Associations Between Deep Learning-Derived Fat, Muscle, and Bone Measures From Abdominal Computed Tomography Scans and Fall Risk in Persons Aged 20 Years or Older.

ABSTRACT:

Objective

To determine whether abdominal computed tomography (CT) measures of body composition are associated with fall risk in adults aged 20 to 89 years.

Patients and methods

We identified persons who received an abdominal CT scan from 2010 to 2020 using the Rochester Epidemiology Project. We calculated subcutaneous adipose and visceral adipose tissue area, skeletal muscle area and density, and vertebral bone area and density using a validated deep learning algorithm applied to CT abdominal section. Sex-specific tertiles of body composition biomarkers were used for primary analyses. We identified falls using International Classification of Diseases codes and verified via chart review. Associations between body composition tertiles and falls were assessed using Cox proporti

SUBMITTER: St Sauver JL 

PROVIDER: S-EPMC12664019 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature