detalle del documento
IDENTIFICACIÓN

oai:pubmedcentral.nih.gov:1057...

Tema
Review
Autor
Zhu, Hao Deng, Xinyuan Luan, Guorui Zhang, Yu Wu, Yichen
Langue
en
Editor

BioMed Central

Categoría

BMC Neuroscience

Año

2023

fecha de cotización

11/12/2023

Palabras clave
meta-analysis network training post-stroke dysphagia non-pharmacological interventions
Métrico

Resumen

Increasingly, non-pharmacological interventions are being identified and applied to post-stroke dysphagia.

Nevertheless, there is insufficient evidence to assess which type of interventions are more effective.

In this study, the randomized controlled trials of non-pharmacological interventions on post-stroke dysphagia were retrieved from the relevant databases.

Including 96 studies and 12 non-drug treatments.

Then, and the network meta-analysis is carried out by statistical software.

The results show: In the aspects of videofluoroscopic swallowing study (VFSS), Standardized Swallowing Assessment (SSA), swallowing-quality of life (SWAL-QOL), Water swallow test (WST); Acupuncture + electrotherapy + rehabilitation training, acupuncture + rehabilitation training + massage, electrotherapy + rehabilitation training, acupuncture + electrotherapy + rehabilitation training, electrotherapy, acupuncture + rehabilitation training + acupoints sticking application have significant effects in post-stroke dysphagia.

Compared with other interventions, they have more advantages in improving the above indicators.

A substantial number of high-quality randomized clinical trials are still necessary in the prospective to validate the therapeutic effectiveness of non-pharmacological interventions in post-stroke dysphagia and the results of this Bayesian network meta-analysis.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12868-023-00825-0.

Zhu, Hao,Deng, Xinyuan,Luan, Guorui,Zhang, Yu,Wu, Yichen, 2023, Comparison of efficacy of non-pharmacological intervention for post-stroke dysphagia: a systematic review and Bayesian network meta-analysis, BioMed Central

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