Sanchez-Santos, MT, Williamson, E, Nicolson, PJA, Bruce, J, Collins, GS, Mallen, CD, Griffiths, F, Garret, A, Morris, A, Slark, M, Lamb, SE and OPAL study team, . (2022) Development and validation of a prediction model for self-reported mobility decline in community-dwelling older adults. Journal of Clinical Epidemiology.

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Abstract

OBJECTIVE: To develop and validate two models to predict 2-year risk of self-reported mobility decline among community-dwelling older adults. STUDY DESIGN AND SETTING: We used data from a prospective cohort study of people aged 65 years and over in England. Mobility status was assessed using the EQ-5D-5L mobility question. The models were based on the outcome: (Model 1) any mobility decline at two years; (Model 2) new-onset of persistent mobility problems over two years. LASSO logistic regression was used to select predictors. Model performance was assessed using c-statistics, calibration plot, Brier scores and decision-curve analyses. Models were internally validated using bootstrapping. RESULTS: Over 18% of participants who could walk reported mobility decline at year two (Model 1), and 7.1% with no mobility problems at baseline, reported new-onset of mobility problems after two years (Model 2). Thirteen and six out of thirty-one variables were selected as predictors in Model 1 and 2, respectively. Models 1 and 2 had a c-statistic of 0.740 and 0.765 (optimism<0.013), and Brier score=0.136 and 0.069, respectively. CONCLUSIONS: Two prediction models for mobility decline were developed and internally validated. They are based on self-reported variables and could serve as simple assessments in primary care after external validation.

Item Type: Article
Additional Information: http://creativecommons.org/licenses/by/4.0/
Uncontrolled Keywords: Prognostic Impaired mobility General population Aging Prediction model Elderly Model performance
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine and Health Sciences > School of Medicine
Related URLs:
Depositing User: Symplectic
Date Deposited: 31 Oct 2022 17:08
Last Modified: 31 Oct 2022 17:08
URI: https://eprints.keele.ac.uk/id/eprint/11638

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