Estimating the Risk of Lower Extremity Complications in Adults Newly Diagnosed With Diabetic Polyneuropathy: Retrospective Cohort Study.

ABSTRACT:

Background

Diabetes-related lower extremity complications, such as foot ulceration and amputation, are on the rise, currently affecting nearly 131 million people worldwide. Methods for early detection of individuals at high risk remain elusive. While data-driven diabetic polyneuropathy algorithms exist, high-performing, clinically useful tools to assess risk are needed to improve clinical care.

Objective

This study aimed to develop an electronic medical record-based machine learning algorithm that would predict lower extremity complications.

Methods

We conducted a retrospective longitudinal cohort study to predict the risk of lower extremity complications within 24 months of an initial diagnosis of diabetic polyneuropathy. From an initial cohort of 468,162 individuals

SUBMITTER: Adams AS 

PROVIDER: S-EPMC12140504 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature