Predictive model for diabetic retinopathy under limited medical resources: A multicenter diagnostic study.

ABSTRACT:

Background

Comprehensive eye examinations for diabetic retinopathy is poorly implemented in medically underserved areas. There is a critical need for a widely available and economical tool to aid patient selection for priority retinal screening. We investigated the possibility of a predictive model for retinopathy identification using simple parameters.

Methods

Clinical data were retrospectively collected from 4, 159 patients with diabetes admitted to five tertiary hospitals. Independent predictors were identified by univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and a nomogram was developed based on a multivariate logistic regression model. The validity and clinical practicality of this nomogram were assessed using concordance in

SUBMITTER: Yang Y 

PROVIDER: S-EPMC9849672 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature