ArticleJVS-vascular insights2025
AI-Powered Remote Monitoring for Lower Extremity Wound Management: A Randomized Controlled Trial Protocol.
Article in JVS-vascular insights, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05579743 (Feasibility of Remote Wound Care), which is not on this map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Feasibility of Remote Wound Care: Implementing a Patient-Centered Remote Wound Monitoring Solution Using a Smartphone Application
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Background: Lower extremity wounds associated with diabetes are a serious global health issue, with diabetic foot ulcers affecting 12% to 25% of adults with diabetes and accounting for 80-90% of all lower extremity amputations in the United States. Comprehensive in-person care for lower extremity wounds is important but can be burdensome for patients and costly for healthcare systems. A cost-effective telehealth model using a smartphone-integrated digital application that remotely analyzes wound status with machine-learning algorithms in real-time could make lower extremity wounds care more accessible to patients. This trial aims to determine if an artificial intelligence (AI)-powered digital remote monitoring is a feasible, patient-centered solution for remote wound monitoring and management compared to standard in-person visits. Methods: We will conduct a non-blinded randomized control trial of 120 patients with active lower extremity wounds treated in the Johns Hopkins Hospital Multidisciplinary Diabetic Foot and Wound Clinic in Baltimore, Maryland (ClinicalTrials.gov: NCT05579743). Participants will be randomly assigned 1:1 to receive wound care monitoring using AI-powered remote wound monitoring technology (Healthy.io Ltd.) or standard in-person monitoring for 12 weeks. The primary aim is to establish the feasibility of a novel remote patient-centered monitoring program for the surveillance and monitoring of lower extremity wounds. Secondary aims include evaluating patient and provider satisfaction with remote wound monitoring technology compared to standard in-person monitoring; and generating pilot data on wound healing time and major amputation rates in patients who are monitored remotely compared to patients treated with standard of care. Conclusion: This trial will determine whether AI-powered remote digital monitoring is feasible and acceptable as an alternative to standard in-person monitoring for the monitoring and management of patients with active lower extremity wounds.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.