Predicting admission for fall-related injuries in older adults using artificial intelligence: A proof-of-concept study.

ABSTRACT:

Aim

Pre-injury frailty has been investigated as a tool to predict outcomes of older trauma patients. Using artificial intelligence principles of machine learning, we aimed to identify a "signature" (combination of clinical variables) that could predict which older adults are at risk of fall-related hospital admission. We hypothesized that frailty, measured using the 5-item modified Frailty Index, could be utilized in combination with other factors as a predictor of admission for fall-related injuries.

Methods

The National Readmission Database was mined to identify factors associated with admission of older adults for fall-related injuries. Older adults admitted for trauma-related injuries from 2010 to 2014 were included. Age, sex, number of chronic conditions and past fall-r

SUBMITTER: Le N 

PROVIDER: S-EPMC11788240 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature