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AI-Powered Remote Monitoring for Lower Extremity Wound Management: A Randomized Controlled Trial Protocol
Y H Andrew Wu1,2,3, Alana C Keegan1,4, Midori P Starks White1
1Division of Vascular Surgery and Endovascular Therapy, Johns Hopkins University, Baltimore, MD.
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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