Traditional Chinese medicine interventions for post-stroke emotional disorders: a protocol for network meta-analysis of randomized controlled trials.

Abstract

<h4>Background</h4>Post-stroke emotional disorders (PSED), primarily encompassing depression, anxiety, and their comorbid conditions, are common and serious complications of stroke. PSED has a high prevalence, significantly reduces patients' quality of life, impedes neurofunctional recovery, and increases the risk of stroke recurrence and mortality. While modern medical treatments are effective, they are generally limited by slow onset, suboptimal response rates, and side effects, and often target a single pathological mechanism, making them inadequate to address the complex interplay of multiple mechanisms characteristic of PSED. Traditional Chinese Medicine (TCM) demonstrates potential advantages through multi-target regulation and relatively good safety. However, the relative efficacy ranking of its numerous therapeutic approaches still lacks robust evidence-based support.<h4>Methods</h4>This study plans to conduct a network meta-analysis (NMA), systematically searching multiple Chinese and English databases and grey literature since the 21st century, including PubMed, Embase, Cochrane CENTRAL, Web of Science, CNKI, CBM, VIP, Wanfang, and ClinicalTrials. Randomized controlled trials (RCTs) comparing different TCM therapies with conventional Western medicine or placebo control for adult PSED will be included. The primary outcome measures include the total clinical effective rate and changes in standardized scale scores. Study screening, data extraction, and risk of bias assessment will be independently completed by two researchers, and any discrepancies will be resolved through discussion or third-party arbitration. A random-effects NMA model based on the Bayesian statistical framework will be constructed to quantify the efficacy differences among different TCM interventions. Additionally, subgroup analyses will be conducted based on PSED types and TCM syndrome patterns to further explore the heterogeneity of efficacy. This study will also comprehensively evaluate the transitivity assumption, heterogeneity, and inconsistency, and use the GRADE framework to grade the quality of evidence. The study protocol strictly follows the PRISMA-P and NMA guidelines and has been registered on the PROSPERO platform.<h4>Results</h4>This NMA will synthesize direct and indirect evidence to quantify effect sizes and rank probabilities of diverse TCM interventions for PSED. Key outputs will include:1. Pairwise comparisons among TCM interventions and between each TCM intervention versus control groups; 2. The ranking of the efficacy of each TCM intervention measure in improving the symptoms of PSED; 3. Subgroup analyses of treatment effects stratified by PSED subtypes and TCM syndrome patterns; 4. Evidence certainty ratings for all effect estimates using the GRADE framework.<h4>Conclusion</h4>This study expects to rigorously conduct a network meta-analysis that will, for the first time within the TCM syndrome differentiation and treatment framework, systematically compare the relative efficacy of multiple TCM therapies for PSED, quantifying their effect sizes and optimal ranking probabilities. The results will provide clinicians with evidence-based hierarchical selection criteria for "acupuncture-Chinese herbal medicine-integrated therapy", addressing the current evidence gap in TCM-based decision-making for PSED. This protocol emphasizes the critical importance of subgroup analyses by PSED subtypes and TCM syndrome patterns, aiming to establish the foundation for more precise and individualized integrated Chinese-Western treatment regimens. Public preregistration enhances research transparency and result credibility, promotes the production of high-quality TCM evidence and its international recognition, ultimately serving to optimize clinical management and improve prognosis in PSED patients.<h4>Systematic review registration</h4>https://www.crd.york.ac.uk/prospero/, identifier CRD420251069356.