Back to Search Start Over

Validation of the ADFICE_IT Models for Predicting Falls and Recurrent Falls in Geriatric Outpatients.

Authors :
van de Loo B
Heymans MW
Medlock S
Boyé NDA
van der Cammen TJM
Hartholt KA
Emmelot-Vonk MH
Mattace-Raso FUS
Abu-Hanna A
van der Velde N
van Schoor NM
Source :
Journal of the American Medical Directors Association [J Am Med Dir Assoc] 2023 Dec; Vol. 24 (12), pp. 1996-2001. Date of Electronic Publication: 2023 May 30.
Publication Year :
2023

Abstract

Objectives: Before being used in clinical practice, a prediction model should be tested in patients whose data were not used in model development. Previously, we developed the ADFICE_IT models for predicting any fall and recurrent falls, referred as Any_fall and Recur_fall. In this study, we externally validated the models and compared their clinical value to a practical screening strategy where patients are screened for falls history alone.<br />Design: Retrospective, combined analysis of 2 prospective cohorts.<br />Setting and Participants: Data were included of 1125 patients (aged ≥65 years) who visited the geriatrics department or the emergency department.<br />Methods: We evaluated the models' discrimination using the C-statistic. Models were updated using logistic regression if calibration intercept or slope values deviated significantly from their ideal values. Decision curve analysis was applied to compare the models' clinical value (ie, net benefit) against that of falls history for different decision thresholds.<br />Results: During the 1-year follow-up, 428 participants (42.7%) endured 1 or more falls, and 224 participants (23.1%) endured a recurrent fall (≥2 falls). C-statistic values were 0.66 (95% CI 0.63-0.69) and 0.69 (95% CI 0.65-0.72) for the Any_fall and Recur_fall models, respectively. Any_fall overestimated the fall risk and we therefore updated only its intercept whereas Recur_fall showed good calibration and required no update. Compared with falls history, Any_fall and Recur_fall showed greater net benefit for decision thresholds of 35% to 60% and 15% to 45%, respectively.<br />Conclusions and Implications: The models performed similarly in this data set of geriatric outpatients as in the development sample. This suggests that fall-risk assessment tools that were developed in community-dwelling older adults may perform well in geriatric outpatients. We found that in geriatric outpatients the models have greater clinical value across a wide range of decision thresholds compared with screening for falls history alone.<br /> (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1538-9375
Volume :
24
Issue :
12
Database :
MEDLINE
Journal :
Journal of the American Medical Directors Association
Publication Type :
Academic Journal
Accession number :
37268014
Full Text :
https://doi.org/10.1016/j.jamda.2023.04.021