Comparative efficacy and safety of different surgical approaches for the treatment of anterior cruciate ligament injury: a Bayesian network meta-analysis protocol

Author:

He YuchenORCID,Fan YishuORCID,Zhai Longxiang,Zhu WeihongORCID

Abstract

IntroductionAnterior cruciate ligament (ACL) rupture can be treated surgically or non-surgically, with several surgical interventions available at present. However, the comparatively effective surgical intervention with relatively fewer side effects remains unknown. This study aims to fill in this gap by conducting a Bayesian network meta-analysis (NMA) and provide a theoretical basis for the clinical application.Method and analysisWe will perform a Bayesian NMA and will include randomised controlled trials (RCTs) published in English or Chinese that compare surgical intervention (ie, standard ACL reconstruction, ACL remnant-preserving reconstruction and ACL repair with suture augmentation to conservative therapy or studies that compare one surgical intervention to another for the symptom relief and function recovery of patients with ACL rupture. Primary outcome will be the proportion of patients with symptomatic and functional improvement measured by the Knee Injury and Osteoarthritis Outcome Score before and 6 months after treatment, with scores ranging from 0 (worst) to 100 (best). Secondary outcomes will be knee-specific quality of life (ACL QoL), return to activity and level of sport participation (Tegner or modified Tegner score), health-related QoL (EuroQol Group 5-Dimension 5-Level, EQ-5D-5L), resource use, intervention-related complications and patient satisfaction. We have developed search strategies for PubMed, Embase, the Cochrane Library and Web of Science, retrieving RCTs that meet the inclusion criteria from database inception to 1 December 2023. The methodological quality of the included RCTs will be assessed based on the Cochrane risk of bias table. The relative ranking probability of the best intervention will be estimated using the surface under the cumulative ranking curve. The Bayesian NMA will be conducted by using WinBUGS V.1.4.3. The Grading of Recommendations Assessment, Development and Evaluation approach will be applied to determine our confidence in an overall treatment ranking from the NMA.Ethics and disseminationEthical approval for this study is not required because no private or confidential patient data will be used in this study. Findings of this study would be disseminated through the publication in a peer-reviewed medical journal.PROSPERO registration numberCRD42023437115.

Funder

Hunan Provincial Health Commission Project

the Natural Science Foundations of Hunan Province

Publisher

BMJ

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