Gait speed, muscle strength, and functional status predict 30‐day unplanned hospital readmission of critical care survivors

Author:

de Melo Thiago Araújo1ORCID,Guimarães Fernando Silva2,Silva José Roberto Lapa e3

Affiliation:

1. UFRJ Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil

2. Physical Therapy Department Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil

3. School of Medicine—Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil

Abstract

AbstractBackground and PurposeDespite intense efforts, predicting hospital readmission risks remains an imprecise task. Growing evidence suggests that unmeasured patient‐related factors, such as functional impairment, seem to be strongly associated with acute readmission and have yet to be extensively explored. We hypothesized that gait speed, hand grip strength, and the Functional independence measure (FIM) might be associated with acute rehospitalization rates after an ICU stay.MethodsIn our study, we assessed gait speed using a 10‐m walk test. Muscle strength was determined by a hydraulic handgrip dynamometer and functional status through the FIM. Our primary outcome was the cumulative incidence of the first unplanned early rehospitalization (occurring within 30 days of hospital discharge) for the entire cohort, and a Receiver Operator Characteristic (ROC) analysis was used to determine the accuracy of gait speed, handgrip strength, and FIM domains in predicting hospital readmission.ResultsROC analysis indicated that the gait speed (AUC 0.96 95% CI 0.93 to 0.99), FIM score (AUC 0.96 95% CI 0.94 to 0.99) and handgrip strength (0.85 95% CI 0.76 to 0.94) were considered accurate predictors of unplanned readmission in the population studied. Additionally, we found that each 0.1 m/s lower gait speed was associated with a 10% higher odd of unplanned readmissions.ConclusionHence, our results suggest gait speed, handgrip strength and functional status demonstrated high potential to contribute to the determination of 30‐day unplanned hospital readmission prediction of critical care survivors.

Publisher

Wiley

Subject

Physical Therapy, Sports Therapy and Rehabilitation

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Prediction of Hospital Readmission using Federated Learning;2023 30th International Conference on Systems, Signals and Image Processing (IWSSIP);2023-06-27

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