An Improved Clinical and Genetics-Based Prediction Model for Diabetic Foot Ulcer Healing.

ABSTRACT: Objective: The goal of this investigation was to use comprehensive prediction modeling tools and available genetic information to try to improve upon the performance of simple clinical models in predicting whether a diabetic foot ulcer (DFU) will heal. Approach: We utilized a cohort study (n = 206) that included clinical factors, measurements of circulating endothelial precursor cells (CEPCs), and fine sequencing of the NOS1AP gene. We derived and selected relevant predictive features from this patient-level information using statistical and machine learning techniques. We then developed prognostic models using machine learning approaches and assessed predictive performance. The presentation is consistent with TRIPOD requirements. Results: Models using ba

SUBMITTER: Hettinger G 

PROVIDER: S-EPMC11339549 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature