Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 3 appraisals
Analytical chemistry
Biodegradable Self-Powered Electrotherapy Patch for Integrated Smart Wound Management
Smart patches based on multimodal wearable devices enable real-time physiologic monitoring and proactive interventions to promote wound healing. Herein, we describe a biodegradable wearable electrotherapy patch (E-patch) that integrates noninvasive self-powered electrical stimulation (ES) therapy for tissue regeneration and a multiplexed electrochemical biosensor array for continuous monitoring of wound status. Custom-developed supercapacitor arrays (SCs) supply stable energy for ES, and constructed wearable biosensors enable sensitive monitoring of biomarkers in the wound exudate. As-fabricated wearable E-patches degrade harmlessly after operation, significantly reducing the environmental pollution pressure associated with flexible electronics. In vitro studies demonstrated that an applied electric field (EF) significantly promotes cell-directed alignment, which is crucial for tissue regeneration and remodeling. In vivo investigations in the Sprague-Dawley (SD) rat model illustrate that combination therapy dramatically accelerates wound healing. Overall, this work provides a promising strategy toward integrated smart wound management and future feedback-assisted wearable therapeutic systems.
15 July 2026
Read appraisal →Journal of diabetes science and technology
Artificial Intelligence for Diabetic Foot Screening Based on Digital Image Analysis: A Systematic Review
INTRODUCTION: Early detection of diabetic foot complications is essential for effective management and prevention of complications. Artificial intelligence (AI) technology based on digital image analysis offers a promising noninvasive method for diabetic foot screening. This systematic review aims to identify a study on the development of an AI model for diabetic foot screening using digital image analysis. METHODOLOGY: The review scrutinized articles published between 2018 and 2023, sourced from PubMed, ProQuest, and ScienceDirect. The keyword-based search resulted in 2214 relevant articles and nine articles that met the inclusion criteria. The article quality assessment was done through Quality Assessment of Diagnostic Accuracy Studies (QUADAS). Data were extracted and analyzed using NVivo. RESULTS: Thermal imagery or foot thermogram was the main data source, with plantar temperature distribution patterns as an important indicator. Deep learning methods, specifically artificial neural networks (ANNs) and convolutional neural networks (CNNs), are the most commonly used methods. The highest performance is demonstrated by the ANN model with MATLAB's Image Processing Toolbox that is able to classify each type of macula with 97.5% accuracy. The findings show the great potential of AI in improving the accuracy and efficiency of diabetic foot screening. CONCLUSION: This research provides important insights into the development of AI in digital image-based diabetic foot screening. Future studies need to focus on evaluating clinical applicability, including ethical aspects and patient data security, as well as developing more comprehensive data sets.
2 July 2026
Read appraisal →Lasers in medical science
Clinical dosimetry and efficacy of LED photobiomodulation for chronic lower-limb wound healing: a systematic review of randomized trials
Chronic lower-limb wounds represent a major clinical and socioeconomic burden due to delayed healing and high recurrence rates. Light-emitting diode (LED) photobiomodulation has been proposed as a noninvasive and low-cost adjunctive therapy; however, clinical evidence remains inconsistent. This systematic review aimed to synthesize evidence from randomized clinical trials investigating the efficacy of LED photobiomodulation for chronic lower-limb wound healing and to identify irradiation parameters associated with improved outcomes. A comprehensive search was conducted in PubMed, Scopus, Web of Science, and Embase up to May 2026. Six randomized clinical trials met the inclusion criteria. Wavelengths ranged from 620 to 950 nm, and energy densities varied between 2.4 and 126 J/cm². The findings suggest that LED photobiomodulation may promote wound area reduction, improve wound bed quality, and increase microcirculation, particularly in diabetic foot ulcers. However, one study using a high energy density (126 J/cm²) did not demonstrate beneficial effects, suggesting a possible dose-dependent response. The overall certainty of the evidence, assessed using the GRADE approach, was classified as very low due to inconsistency and indirectness among the included studies. Although LED photobiomodulation appears to be safe and demonstrates therapeutic potential, substantial heterogeneity in irradiation parameters, small sample sizes, and methodological limitations preclude definitive conclusions regarding its clinical efficacy. Well-designed randomized controlled trials with standardized protocols and dose-response investigations are needed to establish optimal therapeutic parameters and confirm clinical efficacy.
20 June 2026
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