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Development and validation of a prediction model for self-reported mobility decline in community-dwelling older adults.

Sanchez-Santos, MT; Williamson, E; Nicolson, PJA; Bruce, J; Collins, GS; Mallen, C; Griffiths, F; Garret, A; Morris, A; Slark, M; Lamb, SE; OPAL study team, .

Authors

MT Sanchez-Santos

E Williamson

PJA Nicolson

J Bruce

GS Collins

F Griffiths

A Garret

A Morris

M Slark

SE Lamb

. OPAL study team



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.

Acceptance Date Sep 12, 2022
Publication Date Sep 12, 2022
Journal Journal of Clinical Epidemiology
Print ISSN 0895-4356
Publisher Elsevier
Pages 70-79
DOI https://doi.org/10.1016/j.jclinepi.2022.09.002
Keywords Prognostic; Impaired mobility; General population; Aging; Prediction model; Elderly; Model performance
Publisher URL https://www.jclinepi.com/article/S0895-4356(22)00223-2/fulltext