A network meta-analysis on the improvement of cognition in patients with vascular dementia by different acupuncture therapies

INTRODUCTION: The second most prevalent cause of dementia is vascular dementia (VaD). Furthermore, acupuncture is a relatively safe and effective traditional therapy for individuals with VaD. We performed a network meta-analysis to assess the effectiveness and safety of various acupuncture therapies for VaD based on existing research. METHODS: We searched six electronic databases to screen for randomized controlled trials (RCTs) comparing different acupuncture treatments in VaD patients. The Cochrne tool (Review Manager 5.3) was used to evaluate the risk of bias of the included RCTs. Based on the Grading of Recommendations Assessment, Development and Evaluation framework, we assessed the confidence in the evidence using the Confidence In the results from Network Meta-Analysis approach. We used the frequency approach to perform the network meta-analysis. Data were analyzed using R 4.1.1. RESULTS: In total, we included 46 eligible studies. The results of the network analysis showed that the combined interventions of moxibustion (MB) with body acupuncture (BA) (MB + BA) and electroacupuncture (EA) with scalp acupuncture (SA) with BA (EA + SA + BA) were more effective in improving cognitive functions and activities of daily living compared with SA or BA alone. However, in the subgroup analysis, EA + SA + BA showed better efficacy in short- and mid-term acupuncture compared with other acupuncture therapies. CONCLUSION: Combined acupuncture therapy may be a safe and effective intervention for individuals with VaD, and MB + BA and EA + SA + BA appear to be the most effective interventions. However, because the analysis of this study was based on low-to-moderate evidence, there remains no strong supporting evidence. Thus, high-quality, large-scale, and long-term studies should be conducted in the future to assess the effectiveness and safety of acupuncture in VaD. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/, identifier: CRD42022354573.