Published on 01 January 2024

Effects of cardiorespiratory physiotherapy on lung function in stroke: a network meta-analysis

View Dataset
Kim, So-Hyun;Cho, Sung-Hyoun

Description

The efficacy of various physiotherapy interventions for improving lung function has not been compared. To evaluate cardiorespiratory physiotherapy interventions on lung function in patients with stroke, prioritize intervention types, and establish hierarchy. Twelve randomized controlled trials published during 2000–2022 in PubMed, EMBASE, Cochrane Library, and Web of Science were selected. Interventions included aerobic training (AT), combined inspiratory and expiratory training (CIET), inspiratory training (IT), combined aerobic and breadth training (CABT), and conventional training (CT). Outcome variables were forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1/FVC. CIET and IT were more effective than CT for FEV1 and FVC. CIET and IT showed larger effect sizes compared to AT for FEV1. The intervention rankings were as follows: IT (86.62%), CIET (63.31%), CABT (50.79%), AT (28.72%), and CT (20.55%) for FEV1; IT (93.89%), CIET (75.06%), CT (42.38%), CABT (37.73%), and AT (0.94%) for FVC; and IT (78.30%), CT (54.14%), CABT (42.62%), CIET (41.65%), and AT (33.29%) for FEV1/FVC. CIET and IT were more effective than CT for FVC in patients with stroke aged ≥60 years. Besides FEV1/FVC, IT and CIET inhalation exercises improved lung function more effectively than other therapies, with IT or CIET being more effective than AT or CT. CIET and IT were more effective than CT for FVC in patients with stroke aged ≥60 years than in those <60 years. These findings highlight the significance of breathing training for patients with stroke and support clinical decision-making.

Citations (1)

Mentions (0)

Metrics

Dataset Index

0.7

FAIR Score

13%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Taylor & Francis

Assigned Domain

Subfield

Complementary and alternative medicine

Field

Medicine

Domain

Health Sciences

Confidence Score

38%

Source

Scholar Data Model

Keywords

MedicinePhysiologyFOS: Biological sciencesBiological Sciences not elsewhere classifiedScience Policy

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00