Development of the ADFICE_IT Models for Predicting Falls and Recurrent Falls in Community-Dwelling Older Adults: Pooled Analyses of European Cohorts With Special Attention to Medication.

ABSTRACT:

Background

Use of fall prevention strategies requires detection of high-risk patients. Our goal was to develop prediction models for falls and recurrent falls in community-dwelling older adults and to improve upon previous models by using a large, pooled sample and by considering a wide range of candidate predictors, including medications.

Methods

Harmonized data from 2 Dutch (LASA, B-PROOF) and 1 German cohort (ActiFE Ulm) of adults aged ≥65 years were used to fit 2 logistic regression models: one for predicting any fall and another for predicting recurrent falls over 1 year. Model generalizability was assessed using internal-external cross-validation.

Results

Data of 5 722 participants were included in the analyses, of whom 1 868 (34.7%) endured at least 1 fall and

SUBMITTER: van de Loo B 

PROVIDER: S-EPMC9255686 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature