Development and validation of a machine learning-based prediction model for frailty in older adults with diabetes: a study protocol for a retrospective cohort study.

ABSTRACT:

Introduction

Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is crucial for implementing timely interventions. However, there is a lack of specific prediction models for frailty in older adults with diabetes. This study aims to develop and validate a prediction model for frailty in this high-risk group.

Methods and analysis

This study uses data from the national follow-up of the China Health and Retirement Longitudinal Study (CHARLS), which range from 2011 to 2020. The study population includes older adults with diabetes aged 60 and above. Frailty is assessed using Fried's frailty phenotype. Potential predictors will be identified through a syste

SUBMITTER: Luo A 

PROVIDER: S-EPMC12410600 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature