Predictive model development for possible sarcopenia in community-dwelling older adults: a cross-sectional machine learning approach using the Korean frailty and aging cohort study.

ABSTRACT:

Background

Sarcopenia, an age-related decline in muscle mass and physical function, is a major risk factor for frailty, a condition associated with negative health outcomes and increased disease burden in older adults. Providing simple, accurate community-based screening is essential for early prevention and improving the health and quality of life of older adults. Employing screening criteria for possible sarcopenia can broadly identify individuals at risk for sarcopenia and enhance early diagnosis and preventive measures. However, there is a lack of possible sarcopenia prediction models. This study developed and evaluated a model for predicting possible sarcopenia among community-dwelling older adults and identified key predictors.

Methods

A supervised machine learning app

SUBMITTER: Kwon S 

PROVIDER: S-EPMC12667061 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature