Dose-response relationship between acupuncture time parameters and the effects on chronic non-specific low back pain: a systematic review and Bayesian model-based network meta-analysis protocol

Author:

Luo QinORCID,Yang Chunyan,Huang Liuyang,Guixing XuORCID,Hao Tian,Sun MingshengORCID,Liang Fan-rongORCID

Abstract

IntroductionLow back pain (LBP) is a major global public health problem and the majority (nearly 90%) of patients with LBP suffer from non-specific LBP (NSLBP). Acupuncture has been widely used for relieving pain and is recommended as a first-line treatment in LBP guidelines. However, the guidelines do not recommend a specific acupuncture temporal dosage. A Bayesian model-based network meta-analysis (MBNMA) will be conducted to optimise the dosages of time parameters (session, frequency and duration).Methods and analysisThe following databases will be searched from their inception until 1 July 2023: MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials (CENTRAL), EMBASE, Web of Science, Cumulative Index to Nursing & Allied Health Literature (CINAHL), alternative health research database (Alt HealthWatch), China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database for Chinese Technical Periodicals, ClinicalTrials.gov, the WHO’s International Clinical Trial and Chinese Clinical Registry. RCTs assessing the effects of acupuncture on chronic NSLBP will be selected. The primary outcome measure will be the improvement in pain intensity at different acupuncture time points. The MBNMA will be performed using R V.4.2.1 with related R packages. Risk of Bias V.2.0 and Confidence in Network Meta-Analysis will be used to assess the evidence quality.Ethics and disseminationEthical approval is not required for literature-based studies. The results will be published in peer-reviewed journals or conferences.PROSPERO registration numberCRD42022336056.

Funder

Innovation Team and Talents Cultivation Program of the National Administration of Traditional Chinese Medicine

Publisher

BMJ

Subject

General Medicine

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