Dynamic nomogram prediction model for diabetic retinopathy in patients with type 2 diabetes mellitus.

ABSTRACT:

Background

To develop a dynamic prediction model for diabetic retinopathy (DR) using systemic risk factors.

Methods

This retrospective study included type 2 diabetes mellitus (T2DM) patients discharged from the Second Affiliated Hospital of Kunming Medical University between May 2020 and February 2022. The early patients (80%) were used for the training set and the late ones (20%) for the validation set.

Results

Finally, 1257 patients (1049 [80%] in the training set and 208 [20%] in the validation set) were included; 360 (28.6%) of them had DR. The areas under the curves (AUCs) for the multivariate regression (MR), least absolute shrinkage and selection operator regression (LASSO), and backward elimination stepwise regression (BESR) models were 0.719, 0.727, and 0.728

SUBMITTER: Zhang C 

PROVIDER: S-EPMC10142167 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature