Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 7 appraisals
Physics in medicine and biology
Anatomically adaptive feature-wise linear modulation for deep learning-based low-dose CT denoising
Objective.Low-dose computed tomography (LDCT) reduces radiation dose but, introduces heterogeneous noise due to different photon attenuation based on anatomical tissue. Most deep learning techniques assume uniform noise in LDCT and perform equal noise removal across different regions, leading to sub-optimal performance across different tissues. This work aims to design a physics-based framework that explicitly models region-dependent noise characteristics to improve LDCT noise removal.Approach.We propose an anatomically adaptive noise reduction framework. The proposed anatomically adaptive feature-wise linear modulation (FiLM) model consists of a U-Net architecture that integrates two complementary units: the global FiLM unit in the encoder, which modifies features globally based on global image statistics to remove overall noise, and the local FiLM unit in the decoder, which modifies features locally based on the type of anatomical tissue. This dual design enables the modeling of overall image noise characteristics in addition to the removal of local noise associated with each anatomical tissue.Main results.The model performance was evaluated using AAPM-Mayo Clinic LDCT dataset, and the trained model tested on the TCIA dataset. The proposed model outperformed all competing methods. Local noise analysis showed that noise removal was consistent across different anatomical regions, achieving 37.14% in the lung, 48.75% in soft tissue, and 35.18% in bone. Visual results also confirmed significant improvements in noise removal, preservation of structural details, and reduction of non-residual distortions. Furthermore, the model demonstrated its ability to generalize under domain shift.Significance.This work presents a framework for anatomically adapted noise removal by linking feature modification with the physical properties of noise in LDCT through a dual-modulation process for both general and tissue-related noise. The model achieves a balance between noise removal and preservation of anatomical detail, making it a robust approach to LDCT noise removal.
28 July 2026
Read appraisal →Pediatric surgery international
ARM in ARM? Investigating the co-occurrence of anorectal malformations and labioscrotal anomalies.
Anorectal malformations (ARMs) are known to be associated with other defects, however there is no evidence addressing the co-occurrence of ARMs with anomalies of structures derived from the labioscrotal folds. We performed a systematic review (Prospero: CRD420251013945) aiming at investigating correlations and patterns between ARMs and labioscrotal anomalies (LSAs), when presenting simultaneously. Our search identified 1642 articles. After abstract screening, 344 full texts were assessed and 144 met the inclusion criteria. In total, these reported on 319 individual cases with both ARM and LSA. Individuals with complex ARMs had proportionally the most LSAs associated with their ARM - 58.4% of these were associated with only a single LSA. For 'high' and 'low' ARMs, 66.0% and 77.0% of cases were associated with a single LSA respectively. As data reporting prevalence of each type of ARM lacks information about LSAs, the potential to predict the presence of LSAs according to type of ARM is limited. Nevertheless, this review demonstrates a frequent association of ARMs with LSAs, that has not been previously described. This evidence highlights the importance of early screening and timely management of LSAs in patients with any type of ARM, with close collaboration between paediatric surgeons, urologists and other clinicians.
20 July 2026
Read appraisal →Diagnostic and interventional imaging
Artificial intelligence in emergency musculoskeletal imaging: A critical review of current applications.
Artificial intelligence (AI) is increasingly shaping emergency musculoskeletal imaging, where rapid and accurate diagnosis is often challenged by high imaging volumes and time pressure. These constraints increase the risk of missed injuries and underscore the need for tools that support faster and reliable assessments. AI systems show promise in improving workflow efficiency by prioritizing urgent studies, guiding modality selection, and reducing reporting delays. Deep learning models can enhance abnormality detection by identifying fractures, soft tissue injuries, and infectious processes, and can provide structured classifications that support clinical decision making. Pediatric-focused AI systems address age-specific developmental considerations and offer valuable support for clinicians with varying levels of pediatric musculoskeletal expertise. Large language models further expand the role of AI by improving report clarity, generating structured impressions, and facilitating communication with clinicians, patients, and families. Despite these advances, challenges remain, including limited external validation, dataset bias, and medicolegal considerations. This review summarizes current AI applications across these domains and highlights key strengths, limitations, and future directions for safe and effective integration into emergency musculoskeletal imaging.
2 July 2026
Read appraisal →Blood advances
Accurate identification of sickle cell disease cases in a large genotyped cohort using electronic health record data
The US Food and Drug Administration recently approved sickle cell disease (SCD) gene therapies that require a contemporaneous cohort to compare their outcomes with those of individuals who did not receive gene therapy. Previously, we developed an automated algorithm to create a contemporaneous cohort of children and adults with SCD using electronic health record data. We tested the hypothesis that the updated Vanderbilt University Medical Center (VUMC) algorithm can identify individuals with SCD with sensitivity and specificity of >95%. In the VUMC health care system, we identified a cohort of 33 141 adults and children of primarily African ancestry who underwent β-globin gene sequencing, with a 1.4% prevalence of SCD (473/33 141). For SCD, the performance of the VUMC algorithm using International Classification of Diseases (ICD) and laboratory data showed a sensitivity of 97.6% (462/473), specificity of 99.9% (32 663/32 668), positive predictive value of 98.9% (462/467), and negative predictive value of 99.9% (32 663/32 674). Three SCD phenotypes account for 98.5% of the individuals in the cohort. The cohort had sensitivities of 96.8% (272/281), 93.7% (136/145), and 85% (34/40) for hemoglobin SS (HbSS)/Hb Sβ0-thalassemia (HbSβ0), HbSC, and HbSβ+, respectively. The cohort had a specificity of 99.9% across all 3 phenotypes: HbSS/HbSβ0, HbSC, and HbSβ+, respectively. We have developed an updated algorithm using ICD and laboratory data that accurately identifies individuals with SCD within a large health care system, and distinguishes HbSS/HbSβ0, HbSC, and HbSβ+.
9 June 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
Evolution of body image across treatment eras: a systematic review in young people and adults living with cystic fibrosis
OBJECTIVES: Advancements in treatments for cystic fibrosis (CF) have improved prognosis, but variant-specific therapies have also driven weight gain. Traditional challenges to maintain weight are now less prevalent, with new body image concerns potentially emerging. This review aims to synthesise quantitative and qualitative evidence on body image in adults and young people (aged ≥16 years) with CF. METHODS: Systematic search of MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health, the Allied and Complementary Medicine Database and the Cochrane Library (January 2011 to August 2025) using CF-related keywords including body image and physical appearance. RESULTS: Searches retrieved 29 eligible studies (26 quantitative, two qualitative, one mixed methods). The Cystic Fibrosis Questionnaire - Revised (CFQ-R) and Cystic Fibrosis Quality of Life Questionnaire (CFQoL) questionnaires assessed body image quantitatively (0-100). 15 studies reported CFQ-R body image scores (58±19 to 78±23) and five reported CFQoL body image scores (21±26 to 76). Pre-modulator era (≤2012) scores ranged from 64±27 to 70±27; initial rollout phase (2012-2019) scores ranged from 58±19 to 81 (post-ivacaftor); and in the widespread modulator era (2020 to present) were 63±32 to 67 (31). Gender effects were inconsistent. Higher body mass index, weight, and body fat were linked to better body image in some studies; psychological wellbeing and lower anxiety/depression consistently correlated with body image. Ivacaftor and life coaching improved body image, while elexacaftor/tezacaftor/ivacaftor, cognitive behavioural therapy, and self-management programmes showed no effect. Functional health was strongly linked to body image.Qualitative findings highlighted influences of gender, weight change, functional and mental health, social support, early eating experiences, and limited clinician-initiated body image discussions. CONCLUSION: This is the first systematic review of body image in CF since new drug regimens emerged. Emerging body image disturbance patterns highlight the need for clinical strategies to screen for and address body image issues in CF care.
15 May 2026
Read appraisal →American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists
Evaluating medication record creation before and after an electronic health record transition
PURPOSE: In 2022, St. Jude Children's Research Hospital underwent an electronic health record (EHR) transition, migrating from Cerner Millennium to Epic. This transition required a comprehensive revision of the medication build and configuration process and, subsequently, prompted an analysis of lessons learned during the transition. Through enhancement of the medication build and configuration process, the standardized procedure increases collaboration with subject matter experts and other departments within the institution as medication records are created. SUMMARY: The transition involved stakeholder meetings with members from operational leadership, informatics, medication safety, and pharmacy inventory management to update the existing process to support the new system. Through the creation of an initial version and subsequent iterations, the process was refined to efficiently support and control the quality of medication build requests. The updated process also maintained existing oversight over the entire process. The transition highlighted differences between the original EHR and the updated EHR in the management of medication builds. The differences between the EHRs and medication build processes presented a learning curve for individuals involved in medication builds and resulted in an initial lengthening of the turnaround time. Following iterative improvements to the usability of the medication build process and enhancements in automatic communication, the turnaround time substantially decreased. CONCLUSION: The insights gleaned from the transition process underscore the importance of aligning operational processes with user needs, fostering iterative improvements, prioritizing effective communication, and maintaining a delicate balance between urgency and accuracy in managing medication record creation and configuration within EHRs. This knowledge can be used to guide the creation of a medication build process or transition from an existing process.
24 Apr 2026
Read appraisal →Journal of the American Heart Association
Ex Vivo Effect of Apixaban on Hemostatic Biomarkers in Children With Heart Disease: A SAXOPHONE Trial Substudy
BACKGROUND: The SAXOPHONE (Safety of Apixaban on Pediatric Heart Disease on the Prevention of Embolism) trial demonstrated the safety of apixaban for thromboprophylaxis in children with heart disease. Included a priori in the trial design was an exploratory biomarker substudy to evaluate the effects of apixaban on surrogate biomarkers of efficacy, thrombin generation capacity, and hemostatic proteins. The study assessed changes in d-dimer, thrombin generation assay parameters, factor VIII, fibrinogen, protein C, and protein S in children receiving apixaban compared with standard-of-care vitamin K antagonists (VKAs) or low-molecular-weight heparin. METHODS: SAXOPHONE participants aged >1 year (n=182) had blood samples for biomarkers collected at baseline, week 2, or month 6. Participants were randomized to apixaban (n=123) or standard of care (VKA or low-molecular-weight heparin; n=59). Subgroup analyses accounted for prior VKA exposure. RESULTS: d-dimer levels decreased at month 6 in all treatment groups and remained stable during VKA-to-apixaban bridging. Apixaban significantly prolonged thrombin generation assay lag time and time to peak compared with VKAs and decreased peak thrombin similarly to VKAs in anticoagulant-naïve participants. Apixaban was associated with decreased fibrinogen and factor VIII at month 6, with no effect on protein C or S. Prior VKA exposure produced carryover effects, suppressing baseline d-dimer, thrombin generation assay parameters, and proteins C and S. CONCLUSIONS: Apixaban reduced hypercoagulability, as shown by decreased d-dimer levels and prolonged lag time, and preserved endogenous thrombin potential in thrombin generation assay, changes consistent with adult data. These findings align with SAXOPHONE's primary outcomes, supporting apixaban's favorable risk-benefit profile as a thromboprophylaxis option in children with heart disease.
8 Apr 2026
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