2 research outputs found
Mortality in 98 type 1 diabetes mellitus and type 2 diabetes mellitus: Foot ulcer location is an independent risk determinant
From Wiley via Jisc Publications RouterHistory: received 2020-10-04, rev-recd 2021-02-18, accepted 2021-03-24, pub-electronic 2021-06-14Article version: VoRPublication status: PublishedAbstract: Introduction: We previously demonstrated in both a longitudinal study and in meta‐analysis (pooled relative‐risk RR, 2.45) that all‐cause mortality is significantly higher in people with diabetes foot ulceration (DFU) than with those without a foot ulcer. In this prospective study, we looked at the factors linked to mortality after presentation to podiatry with DFU. Methods: Ninety‐eight individuals recruited consecutively from the Salford Royal Hospital Multidisciplinary Foot Clinic in Spring 2016 were followed up for up to 48 months. Data concerning health outcomes were extracted from the electronic patient record (EPR). Results: Seventeen people (17) had type 1 diabetes mellitus, and 81 had type 2 diabetes mellitus. Thirty‐one were women. The mean age (range) was 63.6 (28–90) years with maximum diabetes duration 45 years. Mean HbA1c was 72 (95% CI: 67–77) mmol/mol; 97% had neuropathy (International Working Group on the Diabetic Foot (IWGDF) monofilament); 62% had vascular insufficiency (Doppler studies); 69% of ulcers were forefoot, and 23% of ulcers were hind foot in location. Forty of 98 (40%) patients died in follow‐up with 27% of death certificates including sepsis (not foot‐related) and 35% renal failure as cause of death. Multivariate regression analysis indicated a 6.3 (95% CI: 3.9–8.1) fold increased risk of death with hind foot ulcer, independent of age/BMI/gender/HbA1c/eGFR/total cholesterol level. Conclusion: This prospective study has indicated a very high long‐term mortality rate in individuals with DFU, greater for those with a hind foot ulcer and shown a close relation between risk of sepsis/renal failure and DFU mortality, highlighting again the importance of addressing all risk factors as soon as people present with a foot ulcer
A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcers
This research proposes a mobile and cloud-based framework for the automatic detection of diabetic foot ulcers and conducts an investigation of its performance. The system uses a cross-platform mobile framework which enables the deployment of mobile apps to multiple platforms using a single TypeScript code base. A deep convolutional neural network was deployed to a cloud-based platform where the mobile app could send photographs of patient's feet for inference to detect the presence of diabetic foot ulcers. The functionality and usability of the system were tested in two clinical settings: Salford Royal NHS Foundation Trust and Lancashire Teaching Hospitals NHS Foundation Trust. The benefits of the system, such as the potential use of the app by patients to identify and monitor their condition are discussed