The prediction model of fall risk for the elderly based on gait analysis.

ABSTRACT:

Introduction

Early screening and identification are crucial for fall prevention, and developing a new method to predict fall risk in the elderly can address the current lack of objectivity in assessment tools.

Methods

A total of 132 elderly individuals over 80 years old residing in some nursing homes in Shanghai were selected using a convenient sampling method. Fall history information was collected, and gait data during a 10-meter walk were recorded. Logistic regression was employed to establish the prediction model, and a nomogram was used to assess the importance of the indicators. The Bootstrap method was utilized for internal validation of the model, while the verification set was used for external validation. The predictive performance of the model was evaluated using

SUBMITTER: Jia S 

PROVIDER: S-EPMC11323353 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature