Respiratory Parameters as Predictors of Balance and Gait Ability in Patients with Stroke at Discharge

Hee-Yong Park, Oh-Yun Kwon (), Chung-Hwi Yi, Hye-Seon Jeon, Woochol Joseph Choi, So-Young Ahn and Ui-Jae Hwang
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Hee-Yong Park: Department of Rehabilitation Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea
Oh-Yun Kwon: Department of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea
Chung-Hwi Yi: Department of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea
Hye-Seon Jeon: Department of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea
Woochol Joseph Choi: Department of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea
So-Young Ahn: Department of Rehabilitation Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea
Ui-Jae Hwang: Department of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, Republic of Korea

IJERPH, 2023, vol. 20, issue 23, 1-11

Abstract: Pulmonary complications are frequent in stroke, contributing to both mortality and morbidity rates. Respiratory parameters in such patients encompass both pulmonary function and respiratory muscle strength. Identifying respiratory function variables that influence the balance and gait ability of patients with stroke is crucial for enhancing their recovery in these aspects. However, no study has assessed predictions for a comprehensive array of balance and gait abilities in such patients. We aimed to examine whether initial respiratory muscle strength and pulmonary function can predict balance and gait ability at discharge from a rehabilitation program. Thirty-one patients with stroke were included in this prospective observational study. Multiple regression models with a forward selection procedure were employed to identify respiratory parameters (including peak expiratory flow and maximal expiratory pressure) that contributed to the results of balance assessments and gait evaluations at the time of discharge. The peak expiratory flow (PEF) served as a predictor explaining 42.0% of the variance. Similarly, the maximal expiratory pressure (MEP) was a predictor variable explaining 32.0% of the variance. PEF and MEP assessments at the initial stage as predictive factors for both balance and gait ability are important in stroke management.

Keywords: balance; gait; pulmonary function test; respiratory muscle strength; stroke (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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