Journal of Physical Therapy Science
Online ISSN : 2187-5626
Print ISSN : 0915-5287
ISSN-L : 0915-5287
Original Article
Predictive discriminative accuracy of walking abilities at discharge for community ambulation levels at 6 months post-discharge among inpatients with subacute stroke
Tatsuya IgarashiRen TakedaYuta TaniNaoya TakahashiTakuto OnoYoshiki IshiiShota HayashiShigeru Usuda
ジャーナル オープンアクセス

2023 年 35 巻 3 号 p. 257-264


[Purpose] This study aimed to compare the predictive accuracy of walking ability at discharge among subacute stroke inpatients at 6 months post-discharge in terms of community ambulation level and establish optimal cut-off values. [Participants and Methods] This prospective observational study included 78 patients who completed follow-up assessments. Patients were classified into three groups based on the Modified Functional Walking Category (household/most limited community walkers, least limited community walkers, and unlimited community walkers) obtained by telephone survey at 6 months post-discharge. Predictive accuracy and cut-off values for discriminating among groups were calculated from 6-minute walking distance and comfortable walking speed measured at the time of discharge using receiver operating characteristic curves. [Results] Between household/most limited and least limited community walkers, 6-minute walking distance and comfortable walking speed offered similar predictive accuracy (area under the curve, 0.6–0.7), with cut-off values of 195 m and 0.56 m/s, respectively. Between least limited and unlimited community walkers, the areas under the curve were 0.896 for 6-minute walking distance and 0.844 for comfortable walking speed, with cut-off values of 299 m and 0.94 m/s, respectively. [Conclusion] Walking endurance and walking speed among inpatients with subacute stroke provided superior predictive accuracy for unlimited community walkers at 6 months post-discharge.

© 2023 by the Society of Physical Therapy Science. Published by IPEC Inc.

This article is licensed under a Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International] license.
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