Citation

Jeffery AD, Dietrich MS, Maxwell CA. Arch. Gerontol. Geriatr. 2018; 75: 191-196.

Affiliation

Vanderbilt University School of Nursing, Nashville, TN, United States. Electronic address: cathy.maxwell@vanderbilt.edu.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.archger.2018.01.003

PMID

29331842

Abstract

PURPOSE: The growing incidence of elderly patients injured from falls, combined with a growing understanding of the contribution of cognition and frailty to mortality, prompted this work. Our objective was to develop a clinical risk prediction model for prognosticating disability and mortality among injured older adults 1 year after hospitalization.

METHODS: Secondary analysis of prospective longitudinal data from an urban Level 1 trauma center. A proportional odds regression model was used to model mortality and functional status as ordinal outcomes. Death was treated as the lowest functional status, and 3 ordered groups of the Barthel Index were treated as higher functional status. 188 patients aged 65 and older who were admitted through the emergency department from 2013 to 2014 with a primary injury diagnosis comprised the prospective cohort. Follow-up assessments were performed at 30-days, 90-days, 6-months, and 1-year. Predictors in the model included: baseline physical function, baseline cognition, two physical frailty measures, age, injury severity, a comorbidity index, gender, living location, mechanism of injury, and hospital admitting service.

RESULTS: The full model yielded an R2 of 0.45, and Life Space Assessment, Vulnerable Elders Survey, and Injury Severity were the most influential predictors. Approximated models (to encourage clinical use) yielded an R2 of 0.86. Calibration assessment (i.e., accuracy) demonstrated a mean squared error <0.003 at all 3 intercepts.

CONCLUSIONS: A moderate statistical signal was discovered that contributed to a highly accurate clinical prediction model. Approximated models and nomograms could be used by clinicians, patients, and families in shared decision making during hospitalization.

Published by Elsevier B.V.

Language: en

Keywords

Elderly; Frailty; Injury; Prediction model