Smartphone oxygenation measuring device to differentiate low-risk stable and chronic diabetic foot ulcers from high-risk complicated ulcers: a pilot study in India

Kacie Kaile, Alexander Trinidad, Venkatabashyam Ramnarayan,Coimbatore Subramanian Shanthi Rani,Ranjit Mohan Anjana, Vishwanathan Mohan,Ganesan Uma Sankari, Kumaradas Gini Venisha,Anuradha Godavarty

Optics and Biophotonics in Low-Resource Settings IX(2023)

引用 0|浏览12
暂无评分
摘要
India has over 74 million people currently diagnosed with diabetes today with similar to 35% at risk for diabetic foot ulcers (DFUs). Most patients with DFUs do not require hospitalization unless they have a severe infection with possible sepsis or require surgical intervention. Therefore, DFU care can remain remote for low-risk cases. However, high-risk DFU cases need to be identified and triaged to prevent worsening and hospitalization. These patients are catered to by nurses often performing home visits for wound dressing but with the least wound expertise. Hence, there is a need for point-of-care technologies to triage high-risk DFUs requiring clinical visitation vs stable low-risk DFUs. Recently, a smartphone device or SmartPhone Oxygenation Tool (SPOT) was developed as an add-on optical module to estimate 2D oxygen saturation maps. The hypothesis is that DFUs which are highly infectious or necrotic have poor oxygenation distribution around the wound and can be assessed using our SPOT device as high-risk ulcerations that would require clinical follow-up or visitation. A pilot study was conducted on 11 subjects (43-72 years and 9 male) at Dr. Mohan's Diabetes Specialties Center (India) to observe oxygen distributions in DFUs and determine if SPOT can be established to triage high-risk DFU cases. Oxygenation patterns in complicated (or high-risk) DFUs, as determined by the clinician, were notably different from those that were stable or low-risk DFUs.
更多
查看译文
关键词
Diabetic foot ulcers, near infrared spectroscopy, chronic wound management, telemedicine, smartphone, tissue oxygenation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要