• Haikuo Song, Xuan Zhang, and Xiangfa Zou.
• Department of Orthopedics and Traumatology of Integrated Traditional Chinese and Western Medicine, Tianjin Hospital, Tianjin, China.
• Medicine (Baltimore). 2021 Nov 5; 100 (44): e27648e27648.

BackgroundCurrent studies in patients with congenital muscular torticollis (CMT) have predominantly focused on the role of tuina or paraffin therapy alone. This systematic review with Bayesian network meta-analysis will be performed to sum up the existing evidence on the effects and safety of tuina plus paraffin therapy for CMT in infants and children.MethodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyzes reporting guidelines will be followed to conduct this study. The electronic databases of PubMed, Cochrane Library, PsycINFO, EMBASE, the Chinese Scientific Journal Database, China National Knowledge Infrastructure, WanFang Data, Taiwan Electronic Periodical Services, and Web of Science will be searched from the inception to November 2021 using the following key terms: "Tuina," "traditional Chinese medicine massage," "paraffin," and "congenital muscular torticollis," for all relevant studies. We impose no language restrictions. We include reports on randomized controlled trials (RCTs) and quasi-RCTs of Tuina combline with paraffin therapy for the treatment of CMT in children and adolescents. We include studies that assessed effective rate, symmetry, improvements of range of motion, muscle length, and sternocleidomastoid tumor thickness, quality of life, and adverse events. The Cochrane Bias Risk Tool, which considers sequence generation, allocation concealment, and blinding and other aspects of bias, will be used to assess the risk of bias in studies.ResultsA Bayesian network meta-analysis is an appropriate statistical method to compare all treatment options by statistically simulating the estimated results of a comprehensive trial, and to compare treatments by common and associated comparators. In addition, Bayesian network meta-analysis can produce ranking probabilities of treatments, which may contribute to clinicians' clinical decision-making.Registration Number10.17605/OSF.IO/K5EGN.Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.

28 keywords...

hide…