Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 14 appraisals
Computer assisted surgery (Abingdon, England)
DMRNet: a dynamic multi-scale residual network for Shamrock view and lumbar plexus segmentation
Lumbar plexus block (LPB) is a regional anesthesia technique widely used for hip and knee surgeries. However, despite the assistance of ultrasound guidance, the complex anatomical structure of the lumbar plexus poses significant challenges for anesthesiologists during the procedure. To accurately identify the lumbar plexus located in the posterior third of the psoas major in the Shamrock view, a deep learning-based segmentation model named DMRNet was proposed. This model is designed to precisely delineate muscles, nerves, and bony structures in Shamrock view ultrasound images. DMRNet integrates several innovative modules, including Adaptive Multi-Scale Dilated (AMD) Module that enhances the model's ability to capture multi-scale features; Dense Attention Residual (DAR) Module that adaptively selects salient feature regions; Attention-Enhanced Hybrid (AEH) Module that emphasizes critical features while suppressing irrelevant ones; and two attention mechanisms, Boundary-Aware Spatial Attention Mechanism (BASA) and the Enhanced Residual Multi-Head Attention Mechanism (ER-MHA), that improve the model's capacity to recognize complex contextual patterns. Experimental results demonstrated that DMRNet achieved a mean Intersection over Union of 0.863 and a mean Dice coefficient of 0.926 across all target structures, outperforming other state-of-the-art models. These findings suggest that DMRNet may serve as a useful assistive tool for sonoanatomical recognition in Shamrock view ultrasound images and may provide educational support for ultrasound-guided LPB training. A dynamic multi-scale residual network is proposed for lumbar lexus (LP) segmentation.Two attention mechanisms were improved, and three modules were proposed to improve downsampling, skip connection, and upsampling.We built our own Shamrock view ultrasound database containing the lumbar plexus nerves, and the Anesthesiologist physician of the anesthesiology department annotated it using Labelme.External validation was performed using the Ultrasonic Brachial Plexus Dataset (UBPD).
14 June 2026
Read appraisal →Journal of the American College of Surgeons
What Is Included in Pediatric Enhanced Recovery After Surgery Protocols and How to Encourage Adoption: A Systematic Review of the Literature
The present systematic review is the first to describe and analyze the breadth of enhanced recovery after surgery (ERAS) elements across various pediatric surgery procedures. The aim of the article is to provide a compendium of ERAS elements that are used in pediatric protocols to identify both gaps and variation. In response to these findings, we then propose a methodology for addressing the gaps and variation we found and furthering the use of ERAS in pediatric surgery.
14 June 2026
Read appraisal →PloS one
Long term evaluation of the safety and efficacy of local cooling anesthesia during intravitreal injections: The COOL-2 Trial
BACKGROUND/OBJECTIVE: To evaluate the safety and effectiveness of a medical device providing cooling anesthesia to the eye as local anesthesia for intravitreal (IVT) injections. SUBJECTS/METHODS: As a multicenter, open label, dose escalation clinical trial, subjects receiving at least 3 IVT injections in the study eye were recruited to participate. All patients received subconjunctival lidocaine as their anesthesia for previous IVT injections. Subjects receiving IVT injections were assigned (non-randomized) to four groups in which the cooling device was applied to the conjunctiva at the location of the intravitreal injection: Group 1: -10˚C for 20 seconds; Group 2: -15˚C for 10 seconds; Group 3: -15˚C for 15 seconds; and Group 4: -15˚C for 20 seconds. The primary outcome was pain during IVT injection assessed by a visual analog scale (0-10). RESULTS: Eighty subjects were enrolled at 2 sites. The mean number of prior IVT injections was 20.3 for Group 2 and 15.0 for Group 3. Pain was significantly less for the 10 second vs the 15 second application (2.2 vs 3.6, p = 0.0255). The mean pain score was lower for Group 2 (-15°C for 10 seconds) ranging a score of 1.0 to 2.9 across the study visits, compared with Group 3 (-15°C for 15 seconds) with a mean range of 3.2 to 5.2 across the study visits. Treatment order (visit) significantly decreased by 0.10 pain units per visit (p = 0.0002). Punctate epithelial erosions (PEE) were reported in 20 of 56 eyes (35.7%) in Group 2, none were reported in Group 3. CONCLUSION: Cooling anesthesia device reduced the severity of pain associated with IVT injection during the procedure, although mild and transient PEE may be associated with treatment. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT03956797.
13 June 2026
Read appraisal →Regional anesthesia and pain medicine
Recommendations for disclosure of artificial intelligence in scientific writing and publishing: a regional anesthesia and pain medicine modified Delphi study
INTRODUCTION: The use of artificial intelligence (AI) in the scientific process is advancing at a remarkable speed, thanks to continued innovations in large language models. While AI provides widespread benefits, including editing for fluency and clarity, it also has drawbacks, including fabricated content, perpetuation of bias, and lack of accountability. The editorial board of Regional Anesthesia & Pain Medicine (RAPM) therefore sought to develop best practices for AI usage and disclosure. METHODS: A steering committee from the American Society of Regional Anesthesia and Pain Medicine used a modified Delphi process to address definitions, disclosure requirements, authorship standards, and editorial oversight for AI use in publishing. The committee reviewed existing publication guidelines and identified areas of ambiguity, which were translated into questions and distributed to an expert workgroup of authors, reviewers, editors, and AI researchers. RESULTS: Two survey rounds, with 91% and 87% response rates, were followed by focused discussion and clarification to identify consensus recommendations. The workgroup achieved consensus on recommendations to authors about definitions of AI, required items to report, disclosure locations, authorship stipulations, and AI use during manuscript preparation. The workgroup formulated recommendations to reviewers about monitoring and evaluating the responsible use of AI in the review process, including the endorsement of AI-detection software, identification of concerns about undisclosed AI use, situations where AI use may necessitate the rejection of a manuscript, and use of checklists in the review process. Finally, there was consensus about AI-driven work, including required and optional disclosures and the use of checklists for AI-associated research. DISCUSSION: Our modified Delphi study identified practical recommendations on AI use during the scientific writing and editorial process. The workgroup highlighted the need for transparency, human accountability, protection of patient confidentiality, editorial oversight, and the need for iterative updates. The proposed framework enables authors and editors to harness AI's efficiencies while maintaining the fundamental principles of responsible scientific communication and may serve as an example for other journals.
7 June 2026
Read appraisal →JMIR research protocols
Virtual Reality for Preoperative Anxiety in Patients Undergoing Odontectomy Under General Anesthesia: Protocol for a Randomized Controlled Trial
BACKGROUND: Odontectomy is a common surgical procedure often associated with significant preoperative anxiety, particularly when performed under general anesthesia. Anxiety can lead to physiological changes, such as increased blood pressure and heart rate, and may affect anesthetic requirements and postoperative recovery. Virtual reality (VR) has emerged as a promising non-pharmacological intervention to reduce anxiety through immersive distraction. OBJECTIVE: This study aims to evaluate the effectiveness of VR in reducing preoperative anxiety in patients undergoing odontectomy under general anesthesia. The study will assess anxiety using both subjective measures (Amsterdam Preoperative Anxiety and Information Scale, APAIS) and objective biomarkers (salivary alpha-amylase, salivary cortisol, and vital signs). METHODS: This is a prospective, randomized controlled trial. Patients aged 17-40 years undergoing odontectomy under general anesthesia at the Dental and Oral Hospital, Universitas Padjadjaran, will be recruited. Participants (n=32) will be randomly assigned to either the intervention group (VR experience of the operating room) or the control group (standard verbal education). Data collection includes salivary samples (alpha-amylase and cortisol), vital signs (blood pressure, heart rate, respiratory rate), and APAIS scores measured at baseline, immediately post-intervention, and 15 minutes post-intervention. Data will be analyzed using independent and paired t tests or Mann-Whitney and Wilcoxon tests, depending on normality. RESULTS: The study is scheduled to be conducted between October 2026 and December 2026. The findings will provide evidence regarding the efficacy of VR as a standard anxiolytic tool in oral surgery. CONCLUSIONS: If effective, VR could serve as a non-invasive, safe alternative to pharmacological premedication for managing preoperative anxiety, potentially improving surgical outcomes and patient comfort.
29 May 2026
Read appraisal →PloS one
Comparison between two different concentrations of ropivacaine in pericapsular nerve group block for patients undergoing total hip arthroplasty: A randomized clinical trial
Effective pain control during spinal anesthesia positioning remains a clinical challenge in elderly patients undergoing total hip arthroplasty. The pericapsular nerve group block, a novel ultrasound-guided regional anesthesia technique, has shown promise for alleviating hip pain, yet the optimal concentration of local anesthetics for this approach remains unclear. In this randomized, observer-blinded clinical trial involving 102 patients, we compared the analgesic efficacy of two concentrations of ropivacaine (0.375% vs. 0.5%) administered via pericapsular nerve group block prior to spinal anesthesia. Patients receiving 0.5% ropivacaine reported significantly lower pain scores during positioning and demonstrated prolonged postoperative analgesia up to 48 hours, without a corresponding increase in adverse events. Both concentrations improved positioning quality, reduced opioid requirements, and enhanced recovery compared to controls who received standard intravenous analgesic supplementation (including preoperative midazolam and ketorolac, and postoperative sufentanil PCA), though the higher concentration yielded modest additional benefits. These findings suggest that a 0.5% ropivacaine pericapsular nerve group block may offer superior perioperative analgesia for hip arthroplasty without compromising safety, while highlighting the need to balance analgesic potency with potential motor effects. This study informs optimization of nerve block protocols to improve perioperative outcomes in a high-risk surgical population. This study informs optimization of nerve block protocols to improve perioperative outcomes in a high-risk surgical population. The trial was registered with the Chinese Clinical Trial Registry (registration number: ChiCTR2400089440).
23 May 2026
Read appraisal →PloS one
Double-cuff versus single-cuff bronchial blockers for video-assisted thoracoscopic lobectomy: A randomized controlled trial
BACKGROUND: Bronchial blockers (BBs) manage airways during thoracoscopic lobectomy and isolate lungs by occluding the bronchus at the surgical site. However, intraoperative malpositioning remains a concern. We compared the performance of a new double-cuff BB (DcBB) with an additional cuff near the end of a single-cuff BB (ScBB) with that of ScBBs during thoracoscopic lobectomy. METHODS: This single-center, randomized, parallel, controlled clinical study enrolled 80 patients undergoing thoracoscopic lobectomy for lung cancer at Nanpi People's Hospital. The patients were randomized into two groups (n = 40 each); DcBB (DcBB used during one-lung ventilation) and ScBB (ScBB used during one-lung ventilation). The primary outcomes were the incidence and number of BB malpositioning. Secondary outcomes time for BB placement and positioning, surgical duration, hypoxemia, incidence of adverse cardiovascular events, grades of lung collapse, surgeon satisfaction, tracheal wall damage assessed during bronchoscopy, contamination rates of the non-surgical lung lobe on the surgical site determined by bronchoscopy, radiographic incidence of pulmonary infiltration on postoperative day 1, and intraoperative blood gas values. RESULTS: The incidence of malpositioning was significantly lower in the DcBB than the ScBB group (7.5% vs. 30%, P = 0.02). The incidence of malposition was significantly lower in the DcBB cohort (P = 0.002). However, positioning the DcBB required more time (32.28 ± 5.37 vs. 19.90 ± 4.16 sec, P < 0.001). Other secondary outcomes did not differ significantly. CONCLUSIONS: In patients undergoing thoracoscopic lobectomy, the DcBB was associated with a lower incidence of malposition than the ScBB. The DcBB did not increase tracheal wall injury or cause significant adverse hemodynamic effects, and therefore may serve as a promising optional device for airway management during thoracoscopic lobectomy, particularly in clinical scenarios requiring high placement stability. TRIAL REGISTRATION: the Chinese Clinical Trial Registry ChiCTR2400086472.
22 May 2026
Read appraisal →BMC anesthesiology
Automated end-tidal control versus manual regulation in low-flow volatile anesthesia: a systematic review and meta-analysis
BACKGROUND: In low-flow anesthesia, automated monitoring of end-tidal oxygen (etO2) and end-tidal anesthetic agents (etAA) has been favored to reduce clinicians' cognitive workload during anesthesia maintenance. This systematic review, therefore, aimed to determine the comparative efficacy and safety of automated end-tidal controlled anesthesia (etCA) versus manually controlled anesthesia (MCA). METHODS: An electronic search was conducted across four databases: PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, and Scopus. The retrieved references were then analyzed against the studies' screening and eligibility criteria before the full articles were included in the study. The Review Manager (RevMan 5.4.1) was then used to conduct the statistical analysis of the reported outcomes. RESULTS: The electronic search retrieved 965 articles, among which 10 were included in this review. The studies included a pooled sample size of 1269 who underwent surgical procedures under low-flow anesthesia. The analyzed evidence suggests with low certainty that the type of anesthesia control may not have any significant effect on both the anesthesia duration (SMD - 0.00 min; 95% CI [-0.34, 0.34] p = 0.99) and the procedural duration MCA (SMD 0.04 min; 95% CI; 95% CI [-0.26, 0.33] p = 0.80). Moreover, we found with low certainty in the evidence that the amount of sevoflurane consumed may not be significantly different between etCA and MCA (SMD - 0.32 mLs; 95% CI [-0.94, 0.29] p = 0.31). Our narrative synthesis indicated that etCA can potentially improve anesthesia delivery by reducing the required anesthetist interventions and ensuring stable and accurately administered anesthetics. CONCLUSION: This review found very low-quality evidence suggesting that the type of anesthesia control may not significantly affect anesthesia delivery parameters, such as the amount of anesthesia consumed and procedural and anesthesia duration. The analyses, however, had significant heterogeneity, making the estimates highly unreliable. On the other hand, some studies indicate potential advantages of using etCA, such as reducing the number of interventions required during anesthesia; however, the evidence remains limited, preventing a full exploration of these advantages.
15 May 2026
Read appraisal →Asian journal of psychiatry
Machine learning prediction model for delirium after heart valve replacement with cardiopulmonary bypass: A large-scale cohort study
OBJECTIVE: Postoperative delirium (POD) is a common and severe complication following heart valve replacement (HVR) with cardiopulmonary bypass (CPB), associated with poor outcomes. Accurate early prediction is crucial for targeted prevention. This study aimed to develop and externally validate machine learning (ML) models for predicting POD in this high-risk population. METHODS: We conducted a retrospective cohort study involving 1076 adult patients who underwent HVR with CPB between January 2018 and December 2022. POD was assessed using the CAM-ICU. Perioperative factors were analyzed to develop a traditional logistic regression-based nomogram and four ML models. The best-performing model was then tested on an independent external validation cohort of 281 patients. RESULTS: The incidence of POD was 25.1% (270/1076) and was associated with significantly increased mortality (11.9% vs. 0.2%, P < 0.001) and prolonged hospitalization. In the internal test set, the Random Forest (RF) model demonstrated the highest predictive performance with an AUROC of 0.854 (95% CI, 0.764-0.945), outperforming the traditional nomogram (AUROC: 0.754). The RF model maintained robust performance in the external validation cohort, achieving an AUROC of 0.793. Model interpretation using SHAP analysis identified postoperative awakening time (PAT), postoperative mechanical ventilation time (PMVT), and postoperative reintubation (POR) as the most influential predictors. CONCLUSIONS: Machine learning models, particularly Random Forest, provide a robust and generalizable tool for the early prediction of POD after HVR. These models outperform traditional statistical approaches and offer interpretable insights, highlighting PAT as a critical, modifiable target for perioperative management to mitigate POD risk.
9 May 2026
Read appraisal →Regional anesthesia and pain medicine
Anesthetic approaches and 2-year recurrence rates in non-muscle invasive bladder cancer: a randomized clinical trial
BACKGROUND: The effect of anesthesia methods on non-muscle invasive bladder cancer (NMIBC) recurrence post-resection remains uncertain. We aimed to compare the oncological outcomes of spinal anesthesia (SA) and general anesthesia (GA) in patients with NMIBC. METHODS: This prospective randomized controlled trial recruited 287 patients with clinical NMIBC at Seoul National University Hospital from 2018 to 2020. The patients underwent transurethral resection of the bladder tumor within 4 weeks of randomization. Intrathecal hyperbaric bupivacaine (0.5%) and a mixture of propofol (1-2 mg/kg) and fentanyl (50-100 μg/kg) were used as induction agents in the SA and GA groups, respectively, with desflurane or sevoflurane used for maintaining anesthesia. The primary and secondary outcome measures were disease recurrence and disease progression, respectively, at 2 years after resection. Cumulative incidence of outcomes was compared between the two groups using time-to-event analyses. RESULTS: 15 patients required alternative anesthesia owing to clinical needs such as SA failure or significant obturator reflex, resulting in a modified intention-to-treat (ITT) population of 272 patients. Time-to-event analysis showed a significantly lower recurrence of NMIBC in the SA group than in the GA group, in both ITT (27.4% vs 39.8%) and modified ITT populations (26.8% vs 39.6%). Disease progression occurred more frequently in the GA than in the SA group (15.2% vs 7.8%), although the difference was not statistically significant. CONCLUSIONS: A notable reduction in the 2-year recurrence rate was observed in patients who underwent SA than in those who underwent GA. Thus, SA may be considered the preferred anesthetic approach. TRIAL REGISTRATION NUMBER: NCT03597087.
4 Apr 2026
Read appraisal →Regional anesthesia and pain medicine
Efficacy and safety of intrathecal adjuvants for perioperative management of cesarean delivery: a systematic review and network meta-analysis of randomized controlled trials
BACKGROUND: Cesarean section (CS) rates have increased globally, necessitating effective anesthesia management. Single-shot spinal anesthesia has limitations due to its duration and the dose-limiting adverse effects of local anesthetics. OBJECTIVES: To evaluate the effectiveness and safety of intrathecal adjuvants combined with local anesthetics in the perioperative management of CS pain. DESIGN: Systematic review with network meta-analysis. DATA SOURCES: PubMed, Cochrane Library for Clinical Trials, and Embase. ELIGIBILITY CRITERIA: We included women undergoing CS under single-shot spinal anesthesia with any intrathecal drug or placebo added to a long-acting local anesthetic. We selected single- or double-blind, parallel-group, randomized controlled trials (RCTs) reported in English. We excluded crossover, non-randomized, up-and-down dose-finding studies and clinical trials comparing the same drugs in all study arms. RESULTS: We included 166 RCTs with 14 925 patients assigned to 32 interventions. Buprenorphine and diamorphine were the highest-ranked treatments for reducing pain intensity at 24 hours, though not statistically significant. Morphine alone or in combination with meperidine, neostigmine, epinephrine, or nalbuphine significantly increased the duration of effective analgesia and reduced opioid consumption. Dexmedetomidine and morphine significantly prolonged the motor block duration. The safety profile of intrathecal adjuvants was generally adequate. CONCLUSIONS: While the strength of evidence, overall, was very low to low, our study suggests that while none of the interventions significantly reduced pain intensity at 24 hours, several significantly prolonged effective analgesia and reduced postoperative opioid consumption. Dexmedetomidine and morphine prolonged the duration of motor block. None of the intrathecal adjuvants evaluated significantly increased the occurrence of severe adverse events. Future large-scale RCTs are essential to provide more robust evidence. PROSPERO REGISTRATION NUMBER: CRD42024479424.
4 Apr 2026
Read appraisal →Current opinion in anaesthesiology
Data integration and systems interoperability: the prerequisite for artificial intelligence in anesthesiology
PURPOSE OF REVIEW: Anesthesiology generates large volumes of heterogeneous perioperative data, including high-resolution physiological signals, clinical documentation, and device-generated information. Despite this richness, the clinical deployment of artificial intelligence systems remains limited. This review examines how limitations in data integration and systems interoperability constrain the translation of artificial intelligence into routine practice. RECENT FINDINGS: Recent literature indicates that the principal barrier to artificial intelligence adoption in anesthesiology is not algorithmic performance but inadequate data integration. Data are distributed across anesthesia information management systems, electronic health records, and multiple medical devices, with variable data models, inconsistent semantic representations, and limited temporal synchronization. These systems were primarily designed for documentation, billing, and medicolegal purposes, rather than real-time analytics or secondary data use. In contrast, intensive care medicine has benefited from early investments in shared databases, which have facilitated reproducible artificial intelligence research and validation. Although emerging standards such as HL7 Fast Healthcare Interoperability Resources and common data models provide technical frameworks for interoperability, their implementation in anesthesiology remains partial. SUMMARY: The effective deployment of artificial intelligence in anesthesiology depends on the development of interoperable, high-quality data infrastructures. Establishing standardized data models, semantic harmonization, temporal alignment, and robust data governance is a prerequisite for scalable, trustworthy artificial intelligence-enabled perioperative care.
4 Apr 2026
Read appraisal →Curr Opin Pulm Med
Foreign body removal
PURPOSE OF REVIEW: Airway foreign body aspiration remains a potentially life-threatening emergency, predominantly affecting children under 5 years and adults over 65 years. This review synthesizes current evidence on diagnostic strategies, bronchoscopic extraction techniques, procedural outcomes, complication management, and emerging technologies in airway foreign body management. RECENT FINDINGS: Multidetector computed tomography with three-dimensional reconstruction has significantly improved diagnostic accuracy, achieving sensitivity of 98-99% for radiopaque objects and 85-92% for radiolucent materials. Flexible bronchoscopy has evolved from a diagnostic tool to a first-line therapeutic modality, with recent pediatric meta-analyses demonstrating 87% success rates and adult series showing comparable outcomes to rigid bronchoscopy for appropriately selected cases. Rigid bronchoscopy maintains superiority in asphyxiating presentations, and for large (>1.5 cm), sharp, or severely impacted foreign bodies. Technological innovations including robotic-assisted bronchoscopy, electromagnetic navigation systems, and artificial intelligence-powered imaging analysis are enhancing procedural precision and safety. SUMMARY: Successful airway foreign body management requires individualized, multidisciplinary approaches integrating patient clinical status, foreign body characteristics, and institutional expertise. Success depends on appropriate bronchoscopic modality selection, comprehensive preprocedural planning, availability of specialized retrieval instruments, and readiness to manage potential complications. Integration of advanced imaging, simulation-based training protocols, and telemedicine consultation are becoming essential components of contemporary practice.
1 Jan 2026
Read appraisal →Adv Anesth
The Current Use of Artificial Intelligence in Anesthesiology
Artificial intelligence (AI) applications are increasingly being used in areas of medicine such as radiology. However, within anesthesiology, there is not widespread use of AI applications at this time, though it has the potential to have a profound impact. Many applications of AI, including machine learning, deep learning, and natural language processing, are being used to create applications to enhance patient monitoring, optimize drug administration, improve decision-making, and predict postoperative complications.
1 Dec 2025
Read appraisal →