Machine learning versus binomial logistic regression analysis for fall risk based on SPPB scores in older adult outpatients.

ABSTRACT:

Objective

To compare the performance of the diagnostic model for fall risk based on the short physical performance battery (SPPB) developed using commercial machine learning software (MLS) and binomial logistic regression analysis (BLRA).

Methods

We enrolled 797 out of 850 outpatients who visited the clinic between March 2016 and November 2021. Patients were categorized into the development (n = 642) and validation (n = 155) datasets. Age, sex, number of comorbidities, number of medications, body mass index (BMI), calf circumference (left-right average), handgrip strength (left-right average), total SPPB score, and history of falls were determined. We defined fall risk by an SPPB score of ≤6 in men and ≤9 in women. The main metrics used for evaluating the machi

SUBMITTER: Hasegawa S 

PROVIDER: S-EPMC10722919 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature