Title: Nano sensors for Wound Care Monitoring
PI: J. Peter Rubin, MD
Description: This proof of concept study is to determine whether a verifiable fingerprint can be determined in a diabetic foot ulcer (DFU) using Nano sensor technology guided by an artificial intelligence algorithm. Based off our animal model comparing malignant and non-malignant cells, we would expect to be able to develop an initial diabetic foot ulcer AI fingerprint using swabs collected from the DFU wounds of 15 participants.
Primary & Secondary Objectives: Hypothesis: The goal of the study is to test whether the AI can distinguish from the chemical fingerprint of the swabs, initially testing predicting non-chronic versus chronic for the AI’s initial yes/no question.
Secondary analysis: We will also have a technical testing question, whether there is any difference between the 2 swabs tested immediately on site at UPMC McKeesport the day of the consent/screening visit versus the 2 swabs tested back at Dr. Star’s Eberly Hall lab.
Measurement/Outcomes:
- Assessing whether a distinct, identifiable AI fingerprint can be determined from a swab of the diabetic foot ulcer’s cleaned wound.
- Assessing whether the AI can successfully identify the type of DFU wound (acute versus chronic) from the swabs collected, compared to the subject’s collected data.
Numbers of subjects to have swab collection: 15
For more information, please contact:
Patsy Simon, BS, RN, CCRC, CCRA, ACRP-PM
Director, Operations and Administration
Center for Innovation in Restorative Medicine (CIRM)
University of Pittsburgh, Department of Plastic Surgery
6B Scaife Hall, room 664
3550 Terrace Street
Pittsburgh, PA 15261
Phone: 412-648-9207
simonpa@upmc.edu