DESIGN: A retrospective target trial emulation. SETTING: Single academic medical centre in Boston, Massachusetts, USA. PARTICIPANTS: We included adult patients who underwent CABG and were admitted to the intensive care unit at Beth Israel Deaconess Medical Center between 2008 and 2022. METHODS: Patients were classified into the treatment group if they initiated antiplatelet therapy within 24 hours postoperatively; otherwise, they were assigned to the control group. To address immortal-time bias for the primary outcome of 30-day mortality, we used clone-censor-weighting. For the exploratory outcome of 30-day acute kidney injury (AKI) incidence, we employed inverse probability of treatment weighting to balance baseline covariates. RESULTS: The analysis for 30-day mortality included 6887 patients. The mortality was 2.35% in the control group versus 1.44% in the treatment group, yielding an absolute risk difference of 0.90% (control group minus treatment group, 95% CI 0.09% to 1.72%). The difference in restricted mean time lost was 0.19 days (control group minus treatment group, 95% CI 0.03 to 0.36). For AKI incidence, 5543 patients were analysed. The incidence was 78.61% in the control group and 69.13% in the treatment group, with an absolute difference of 9.48% (control group minus treatment group, 95% CI 6.40% to 12.50%; p<0.001). CONCLUSIONS: In this target trial emulation, early antiplatelet therapy initiated within 24 hours after CABG was associated with lower 30-day mortality and a reduced incidence of postoperative AKI. These findings warrant confirmation in prospective randomised controlled trials.
24 Apr 2026
Read appraisal →Critical care explorations
The Effects of Conservative Fluid Management and Active Deresuscitation on Markers of Tissue Perfusion, Kidney Injury, and Vascular Injury in Critically Ill Adults: A Secondary Analysis of the Role of Active Deresuscitation After Resuscitation-2 (RADAR-2) Trial
OBJECTIVES: Test the hypothesis that conservative fluid management with active deresuscitation would not adversely affect tissue perfusion or kidney injury and would be associated with reduced vascular injury compared with usual care. DESIGN: Secondary analysis of the Role of Active Deresuscitation After Resuscitation-2 (RADAR-2) trial. SETTING: ICUs. PATIENTS OR SUBJECTS: Critically ill patients enrolled in the RADAR-2 trial. INTERVENTIONS: Conservative fluid management with active deresuscitation vs. usual care. MEASUREMENTS AND MAIN RESULTS: Measures of tissue hypoperfusion (whole blood lactate), acute kidney injury (AKIRisk score and urinary cystatin-C), and vascular injury (plasma hyaluronan, syndecan-1, and angiopoietin-2) were compared between groups. For each analyte, change from baseline was compared between groups and the median inter-group difference at each timepoint was estimated with bootstrapped CIs. Exploratory logistic regression examined associations between plasma biomarker levels (including N-terminal pro-B-type natriuretic peptide [NT-proBNP]), 28-day mortality, and treatment allocation. Whole blood lactate levels were similar between groups at all timepoints. Using change from baseline comparisons, no statistically detectable between-group differences were observed in AKIRisk scores or urinary cystatin-C levels. Plasma vascular injury biomarkers showed no statistically detectable between-group differences at any timepoint. High baseline hyaluronan (adjusted odds ratio [aOR], 5.75; 95% CI, 1.94-17.02; p = 0.002), syndecan-1 (aOR, 8.82; 95% CI, 2.67-29.15; p < 0.001), and NT-proBNP greater than 2500 pg/mL (aOR, 21.48; 95% CI, 3.57-129.41; p < 0.001) were independently associated with increased 28-day mortality. There was no evidence of differential treatment response based on these biomarker levels. CONCLUSIONS: Conservative fluid management and active deresuscitation were not associated with worsening tissue perfusion or acute kidney injury. A reduction in vascular injury markers was not observed. Given the modest sample size and resultant imprecision, clinically important effects cannot be excluded.
23 Apr 2026
Read appraisal →Archives of disease in childhood. Fetal and neonatal edition
Cerebral fuels within the first week of life in very preterm infants: a cohort study
BACKGROUND: Ketones and lactate may contribute towards overall cerebral fuel availability in term infants, yet the availability of such cerebral fuels in very preterm infants is unclear. We undertook a prespecified substudy to explore ketone and lactate concentrations in the first week of life in infants recruited to the REACT trial (real-time continuous glucose monitoring in the newborn): an international multicentre randomised controlled trial of 182 very low birth weight infants investigating the use of continuous glucose monitoring in glycaemic care. METHODS: Ketone and lactate measurements were prospectively collected over the first week of life using the Nova Biomedical point-of-care meter. A longitudinal analysis was undertaken to explore lactate and ketone concentration trends across time and their relationships with blood glucose, baseline demographics, nutritional support and insulin treatment. RESULTS: Data were available for 168 infants (85 females) including 2902 blood glucose, 2084 ketone and 2017 lactate samples. The mean (SD) gestational age was 27.4 (2.0) weeks. Lactate concentrations were higher initially, with mean (SD) 1.72 (1.26) mmol/L on day 2 and lowered to 1.19 (1.1) mmol/L on day 7. Ketone concentrations remained consistently low at 0.1 mmol/L. Neither simultaneous blood glucose concentrations, macronutrient intake nor receipt of insulin was consistently related to ketone or lactate concentrations. CONCLUSION: In this cohort of very preterm infants, there were persistently low concentrations of ketones and relatively higher concentrations of lactate throughout the first week of life. Future research should evaluate changes in these metabolites during episodes of acute hypoglycaemia or hyperglycaemia over more prolonged periods of neonatal intensive care.
20 Apr 2026
Read appraisal →Medicine
Saturation effect of anion gap in predicting long-term mortality in critically ill patients with chronic obstructive pulmonary disease (COPD): A retrospective cohort study based on the MIMIC-IV database
The relationship between anion gap (AG) and long-term mortality in intensive care unit has been widely reported, but whether this association exists in critically ill patients with chronic obstructive pulmonary disease (COPD) is still unknown. The data of this study were collected from the Medical Information Mart for Intensive Care-IV. First of all, we used the Cox regression analysis and Kaplan-Meier curves to measure the relationship between AG and 365-day mortality for critically ill patients with COPD. Next, a restricted cubic spline was used to analyze the relationship between AG and mortality. Finally, age, sex, weight, hypertension, type 2 diabetes mellitus, heart failure, myocardial infarction, and chronic kidney disease were considered for subgroup analysis. A total of 2594 eligible subjects were sampled, of which 36.24% died within 365 days of intensive care unit admission. Cox regression analysis, after adjusting for confounders, demonstrated a significant association between AG and 365-day mortality in patients with COPD (hazard ratio = 1.03, 95% confidence interval: 1.01-1.05. P < .05). Stratifying AG into quartiles revealed higher levels of AG associated with an increased risk of death (Q1: 1.00, Q2: 1.34 [1.09-1.66], Q3: 1.44 [1.17-1.78], and Q4: 1.49 [1.19-1.87]). Additionally, restricted cubic spline analysis indicated a nonlinear relationship, with a critical value of AG at 14 mmol/L. Subgroup analysis highlighted AG as a significant predictor of long-term mortality in COPD patients across different subgroups, with an interaction effect observed in the subgroup with type 2 diabetes mellitus. In critically ill patients with COPD, there was a significant positive association between AG and 365-day mortality. In addition, there is a saturation effect at AG of 14 mmol/L.
20 Apr 2026
Read appraisal →BMJ open
Implementation of a digital tool for monitoring and managing the emotional and cognitive sequelae of post-intensive care syndrome: ICURA study protocol for a randomised clinical trial
INTRODUCTION: Intensive care units (ICUs) can be a particularly challenging environment for patients who are mentally vulnerable. In addition to the physical stress associated with critical illness and its management, there are physiological and psychosocial factors that can negatively impact a patient's mental health. Approximately half of ICU survivors will experience post-intensive care syndrome, a set of emotional, neuropsychological and physical sequelae that can significantly affect patients' functionality and quality of life, both in the short and long term. The main objective of this study is to investigate whether the ICU Recovery Answers (ICURA) digital follow-up platform can effectively detect emotional and cognitive problems in critically ill patients and its impact on functionality and health-related quality of life during the first year after ICU discharge. METHODS AND ANALYSIS: Multicentre longitudinal prospective study involving ICU adult patients, with randomised follow-up comparing a telemedicine monitoring programme versus usual medical care during 1 year after discharge. A total of 360 participants will be recruited during their ICU admission in two hospitals in Spain. Efficacy outcomes will focus on participants' level of functioning, assessed with the WHO Short Disability Assessment Schedule, and quality of life, measured with the 12-Item Short Form Survey at 1, 6 and 12 months after ICU discharge. Emotional state and cognitive impairment will be evaluated using the Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and Treatment-Outcome Post-Traumatic Stress Disorder Scale and the Montreal Cognitive Assessment by telephone at 1, 3, 6, 9 and 12 months after ICU discharge. ETHICS AND DISSEMINATION: The implementation of this project is expected to have a direct impact on the satisfaction of ICU survivors, improving their well-being, personalised follow-up and quality of life. Results from this study will be disseminated at various scientific conferences, national and international meetings, and will be shared with the general public and other relevant parties. The dissemination of these results will occur through scientific publications, allowing the medical and scientific community to benefit from the study's findings. Ethics approval from the Ethics Board of Parc Taulí Foundation and Balearic Islands with reference numbers 2022/3031 and IB 5072/22 PI: Protocol version 1 of 18 November 2022. TRIAL REGISTRATION NUMBER: NCT06504979.
20 Apr 2026
Read appraisal →Archives of disease in childhood. Fetal and neonatal edition
Cost-consequence analysis of early full milk feeding versus gradual feeding with intravenous support in preterm infants: results from the FEED1 trial
OBJECTIVE: To assess the economic consequences of initiating full milk feeds from birth compared with intravenous fluids with gradual feeding in infants born preterm. DESIGN: Within-trial economic evaluation alongside a prospective, multicentre, randomised controlled trial (Fluids Exclusively Enteral from Day 1). A cost-consequence approach was used (revised from the planned cost-effectiveness analysis to avoid double counting length of stay within costs). SETTING: 46 UK National Health Service (NHS) neonatal units. PATIENTS: Preterm infants born at 30+0to 32+6 weeks' gestation. INTERVENTIONS: Infants were allocated to either full milk feeds or gradual feeding with intravenous support within 3 hours of birth. MAIN OUTCOME MEASURE: Resource use and costs were captured from birth to 6 weeks' corrected age. Costs were assessed from an NHS and personal social services perspective. The primary clinical outcome was length of hospital stay. RESULTS: 2088 infants were enrolled. There was no statistically significant difference in mean (95% CI) length of hospital stay between groups (-0.050 days (-0.638 to 0.538)). Mean total costs were £670 lower in the full milk group (95% CI: -£1562 to £223; p=0.141). Subgroup analyses suggested lower costs among infants born at 30 weeks' gestation and those below the 10th birth weight centile; no evidence of interaction was found. CONCLUSIONS: Initiating full milk feeds from birth was associated with a modest reduction in costs compared with gradual feeding. While overall hospital stays and costs were not significantly reduced, early full feeding may offer economic advantages in selected subgroups. Further research is needed to assess long-term outcomes. TRIAL REGISTRATION NUMBER: ISRCTN89654042.
19 Apr 2026
Read appraisal →Inflammation research : official journal of the European Histamine Research Society ... [et al.]
The calcium-sensing receptor in sepsis and septic shock, mechanistic pathways and translational perspectives: a systematic review.
BACKGROUND: Sepsis and septic shock are major causes of mortality in critically ill patients. They are linked to widespread metabolic and immune dysregulation, including alterations in calcium and phosphate homeostasis. The calcium-sensing receptor (CaSR) not only plays a role in mineral balance, but also modulates key immune pathways and may contribute to the pathogenesis of sepsis. METHODS: A systematic literature review was conducted according to PRISMA 2020 guidelines. Four databases (PubMed, EMBASE, Cochrane Library, and Google Scholar) were searched for studies published since 1990. To be eligible for inclusion, articles had to be original research, reviews, or clinical trials involving adult models (mammalian or human). Full-text availability was required. Risk of bias was assessed for all studies included. RESULTS: Sixty-six articles met the inclusion criteria: 49 original studies and 17 reviews. No randomized controlled trials or meta-analyses were identified. Most studies relied on in vitro or in vivo models. CaSR was consistently reported to be upregulated or activated following exposure to bacterial and inflammatory stimuli in immune cells, including monocytes and lymphocytes. CaSR activation promotes proinflammatory cytokine release, notably IL-1β via the NOD like receptor family 3 (NLRP3) inflammasome although results in intestinal epithelial models remain inconsistent. In non-septic models, CaSR activation was associated with tissue and organ injury, including renal and cardiac damage, as well as vasoplegia related to endothelial dysfunction. Preclinical models of pneumonia and endotoxemia suggest that CaSR antagonists may effectively mitigate inflammation and organ injury. CONCLUSION: This systematic review identifies the CaSR as an amplifier of the host inflammatory response across both septic and non-septic preclinical models The lack of robust clinical data underscores the need for translational studies assessing CaSR expression or activity in patients with sepsis or septic shock, alongside in vivo validation of CaSR inhibition as a therapeutic strategy.
19 Apr 2026
Read appraisal →Archives of disease in childhood. Fetal and neonatal edition
Intermittent hypoxia and caffeine in infants born preterm: the ICAF Randomized Clinical Trial
OBJECTIVE: To determine whether extending caffeine therapy through 43 weeks' postmenstrual age (PMA) decreases intermittent hypoxia (IH) in convalescing preterm infants. Secondary objectives were to assess caffeine effects on changes in inflammation-related plasma biomarkers and brain MRI. DESIGN: Multicentre masked randomised trial. SETTING: 16 US hospitals. PATIENTS: Infants at <30 weeks + 6 days gestational age on caffeine between 32 weeks and 36+5 days PMA in room air with routine caffeine discontinuation prior to 36 weeks +6 days. INTERVENTION: Randomisation to caffeine or placebo and treated through 42 completed weeks. Pulse oximetry was recorded from enrolment through 1 week after stopping study drug. Blood for 12 inflammation-related biomarkers obtained at enrolment and 38 weeks' PMA and brain imaging after enrolment or <3 days of randomisation, and study end. MAIN OUTCOME MEASURE: Seconds/hour of oxygen saturation <90% from randomisation to study end. RESULTS: Randomised 160 subjects, 78 placebo, 82 caffeine. IH was less at every PMA with caffeine treatment from 34 (172.7 (123.4, 241.7); 84.7 (64.4, 111.4, p<0.01) through 41 weeks (73.0 (51.3, 103.7); 26.6 (18.5, 38.2, p<0.001). Adjusted TNF-α levels were 23% lower at follow-up in the caffeine group compared with placebo (p<0.02), without other biomarker differences. Paired brain imaging found no significant differences. CONCLUSIONS: Extended caffeine reduced the burden of IH in very preterm infants and may reduce inflammation. Further study is needed to determine if this effect of caffeine is associated with reduced risk of adverse outcomes. TRIAL REGISTRATION NUMBER: NCT03321734.
19 Apr 2026
Read appraisal →PloS one
The association between RDW-to-platelet ratio and in-hospital mortality in critically ill stroke patients: A retrospective cohort study based on the eICU database
OBJECTIVE: The red cell distribution width-to-platelet ratio (RDW-to-platelet ratio, RPR) is a potential biomarker of inflammation and bone marrow function. This study aimed to investigate the association between RPR and in-hospital mortality in critically ill stroke patients in the eICU, and to evaluate mediating role of APACHE-IV score. METHOD: This retrospective cohort study utilized data from the 2014-2015 US multicenter eICU database. Of 200,859 initially included patients, 9,736 critically ill stroke patients were analyzed after excluding non-stroke cases and those with missing key variables. Multivariable logistic regression assessed the relationship between RPR and in-hospital mortality, adjusting for age, sex, comorbidities, and laboratory parameters, with multiple imputation for missing data. Subgroup analyses, mediation analysis, and restricted cubic spline modeling were performed. RESULTS: Patients with higher RPR exhibited significantly elevated in-hospital mortality (17.7% vs. 11.6%, P < 0.001). After adjustment, each unit increase in RPR was associated with 4.6% higher odds of death (adjusted OR=1.046, 95% CI: 1.032-1.061, P < 0.001), with consistent findings across subgroups. Restricted cubic spline analysis indicated a linear relationship. Mediation analysis showed that APACHE-IV score mediated 20.15% of the total effect (P < 0.001). CONCLUSIONS: Elevated RPR is independently associated in-hospital mortality in critically ill stroke patients, partly mediated by disease severity. As a simple and accessible marker, RPR shows promise for clinical prognostic risk stratification.
18 Apr 2026
Read appraisal →Journal of neurointerventional surgery
Systolic blood pressure within 24 hours after successful reperfusion correlates with outcomes in acute ischemic stroke: a secondary analysis of the EHCHANTED2/MT Trial
BACKGROUND: The optimal threshold or range for systolic blood pressure (SBP) control in patients with successful reperfusion after endovascular thrombectomy for acute ischemic stroke (AIS) remains undefined. This study investigated whether SBP within the first 24 hours after successful reperfusion correlates with functional outcomes in AIS. METHODS: In this secondary analysis of the ENCHANTED2/MT trial, patients were categorized into two groups (120-140 mm Hg and 140-180 mm Hg, respectively) based on achieved SBP within 24 hours after randomization. The primary outcome was the modified Rankin Scale (mRS) score at 90 days. Secondary outcomes included neurological deterioration at 7 days, major disability (mRS score of 3-5 at 90 days), hospitalization duration, and health-related quality of life assessed by the three-level EuroQoL 5-Dimension Self-Report Questionnaire (EQ-5D-3L) at 90 days. Safety outcomes included early neurological decline (END), 90-day mortality, symptomatic intracranial hemorrhage (sICH), and any intracranial hemorrhage (ICH). Treatment effects were expressed as ORs with 95% confidence intervals (CIs). RESULTS: A total of 611 patients (363 in the 120-140 mm Hg group and 248 in the 140-180 mm Hg group) were included. The mean (SD) age was 67 (12) years and 37.8% were female. After adjusting for confounders, the 120-140 mm Hg group was significantly associated with better functional outcomes (mRS: 2 (IQR 1-4) vs 2 (IQR 1-5); adjusted OR 1.54 (95% CI 1.10 to 2.17), P=0.013). Compared with the 140-180 mm Hg group, the 120-140 mm Hg group had lower rates of neurological deterioration at 7 days (adjusted OR 0.68 (95% CI 0.47 to 0.98), P=0.037) and 90-day mortality (47 (13.0%) vs 53 (21.4%); adjusted OR 0.48 (95% CI 0.27 to 0.86), P=0.013). There were no significant differences between groups in END, major disability at 90 days, hospitalization duration, EQ-5D-3L score, sICH, or ICH (all P>0.05). CONCLUSIONS: In patients with successful reperfusion after endovascular thrombectomy, an average SBP within 24 hours of 120-140 mm Hg was associated with a greater likelihood of functional independence compared with 140-180 mm Hg.
18 Apr 2026
Read appraisal →Journal of global health
Associations between haemoglobin-to-red cell distribution width ratio and mortality in intracerebral haemorrhage: a population-based analysis of the MIMIC-IV database
BACKGROUND: Intracerebral haemorrhage (ICH) is a leading cause of mortality and morbidity worldwide. Identifying early prognostic biomarkers is crucial to optimise clinical management of critically ill patients with ICH. The haemoglobin-to-red cell distribution width ratio (HRR) has recently emerged as a potential predictor in various critical illnesses, but its role in ICH remains unclear. This study aimed to evaluate associations between HRR and mortality in patients with ICH. METHODS: This retrospective cohort study included the data of adults (≥18 years) extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database (version 1). HRR was calculated from the first available haemoglobin and RDW measurements within one day of each other. Patients were categorised into HRR quartiles. The primary outcomes were 28-day and 1-year all-cause mortality. Associations were assessed using Cox proportional hazards models. RESULTS: The data of 1915 patients (mean age 67.5 years) were analysed retrospectively. After adjusting for possible confounders, compared with the lowest HRR quartile (Q1), patients in Q3 and Q4 had significantly lower 28-day mortality (Q3: adjusted hazard ratio (aHR) = 0.72; 95% CI = 0.54, 0.97; Q4: aHR = 0.67; 95% CI = 0.49, 0.90). Similarly, higher HRR quartiles were associated with reduced 1-year mortality risk (Q3: aHR = 0.64; 95% CI = 0.49, 0.84; Q4: aHR = 0.56; 95% CI = 0.42, 0.75). CONCLUSIONS: Lower HRR at admission is independently associated with higher short-term and long-term mortality in ICU patients with ICH. HRR may serve as a candidate prognostic biomarker for early risk stratification in this high-risk population. Further prospective studies are warranted to confirm these findings.
18 Apr 2026
Read appraisal →Journal of neurointerventional surgery
Explainable machine learning model for predicting functional outcomes in posterior circulation stroke after thrombectomy
BACKGROUND: The early prediction of functional outcomes in patients with posterior circulation stroke (PCS) is crucial for timely interventions and optimizing treatment plans. We have developed and validated a machine learning (ML) model for predicting 3-month functional outcomes in patients with PCS undergoing endovascular thrombectomy (EVT). METHODS: The derivation cohort, consisting of 202 patients with PCS who underwent EVT at four medical centers from January 2020 to December 2023, was separated for training and internal validation, and an external dataset of 54 patients admitted from January 2020 to July 2023 was used for external validation. The target outcome was a good functional outcome, defined as a modified Rankin Scale score of 0-3 at 3 months. Seven ML models were trained using preoperative features, with the primary evaluation metric being the area under the receiver operating characteristic curve (AUC). The top performing model was further trained using intraoperative and postoperative features. Model interpretations were generated using the Shapley additive explanations (SHAP) method. RESULTS: The Random Forest model demonstrated the best discriminative ability among the models considered. After feature selection, the final preoperative model used seven features, achieving an AUC of 0.83 in the test set and 0.81 in the external validation cohort. The inclusion of intraoperative and postoperative features further enhanced the model's performance, resulting in an AUC of 0.84 and 0.90 in the test set and 0.83 and 0.90 in the external validation cohort, respectively. These models have been incorporated into a publicly accessible web-based calculator (https://zhelvyao-123-60-basilarz.streamlit.app). CONCLUSION: The interpretable ML models provide dynamic accurate predictions of functional outcomes in patients with PCS after EVT, offering valuable insights for personalized risk stratification and optimizing perioperative management, with potential for integration into clinical workflows.
18 Apr 2026
Read appraisal →Stem cell reports
Cellular immunotherapy for COVID-19-induced acute respiratory distress syndrome: Results of the CIRCA-19 phase 1 safety and phase 2 randomized controlled trials
The ability of immunomodulatory mesenchymal stromal cells (MSCs) to improve COVID-19-associated acute respiratory distress syndrome (ARDS) in clinical trials is uncertain. We assessed whether freshly cultured umbilical cord (UC)-derived MSCs improved outcomes in patients with severe COVID-19 ARDS. We enrolled 37 patients with severe COVID-19 ARDS: 15 in the phase 1 dose escalation and open label extension studies (NCT04400032), and 22 patients in the phase 2b randomized clinical trial (NCT04865107). Delivery of up to 270 × 106 MSCs in three divided daily doses was well tolerated and resulted in qualitative improvement in all clinical outcomes. Furthermore, MSCs resulted in resolution of lymphopenia, consistent with an important immunomodulatory effect, with significant improvement in patient reported quality-of-life measures (SF-36) at 6 months pointing to possible durable clinical effects. These findings suggest a potential benefit of freshly cultured, UC-MSCs in severe COVID-19 ARDS, associated with biological evidence of favorable immunomodulatory activity.
17 Apr 2026
Read appraisal →European journal of pediatrics
7-days versus 14-days antibiotic therapy in uncomplicated culture proven neonatal sepsis: a randomized control assessor-blinded trial
UNLABELLED: The trial aimed to establish the non-inferiority of a 7-day antibiotic therapy for uncomplicated neonatal sepsis when compared to the standard 14-day therapy. This study was a parallel-group, randomized non-inferiority assessor-blinded trial conducted in a tertiary Neonatal Intensive Care Unit in Central India. Neonates weighing ≥ 1000 g with suspected sepsis were screened and those meeting criteria were enrolled. Exclusions included babies with CNS (central nervous system) infections, septic arthritis, and life-threatening congenital malformations. Participants were observed for 7 days on antibiotics and re-evaluated; those with positive blood cultures were then randomized to receive either 7 or 14 days of antibiotics. The primary outcome was the relapse of sepsis, and a sample size of 70 in each arm was calculated based on a non-inferiority margin. Follow-ups were conducted for 48 h post-antibiotic treatment and weekly for 35 days to monitor any recurrence of illness. During the study, 917 babies with suspected sepsis were admitted, of which 256 had culture-positive sepsis. After excluding those with meningitis, staphylococcus, and fungal infections, 140 babies showed improvement at day 5 and were randomized into two groups: one receiving antibiotics for 7 days and the other for 14 days, each consisting of 70 babies. Klebsiella pneumoniae was the prevalent organism. The 7-day group had a shorter hospital stay (p < 0.05) and less respiratory support (p < 0.05). Outcomes revealed a low incidence of probable relapse in both groups, with no fatalities or definitive relapses recorded. CONCLUSIONS: A 7-day antibiotic regimen for uncomplicated neonatal sepsis is not inferior to a 14-day regimen. WHAT IS KNOWN: • Unregulated use of antibiotics can lead to a myriad of problems, especially in neonates. • There is some evidence that uncomplicated neonatal sepsis can be treated with short-course antibiotics. WHAT IS NEW: • Data is lacking-especially from Central India. • This trial checks if it is possible to reduce the duration of antibiotic therapy in uncomplicated neonatal sepsis.
16 Apr 2026
Read appraisal →Neurology
Systolic Blood Pressure Trajectory and Outcomes in Acute Intracerebral Hemorrhage: Pooled Analysis of the 4 INTERACT and ATACH-II Clinical Trials
BACKGROUND AND OBJECTIVES: While moderate and rapid systolic blood pressure (SBP) lowering was associated with better functional outcomes after intracerebral hemorrhage (ICH), large reductions in SBP within 1 hour, for example, reductions from >200 to <140 mm Hg, diminished or even reversed these beneficial effects. We aimed to define the optimal trajectory of SBP control in relation to favorable functional outcomes after acute ICH. METHODS: We conducted a pooled analysis of individual patient-level data from all 4 Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial (INTERACT) and second Antihypertensive Treatment of Acute Cerebral Hemorrhage (ATACH-II) trials, which were international, randomized, open-label, blinded, end point-assessed, controlled trials that determined the effectiveness of early intensive SBP control in acute ICH. Latent class analysis grouped SBP trajectories over the first 24 hours (9 measurements) into defined clusters. The primary outcome was functional recovery at 90 days after randomization, defined as modified Rankin Scale (mRS) scores of 3-6. Logistic regression models with adjustment for baseline covariates and trial were used to determine associations between SBP cluster trajectories and outcomes in INTERACT, with validation in ATACH-II. RESULTS: A total of 11,269 patients (INTERACT n = 10,269; ATACH-II n = 1,000; mean age 62.4 years; female 36.4%) with at least 1 postrandomization SBP reading were included. Six SBP trajectories were identified: low, moderate-to-low, moderate, high, high-to-moderate, and high-to-low. Compared with the low SBP group, associations with poor functional outcome (mRS scores 3-6) increased progressively across other groups in INTERACT (p = 0.04 for trend). Adjusted odds ratios (95% CI) for groups 2 to 6 were 1.16 (0.98-1.37), 1.44 (1.18-1.75), 1.46 (1.15-1.87), 1.90 (1.32-2.73), and 1.28 (1.02-1.60), respectively. A similar albeit nonsignificant trend was observed in ATACH-II due to limited power. DISCUSSION: Distinct SBP trajectories over 24 hours defined prognosis after ICH, with a severe hypertensive group having the highest odds of death or disability, regardless of the BP-lowering strategy used. These findings highlight the importance of well-controlled but tailored SBP management strategies after ICH. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that distinct SBP trajectories over 24 hours are associated with prognosis after acute ICH, with a severe hypertensive group having the highest odds of poor functional outcome, regardless of the BP-lowering strategy used. TRIAL REGISTRATION INFORMATION: (INTERACT1 NCT00226096; INTERACT2 NCT00716079; INTERACT3 NCT03209258; INTERACT4 NCT03790800; ATACH-2 NCT01176565).
15 Apr 2026
Read appraisal →JAMA
Restrictive vs Liberal Physical Restraint Strategies in Critically Ill Patients: The R2D2-ICU Randomized Clinical Trial
IMPORTANCE: The effect of wrist-strap physical restraints on outcomes in patients receiving mechanical ventilation in the intensive care unit (ICU) remains uncertain. OBJECTIVE: To investigate the effect of a low-use wrist-strap physical restraint strategy in critically ill patients receiving invasive mechanical ventilation. DESIGN, SETTING, AND PARTICIPANTS: Open-label randomized clinical trial conducted across 10 ICUs in France. Between January 5, 2021, and January 2, 2024, 405 adult patients who had initiated invasive mechanical ventilation within the previous 6 hours and were expected to require ventilation for at least 48 hours were enrolled. Follow-up was completed on May 17, 2024. Statistical analysis was conducted from June 1, 2025, to December 15, 2025. INTERVENTIONS: Patients were randomized to undergo either a restrictive, low-use physical restraint strategy (wrist straps avoided unless necessary because of severe agitation, defined as a Richmond Agitation-Sedation Scale score of ≥3 [on a scale from -5 (unresponsive) to 4 (combative)]; n = 201) or a liberal, high-use strategy (wrist straps applied systematically and reassessed daily; n = 204). Discontinuation of restraints was allowed in patients who were awake or extubated without delirium (measured via the Confusion Assessment Method for the ICU). MAIN OUTCOMES AND MEASURES: The primary outcome was the number of days alive without coma or delirium during the first 14 days after randomization. Secondary outcomes included incidence of self-extubation and day-90 mortality. RESULTS: Among 396 patients with available primary outcome data, the median (IQR) age was 65 (56-73) years, 245 (62%) were male, and the median (IQR) Sequential Organ Failure Assessment score was 7 (4-10). The mean days alive without coma or delirium were 6.67 days (95% CI, 5.69-7.65) in the low-use strategy group and 6.30 days (95% CI, 5.35-7.24) in the high-use strategy group (adjusted mean difference, 0.37 days [95% CI, -0.71 to 1.46]; P = .51). Self-extubation occurred in 18 patients (9.2%) in the low-use strategy group and 17 (8.5%) in the high-use strategy group, and day-90 mortality was 37.2% and 41.0%, respectively. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, among adult patients receiving mechanical ventilation in the ICU, a low-use wrist-strap physical restraint strategy compared with a high-use strategy did not reduce days free of delirium or coma at 14 days. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04273360.
15 Apr 2026
Read appraisal →Medicine
Association of blood urea nitrogen to serum albumin ratio with mortality in ICU patients with sepsis-induced coagulopathy: A Retrospective Cohort Study from MIMIC-IV database
The blood urea nitrogen to serum albumin ratio (BAR) has shown promise as a prognostic marker in sepsis, yet its specific role in sepsis-induced coagulopathy (SIC) remains unclear. We aimed to clarify whether BAR informs mortality risk in critically ill intensive care unit (ICU) patients with SIC. Using the Medical Information Mart for Intensive Care IV database, we identified consecutive ICU patients admitted between 2008 and 2022 who fulfilled Sepsis-3 criteria and had an SIC score ≥4. BAR was calculated from the 1st available laboratory values. Multivariable Cox regression and restricted cubic splines were used to estimate mortality associations after adjustment for demographics, comorbidities, interventions, severity scores (Sequential Organ Failure Assessment, Simplified Acute Physiology Score II), and laboratory parameters. The primary end-point was 30-day mortality; 90- and 365-day mortality were secondary. Among 4244 patients, higher admission BAR independently predicted increased mortality at 30, 90, and 365 days. Each 10-unit rise in BAR conferred a 30% higher hazard of death within 30 days (unadjusted hazard ratio (HR) 1.30, 95% confidence interval (CI) 1.25-1.35; P < .001). After full adjustment, the association persisted (HR 1.18, 95% CI 1.12-1.24; P < .001). Similar patterns were seen for longer-term outcomes. A clear dose-response relationship was observed across BAR tertiles; patients in the highest tertile (BAR ≥ 10 mg/g) had markedly higher mortality risk (adjusted HR 1.69, 95% CI 1.43-2.00; P < .001) than those in the lowest. Nonlinear analysis revealed a curvilinear BAR-mortality relationship, and subgroup analyses showed consistent findings, with significant effect modification by age. In critically ill patients with SIC, an elevated admission BAR independently predicts short- and long-term mortality and may aid risk stratification and early intervention planning.
12 Apr 2026
Read appraisal →Heart (British Cardiac Society)
Parsimonious machine learning model to predict 1-year mortality and procedural futility after transcatheter aortic valve replacement
BACKGROUND: Current risk scores inadequately predict long-term mortality after transcatheter aortic valve replacement (TAVR), limiting their ability to guide decisions around procedural futility. We aimed to develop and externally validate a machine learning (ML) model using only preprocedural variables to predict 1-year all-cause mortality. METHODS: An ML model was trained on a retrospective cohort of 1025 TAVR patients using 52 clinical and echocardiographic variables. Feature selection and model tuning were performed via a multiobjective evolutionary algorithm to optimise predictive performance and model simplicity. The final model used 13 preprocedural variables and was externally validated in an independent cohort of 270 patients. Performance was compared with European System for Cardiac Operative Risk Evaluation II (EuroSCORE II), FRANCE-2 and TAVI2-SCORE using the area under the curve (AUC), calibration and net reclassification improvement (NRI). RESULTS: The ML model demonstrated excellent discrimination, with AUCs of 0.81 in the discovery cohort and 0.84 in the external validation cohort. This exceeded the performance of EuroSCORE II (AUC: 0.61 and 0.70), FRANCE-2 (0.52 and 0.58) and TAVI2-SCORE (0.56 and 0.64). Calibration plots showed strong agreement between predicted and observed risks. NRI in the test set compared with FRANCE-2 was 0.62 (95% CI: 0.49 to 0.75); compared with TAVI2-SCORE, it was 0.36 (95% CI: 0.14 to 0.61). The final model incorporated age, atrial fibrillation, creatinine, haemoglobin, pulmonary function, frailty markers (Katz Index, poor mobility) and tricuspid regurgitation. Misclassification analysis revealed that most errors were clustered near the decision threshold, with no evidence of systematic bias. Performance was consistent across subgroups and robust to temporal and institutional variation. CONCLUSION: This externally validated ML model, using 13 routinely available variables, significantly outperforms existing risk scores in predicting 1-year mortality post-TAVR. Its simplicity and generalisability support its potential use in real-world clinical decision-making to identify patients at high risk of procedural futility.
12 Apr 2026
Read appraisal →Medicine
Effectiveness of Chinese herbal medicine mouthwash in preventing ventilator-associated pneumonia in patients with endotracheal intubation: A systematic review and meta-analysis
BACKGROUND: To systematically evaluate the effectiveness and safety of Chinese herbal medicine mouthwash (CHMM) in preventing ventilator-associated pneumonia (VAP) in patients with endotracheal intubation (ETT). METHODS: Computer searches were conducted for relevant randomized controlled trials (RCTs) in the China National Knowledge Infrastructure (CNKI), WANFANG DATA, Chinese Scientific and Technical Journal Database (VIP), Chinese Biomedical Literature Database (SinoMed), PubMed, Embase, Cochrane Library, and CINAHL Database from the establishment to April 5, 2023. The data were analyzed by RevMan 5.3 software. The methodological quality of papers was evaluated by the Cochrane version 5.1.0 and the certainty of evidence was evaluated by the GRADE system. RESULTS: We included 27 RCTs with 2426 patients. Most of the included studies were of poor methodological quality. Meta-analysis showed that CHMM (RR = 0.41, 95% CI: 0.34-0.50, P < .00001, low-certainty evidence) or CHMM + routine oral care (RR = 0.31, 95% CI: 0.18-0.56, P < .0001) could reduce the incidence of VAP compared to non-CHMM. CHMM may be superior to saline (low-certainty evidence) and chlorhexidine (moderate-certainty evidence) in preventing VAP (P < .05). CONCLUSION: Low-certainty evidence shows that CHMM may be more advantageous in reducing the incidence of VAP compared to non-CHMM. However, due to some limitations and the low certainty of evidence, we cannot recommend CHMM for routine clinical use at this time. Large-scale and high-quality RCTs are also needed to definitively evaluate the safety and clinical benefits of CHMM in the future.
12 Apr 2026
Read appraisal →BMJ paediatrics open
Systematic review of the evidence of cardiac dysfunction and intravenous fluid use among children with severe acute malnutrition and severe dehydration
BACKGROUND: A sizeable proportion of cholera attributed mortality occurs among children with severe acute malnutrition (SAM). International guidelines severely limit the use of intravenous fluids among children with SAM and cholera due to their perceived vulnerability to fluid overload. We reviewed the cardiac function evidence and studies of intravenous fluid use among children with SAM. METHODS: Two systematic reviews of Chinese, English, French and Spanish language papers published after the last Global Task Force for Cholera Control recommendations on the treatment of children with cholera and SAM (2017) were conducted. The first included studies of cardiac function among children presenting to hospital with SAM. The second included studies of intravenous fluid use among children with dehydrating diarrhoea and SAM. RESULTS: Among eight echocardiographic studies of cardiac function in children with SAM at presentation to hospital, all found left ventricular mass to be decreased but none found systolic function to be impaired. Seven of the eight studies assessing diastolic function found some degree of mild-to-moderate impairment. Two echocardiographic studies monitored responsiveness to intravenous fluid resuscitation and found no evidence of fluid overload. Finally, four studies gave intravenous fluids to children with SAM and either shock or dehydration. Collectively, these studies included 251 children with SAM given intravenous fluid. No cases of fluid overload were observed. CONCLUSION: No evidence to support decreased systolic function among children with SAM and no documented cases of fluid overload during intravenous rehydration of these children were identified. These data call into question guidelines that severely restrict intravenous fluids among children with SAM and highly dehydrating conditions such as cholera.
12 Apr 2026
Read appraisal →A&A practice
Efficacy and Safety of Ketamine or Esketamine versus Fentanyl-Class Opioids as Adjuncts to Propofol for Gastrointestinal Endoscopy: A Systematic Review and Meta-Analysis
OBJECTIVE: Propofol is widely used for gastrointestinal (GI) endoscopies but may cause respiratory depression and hemodynamic compromise when used alone. Adjuncts such as ketamine or esketamine and fentanyl-class opioids (fentanyl, alfentanil, and sufentanil) are used to optimize sedation, yet their comparative efficacy and safety remain uncertain. This meta-analysis evaluated ketamine or esketamine plus propofol (KP regimens) versus fentanyl/alfentanil/sufentanil plus propofol (FP regimens). METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched PubMed, Scopus, Cochrane Library, and Google Scholar from inception to February 2025 for randomized controlled trials (RCTs). Eligible studies included patients undergoing GI endoscopy (Population), receiving ketamine or esketamine with propofol (Intervention), compared with fentanyl-class opioids with propofol (Comparison), and reporting outcomes including propofol dose, comfort, adverse events, recovery time, or procedure time (Outcomes). Risk of bias was assessed with the Cochrane tool. Heterogeneity was evaluated using Cochran's Q test and the I2 statistic, and clinical heterogeneity was considered based on study design and population differences. Sensitivity analyses were conducted to test robustness of findings. RESULTS: Fifteen RCTs (1492 participants) were included. KP regimens significantly reduced total propofol use compared with FP (mean difference [MD] -0.42; 95% confidence interval [CI] -0.66 to -0.19; P = .0005), with greater benefit observed for esketamine (p for subgroup = 0.001). No significant differences were found in sedation (MD 0.01; 95% CI -0.40 to 0.43; P = .95) or pain scores (MD 0.24; 95% CI -0.18 to 0.65; P = .26). Safety outcomes were comparable across groups, with no significant differences in desaturation, nausea/vomiting, bradycardia, or tachycardia, except for hypotension, which was lower with KP (risk ratio [RR] 0.56; 95% CI 0.39 to 0.82; P = .003). Recovery and procedure times were similar between groups. CONCLUSIONS: Both KP and FP regimens are effective and safe for GI endoscopy. KP regimens reduce total propofol requirements and significantly lower the risk of hypotension, while showing comparable sedation quality, analgesia, and recovery profiles to FP. These findings suggest KP may offer safety and dosing advantages, though larger standardized trials are needed to confirm its clinical superiority.
10 Apr 2026
Read appraisal →PloS one
An interpretable deep learning framework for predictive modeling of postoperative infections in ICU patients
A significant proportion of intensive care unit (ICU) patients undergo surgical procedures, and some may develop postoperative infections. Accurately predicting postoperative infection risk and identifying key contributing factors is crucial for improving postoperative management and understanding infection mechanisms. However, this task is challenging due to the complex interplay of multiple risk factors. While machine learning models can model these intricate associations to predict postoperative infection risk, their lack of interpretability - failing to uncover each factor's impact-hinders their adoption in clinical settings. To address this difficulty, we introduced an interpretable deep neural network (DNN) model that integrates a permutation feature importance test (PermFIT). PermFIT rigorously evaluates the impact of each feature on postoperative infection risk through a rigorous statistical inference. By using only the identified important features as inputs, the DNN's predictive performance can be further enhanced. We conducted an extensive study using electronic health records (EHRs) from the Medical Information Mart for Intensive Care (MIMIC-III), a large-scale ICU EHR database. Under the PermFIT framework, our DNN model effectively identifies significant factors associated with postoperative infections while delivering the most accurate postoperative infection risk predictions. These findings highlight the clinical utility of our proposed DNN framework in managing postoperative care for ICU surgical patients, ultimately improving their health outcomes.
10 Apr 2026
Read appraisal →European journal of pediatrics
Randomised crossover trial of neurally adjusted ventilatory assist (NAVA) for neonates with congenital diaphragmatic hernias: the NAN-C study
Retrospective studies comparing NAVA to assist control ventilation (ACV) in neonates with congenital diaphragmatic hernia (CDH) have shown that ventilatory mode may improve respiratory parameters. The aim of this study is to determine if infants with CDH studied post-operatively had a lower oxygenation index (OI) on NAVA compared to ACV. This dual-centre randomised cross-over trial compared post-operative NAVA with ACV in infants with CDH. Infants were randomised to receive either NAVA or ACV first in a 1:1 ratio for a 4-h period. At the end of each 4-h period, blood gas analysis was performed and the OI calculated. The inspired oxygen concentration (FiO2), the peak inflation (PIP), and mean airway pressure (MAP) were averaged from the last 5 min on each mode. Eleven infants were randomised. Nine infants completed the trial. with median gestational age of 38 (range 34.6-39.3) weeks and median postnatal age of 7 (range 5-36) days. Eight had left-sided CDH, six had patch repair and two had thoracoscopic repair. The mean OI after 4 h on NAVA was 3.9 ± 1.8 compared to 5.9 ± 1.61 on ACV (p = 0.008). The peak Edi (6.05 ± 4.5 versus 9.86 ± 7.3 µV, p = 0.028), PIP (17 ± 6.3 versus 22 ± 5.3 cmH2O, p = 0.017), and MAP (8.7 ± 2.6 versus 11.1 ± 1.8 cmH2O, p = 0.008), expiratory tidal volume (5.06 ± 0.71 versus 9.86 ± 1.29 ml/kg, p = 0.043) were lower on NAVA versus ACV. Two infants were randomised, but the trial was stopped due to a low Edi signal.Conclusion: NAVA compared to ACV improved oxygenation postoperatively in infants with CDH. On NAVA, infants had lower oxygen indices, peak Edi, expiratory tidal volume and peak and mean airway pressures.
10 Apr 2026
Read appraisal →Scientific reports
Association between estimated plasma volume status and all-cause mortality in critically ill patients with non-traumatic subarachnoid hemorrhage: analysis of the MIMIC-IV database
BACKGROUND: The estimated plasma volume status (ePVS) is an independent risk factor for poor prognosis in certain cardiovascular disease populations. However, the relationship between ePVS and prognosis in critically ill patients with non-traumatic subarachnoid hemorrhage (NSAH) remains unclear. This study aims to explore the association between ePVS and all-cause mortality (ACM) in NSAH patients. METHODS: A total of 750 NSAH patients were included in this retrospective study. The primary outcome was 1-month ACM. A Cox proportional hazards model was constructed to examine the relationship between ePVS and ACM in critically ill NSAH patients. A restricted cubic spline model was used to assess the relationship between ePVS and the outcome. RESULTS: In this patient cohort, 1-month, 3-month, and 1-year ACM rates were 21%, 25%, and 29%, respectively. After adjusting for potential confounders, we found a U-shaped relationship between ePVS and 1-month ACM, with an inflection point at 3.94. Specifically, when ePVS is below the inflection point, each unit increase in ePVS reduces the mortality risk by 56% [HR, 0.44 (95% CI 0.25, 0.76)]. However, once the inflection point is surpassed, each unit increase in ePVS increases the mortality risk by 1.8 times [HR, 2.80 (95% CI 1.58, 4.97)]. CONCLUSION: We identified a U-shaped relationship between ePVS and ACM in critically ill patients with NSAH, suggesting both low and high ePVS levels may portend adverse outcomes. Prospective multicenter studies are warranted to validate these findings and elucidate underlying mechanisms.
10 Apr 2026
Read appraisal →Brain : a journal of neurology
Multimodal multicentre investigation of diagnostic and prognostic markers in disorders of consciousness
Severely brain-injured patients may enter a spectrum of conditions collectively known as disorders of consciousness. This spectrum includes clinical conditions such as unresponsive wakefulness syndrome or minimally conscious state, where the behavioural assessment of consciousness can often be deceptive. To bridge this dissociation, neuroimaging techniques are employed to identify the residual brain functions. Each neuroimaging modality imperfectly captures distinct aspects of brain preservation-functional, anatomical, or both. In this study, we adopt a comprehensive approach by integrating the neurophysiology and neuroimaging modalities available from the standard and advanced clinical assessments through interpretable machine learning. The electrophysiological modalities included high-density EEG (resting state and task), whereas neuroimaging modalities included anatomical and resting-state functional MRI, diffusion MRI and 18F-fluorodeoxyglucose PET. Our investigation reveals that specific modalities, such as functional assessments, provide comprehensive insights into the currently evaluated state of consciousness, the diagnosis of the patients. Conversely, structural modalities offer valuable information about the patient's evolution within the consciousness spectrum. We validate the proposed analysis with data coming from other centres with different acquisition parameters. Importantly, we demonstrate that model performance improves with an increase in the number of modalities. We observe a higher inter-modality disagreement for minimally conscious state patients and those patients who improve. Lastly, we observe a difference in feature importances between diagnosis and prognosis, with an interaction between modality and anatomical structures: some subcortical markers tend to contribute more to prognosis, while other cortical markers are more informative for diagnosis. This integrative multimodal and machine learning methodology presents a promising avenue for a more nuanced understanding of disorders of consciousness, contributing to enhanced diagnostic precision, prognostic capabilities and the personalization of rehabilitative strategies in clinical practice.
9 Apr 2026
Read appraisal →Journal of the American Heart Association
Effects of Computed Tomography Hyperdense Middle Cerebral Artery Sign on the Efficacy of Endovascular Therapy in Acute Ischemic Stroke With Large Infarcts: A Subgroup Analysis of the ANGEL-ASPECT Trial
BACKGROUND: The hyperdense middle cerebral artery sign (HMCAS) observed on noncontrast computed tomography is associated with thrombus composition and thrombectomy outcomes. The impact of HMCAS on the efficacy of endovascular therapy (EVT) in patients with large core infarcts remains unclear. METHODS: This analysis uses data from the ANGEL-ASPECT (Endovascular Therapy in Acute Anterior Circulation Large Vessel Occlusive Patients With a Large Infarct Core) trial, a multicenter randomized controlled trial conducted in China. Patients with acute ischemic stroke and anterior-circulation large-vessel occlusion were categorized according to whether HMCAS was present on baseline noncontrast computed tomography. The primary outcome was the 90-day modified Rankin Scale score. RESULTS: Of the 432 patients included in this analysis, 33% were HMCAS positive on baseline noncontrast computed tomography. In the EVT-treated patients, patients with HMCAS had worse functional outcomes than those without HMCAS (adjusted relative risk, 0.44 [95% CI, 0.26-0.73]; P=0.002). Patients with HMCAS required a greater number of thrombectomy passes (P<0.001). Among patients without HMCAS, EVT was associated with better functional outcomes than medical management (generalized odds ratio [OR], 2.78 [95% CI, 1.80-4.27]; P<0.001), whereas this benefit was not statistically significant among patients with HMCAS (adjusted OR, 1.69 [95% CI, 0.93-3.08]; P=0.09). There was no significant interaction between HMCAS status and treatment assignment (P=0.19). CONCLUSIONS: In this subgroup analysis comparing EVT with medical management, we found no statistically significant treatment-by-HMCAS status interaction, indicating that the benefits of EVT extend to patients with large core infarcts irrespective of HMCAS status. However, the magnitude of benefit appears greater in patients without HMCAS, whereas those with HMCAS tend to have a poorer overall prognosis. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique Identifier: NCT04551664.
9 Apr 2026
Read appraisal →Journal of neural engineering
Large-scale training data enhances silent speech decoding with around-ear EEG.
Objective. Silent speech decoding (SSD) offers a potential communication alternative for individuals with impaired vocalization. However, conventional multi-electrode electroencephalography (EEG) or facial electromyography (EMG) systems require cumbersome preparation and are unsuitable for daily use. This study evaluates the practicality of SSD using a wearable around-ear EEG device, focusing on data scaling, cross-subject transfer, vocabulary extensibility, and online decoding performance.Approach. We collected 72 h of around-ear EEG from 24 healthy participants and one individual with incomplete locked-in syndrome (LIS) during silent, vocalized, and attempted speech, and integrated these around-ear EEG recordings with prior EMG + high-density EEG datasets, yielding 282.4 total h of training data. Using a 64-word classification task as the evaluation metric, we assessed: (1) whether larger datasets improve around-ear EEG-based SSD, (2) whether healthy-participant data supplement limited LIS-participant data despite articulatory differences, (3) transferability to unseen vocabulary, and (4) online user-interface performance.Main results. Large-scale EEG/EMG data improved SSD accuracy in both healthy participants and the LIS participant. Training on the heterogeneous dataset achieved 56.6% accuracy for healthy users and 47.3% for the LIS participant. Fine-tuning this decoder for new vocabulary increased the accuracy by 22 percentage points relative to training from scratch. Regression analysis showed that, for decoding in the LIS participant, data from the LIS participant contributed approximately four times the weight of healthy-participant data, quantifying data strategies for SSD. Online experiments achieved top-1/top-5 accuracies of 47.2%/76.0% for healthy users and 26.5%/49.1% for the LIS participant.Significance. The results indicate that lightweight, commercially feasible around-ear EEG can enable practical SSD when combined with large-scale healthy-participant data, supporting online operation. Moreover, models trained on a 64-word vocabulary facilitate decoding of a new vocabulary, providing a path toward SSD systems requiring minimal LIS-participant data. This study advances non-invasive SSD systems suitable for everyday communication.
8 Apr 2026
Read appraisal →Medical science monitor : international medical journal of experimental and clinical research
AI-Assisted Dialysis Decision-Making: Assessing Agreement Between ChatGPT and Nephrologist in Initial Dialysis Indication and Prescription in Emergency and ICU Settings
BACKGROUND Artificial intelligence (AI) is increasingly explored as a clinical decision-support tool in nephrology; however, its real-world applicability for dialysis decision-making in emergency and intensive care unit (ICU) settings remains insufficiently studied. Hemodialysis initiation and prescription are complex, time-sensitive, and dynamic processes that require expert clinical judgment. MATERIAL AND METHODS This retrospective observational study evaluated agreement between AI-generated (ChatGPT) and nephrologist-made dialysis decisions in emergency and ICU settings. Adult patients undergoing first-time dialysis were included. Agreement was assessed for dialysis initiation, modality selection, and key prescription parameters. To ensure clinical relevance, continuous prescription variables were categorized into predefined ranges. Agreement was quantified using Gwet's AC1 coefficient and Cramer's V statistic. RESULTS Eighty-four patients were included. AI demonstrated 100% agreement with nephrologists regarding dialysis initiation. Overall agreement for dialysis modality selection was 92.9% (Cramer's V=0.87, P<0.001). Agreement for core dialysis prescription parameters - including blood flow rate, dialysate sodium, potassium, and calcium concentrations - was high across modalities (all P<0.001). Lower agreement was observed for ultrafiltration-related parameters, particularly ultrafiltration duration, reflecting the individualized and dynamic nature of volume management during dialysis. CONCLUSIONS AI-assisted decision support demonstrated high agreement with nephrologist decisions for initial dialysis initiation, modality selection, and core prescription parameters in emergency and ICU settings. Discrepancies were primarily confined to ultrafiltration-related decisions, underscoring the necessity of ongoing bedside clinical judgment. These findings support the role of AI as a decision-support tool rather than a replacement for clinician-led dialysis management.
8 Apr 2026
Read appraisal →Annals of medicine
Immersive virtual reality-assisted anatomy training improves endotracheal intubation performance in simulation: a randomized controlled trial among Chinese non-anesthesiology residents
INTRODUCTION: This study aimed to compare immersive virtual reality (IVR)-assisted versus conventional anatomy training for teaching endotracheal intubation (ETI) to novice non-anesthesiology residents enrolled in China's Standardized Residency Training program. METHODS: A total of 90 non-anesthesiology residents without prior ETI experience were randomly assigned to either an IVR group receiving IVR-assisted anatomy training (n = 45) or a control group receiving conventional anatomy training (n = 45). All participants underwent a standardized teaching protocol. The primary endpoint was residents' ETI performance on a simulator, assessed using both the Global Rating Scale (GRS) and a task-specific checklist. The secondary endpoints included changes in written multiple-choice question (MCQ) scores and residents' evaluations of the course. RESULTS: In practical ETI assessments on a manikin, the IVR group achieved significantly higher scores on the task-specific checklist than the control group (90.34 ± 2.89 vs. 87.20 ± 3.29; p < 0.001), whereas GRS scores were comparable between groups. Both groups showed significant post-training improvement in knowledge scores (p < 0.001), with the IVR group showing a greater gain in theoretical knowledge (54.0% vs. 36.3%; p < 0.001). Participants in the IVR group also expressed a stronger preference for their training method (80.8%) and reported higher levels of motivation, confidence, and enjoyment (all p < 0.05). CONCLUSION: IVR-assisted anatomy training enhances the effectiveness of ETI training for novice non-anesthesiology residents, offering an interactive, engaging, and reproducible approach within China's Standardized Residency Training framework.
5 Apr 2026
Read appraisal →Medicine
Development of a prediction model for the risk of prolonged ICU length of stay in patients undergoing coronary artery bypass surgery: A retrospective analysis based on the MIMIC-IV database
The duration of hospitalization, particularly in the intensive care unit (ICU), for patients undergoing coronary artery bypass grafting (CABG), is influenced by both patient prognosis and treatment-related costs. Reducing the ICU length of stay (LOS) in CABG patients is critical for improving healthcare resource utilization. This study aimed to develop a model for identifying risk factors associated with prolonged ICU LOS in CABG patients, thus providing a foundation for clinical treatment, healthcare safety, and quality management research. In this single-center, retrospective cohort study, data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analyzed. Clinical data from 6152 CABG patients who required treatment in ICU were included. The dataset was split into a training set and an internal validation set. Predictor variables were identified using least absolute shrinkage and selection operator regression. A nomogram prediction model was developed based on the identified predictors. The predictors incorporated into the model included the Charlson comorbidity index, acute physiology score III, atrial fibrillation, heart failure (HF), body mass index, acute kidney injury stage, type 1 diabetes mellitus and glucose levels. The prediction model demonstrated robust performance, achieving an area under the curve of 0.789 in the training cohort and 0.790 in the validation cohort. The Hosmer-Lemeshow (H-L) test and calibration plots validated the model's accuracy in both cohorts. The nomogram prediction model proposed in this study provides significant clinical utility for predicting prolonged ICU LOS in patients undergoing CABG. This model can assist clinicians in identifying CABG patients at risk for prolonged ICU LOS, thus enabling timely interventions and improving prognostic outcomes.
5 Apr 2026
Read appraisal →Critical care explorations
Physician Gestalt Compared With Artificial Intelligence Model to Predict Intubation in Critically Ill Patients
IMPORTANCE: Accurate prediction of intubation in critically ill patients could enable interventions that improve patient outcomes. However, the performance of intensive care physicians compared with machine learning (ML) models remains unknown. OBJECTIVES: To investigate intensive care physicians' ability to predict the need for intubation within 24 hours and compare their performance against an established ML model, Vent.io. DESIGN, SETTING, AND PARTICIPANTS: This prospective observational study in two ICUs surveyed intensivists to test their ability to predict the need for intubation of adult patients under their care. Physician predictions of intubation were then compared with predictions from Vent.io. MAIN OUTCOMES AND MEASURES: Primary metrics include prediction sensitivity, specificity, and descriptive statistics for both physicians and ML model. Generalized linear mixed models investigated the fixed effect of the predictor (physician vs. Vent.io) on both sensitivity and specificity while accounting for the random effects from different physicians. Similar modeling was used to investigate the relationship between physician confidence and correctness. RESULTS: Overall, physicians were quite confident in their predictions of intubation with a median score of 8 (on a 0-10 point scale, with 0 being not at all confident and 10 being extremely confident) out of the 302 surveys administered. Sensitivity was 0.190 and 0.714 for physicians and Vent.io, respectively. Specificity was 0.960 and 0.673 for physicians and Vent.io, respectively. Generalized linear mixed modeling showed that physician confidence was associated with greater odds of correctly predicting intubation outcome (odds ratio [OR] 1.49; 95% CI, 1.22-1.84; p < 0.001). Vent.io had significantly greater odds of being correct when patients required intubation compared with physicians (OR 18.68; 95% CI, 1.87-186.31; p = 0.013). However, intensive care physicians outperformed Vent.io at correctly predicting when patients did not require intubation (OR 24.80; 95% CI, 13.22-46.52; p < 0.001). CONCLUSIONS AND RELEVANCE: Although predictive performance compared with human experts is promising, Vent.io needs real-time testing in a randomized clinical trial to determine if its deployment can improve clinical outcomes.
4 Apr 2026
Read appraisal →Physiological measurement
Deep learning approach for stroke volume variation estimation: retrospective modeling and prospective deployment in real-world practice
Objective. We developed stroke volume variation (SVV) Net, a deep learning-based model for estimating SVV, and validated its performance and clinical applicability through both large-scale retrospective modeling and prospective real-time deployment within intraoperative settings.Approach. A SVVNet was trained on arterial blood pressure (ABP) waveforms from 2849 patients undergoing general anesthesia at Asan Medical Center (AMC). For retrospective validation, we utilized AMC cohorts and a publicly accessible database to assess agreement, trending ability, noise robustness (quantifies via signal quality index), and inter-individual deviation against ABP-based pulse wave analysis (ABP-PWA) and other DL models. For prospective validation, the optimized model was deployed onto a tablet and prospectively evaluated in real-time during 67 surgeries.Main results. In the retrospective external validation, SVVNet achieved higher agreement mean absolute error (MAE = 0.70, Pearsonρ= 0.92), compared to ABP-PWA algorithm (MAE = 1.30, Pearsonρ= 0.80) and lower inter-individual deviation. It was more robust to signal noise (MAE = 4.33 vs 30.87). In the prospective real-time deployment, our deployed model achieved an MAE of 1.33 and a Pearson correlation of 0.87 against the ground truth.Significance. This study emphasizes the advantages of the DL-based model compared to ABP-PWA-based algorithms and presents prospective results that support the clinical applicability of SVVNet in the operating room. Our model has the potential to replace pre-existing monitoring systems and to enhance the complex surgical environment.
4 Apr 2026
Read appraisal →Intensive Care Med
Critical care management of the patient with pharmaceutical poisoning
Poisonings account for up to 10% of admissions to intensive care units and represent a common yet complex challenge in critical care. While most patients recover with supportive care alone, a significant proportion require targeted interventions and advanced organ support. This state-of-the-art review provides a practical, evidence-based guide to manage pharmaceutical poisoning in the intensive care unit, with emphasis on real-world applicability for intensivists. It highlights toxicant-specific considerations for early resuscitation, structured by the ABCDE approach. Essential principles of the diagnostic workup are also summarized. In addition, the review offers actionable guidance on when and how to escalate care, moving from supportive measures to specific interventions including gastrointestinal decontamination, extracorporeal toxicant elimination, antidote therapy, and rescue strategies such as intravenous lipid emulsion and extracorporeal membrane oxygenation. Key algorithms and decision pathways-such as the diagnostic evaluation, ABCDE-based stabilization, gastrointestinal decontamination, and extracorporeal elimination approaches-are presented with visually structured figures. A comprehensive table provides an overview of the most relevant antidotes used in critical care, including indications and dosing.
1 Dec 2025
Read appraisal →Intensive Care Med
Invasive candidiasis in intensive care medicine: shaping the future of diagnosis and therapy
BACKGROUND: Invasive candidiasis (IC) remains one of the most challenging infections in critical care, contributing significantly to morbidity, prolonged organ support, and mortality among intensive care unit (ICU) patients. The clinical landscape of IC is evolving, with increasing recognition of Candida non-albicans species and other yeasts formerly classified as Candida spp., alongside emerging multidrug resistance and growing complexity in host immune profiles. OBJECTIVES: This contemporary, multidisciplinary narrative review-authored by intensivists, infectious diseases specialists, clinical microbiologists, and pharmacologists-aims to provide ICU clinicians with practical, up-to-date insights into the diagnosis and management of IC. To maintain clinical focus, the review excludes non-IC fungal infections and non-ICU patient populations. METHODS: Relevant literature and expert consensus were critically reviewed to summarize current diagnostic and therapeutic approaches for IC in critically ill patients. Emphasis was placed on pragmatic clinical application, diagnostic limitations, antifungal stewardship, and personalized therapeutic decision-making. RESULTS: Despite the availability of novel antifungal agents with improved pharmacokinetic properties, treatment success in IC depends equally on timely and accurate diagnosis and individualized, context-aware therapy. Blood cultures continue to demonstrate limited sensitivity (~40%). Non-culture assays, including β-D-glucan and molecular diagnostics, provide faster detection and high negative predictive value but suffer from low positive predictive value and inconsistent adoption in clinical practice. The absence of validated host-derived biomarkers further limits risk stratification, antifungal discontinuation decisions, and personalized care. CONCLUSIONS: Emerging antifungal agents, stewardship strategies, and multidisciplinary care models are essential to improve clinical outcomes and reduce antifungal resistance. This review underscores the need for integrated, team-based diagnostic and therapeutic approaches to close persistent gaps in IC management, ultimately promoting more effective, timely, and individualized care for critically ill patients with Candida spp.
1 Nov 2025
Read appraisal →Blood Rev
Advances in the critical care management for patients with hematological malignancies
Hematological malignancies (HMs) are increasingly associated with life-threatening complications requiring intensive care unit (ICU) management. Recent advancements in therapies, diagnostics, and critical care protocols have improved outcomes for these patients, yet significant challenges persist. This manuscript explores the evolving landscape of critical care in hematology, emphasizing the unique complications, management strategies, and future directions in the field. Patients with HMs are particularly vulnerable to infections, sepsis, organ dysfunction, and treatment-related toxicities such as cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), and coagulopathies. Innovations in the management of acute respiratory failure, septic shock, and invasive fungal infections have contributed to better survival rates, yet outcomes remain suboptimal for certain high-risk groups. Furthermore, new therapies, including CAR-T cells, bispecific antibodies, and immune checkpoint inhibitors, present both opportunities and challenges in the ICU setting due to their potential toxicities. Emerging trends emphasize the importance of early ICU admission, multidisciplinary collaboration, and precision medicine in improving patient care. The integration of biomarker-driven strategies, advanced diagnostics, and artificial intelligence holds promise for optimizing therapeutic interventions and enhancing antimicrobial stewardship. Additionally, patient-centered approaches, including time-limited trials and goal-oriented discussions, aim to balance aggressive care with quality-of-life considerations. This review underscores the need for continued research to address disparities in access to care, improve long-term outcomes, and develop standardized protocols for managing critically ill hematology patients. By advancing the integration of oncology and critical care, clinicians can better navigate the complexities of modern therapies and provide holistic, evidence-based care that aligns with patient values and priorities.
1 Nov 2025
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