Acupoint Catgut Embedding for Insomnia: A Meta-Analysis of Randomized Controlled Trials

Wanrong Li, Zhen Li, Huixing Zhang, Yue Wang, Hui Chen, Lize Xiong, Wanrong Li, Zhen Li, Huixing Zhang, Yue Wang, Hui Chen, Lize Xiong

Abstract

Objectives: A Meta-analysis was carried out to evaluate the efficacy and safety of acupoint catgut embedding (ACE), a procedure of embedding sutures made of absorbable materials into the skin tissue of acupoints, on insomnia.

Methods: Relevant clinical randomized controlled trials (RCTs) were comprehensively searched from eleven electronic databases (up to 1 March 2020). Two authors independently screened literature, extracted data, and assessed the risk of bias of included studies. Stata 12 and RevMan 5.3.0 software were used for meta-analysis. PyCharm 2019 and Gephi software (version 0.9.2) were used for complex network analysis.

Results: Thirty-four RCTs involving 2,655 patients were included. The meta-analysis suggested that ACE induced a better clinical efficacy compared with that in the estazolam tablets (EZ) group (RR = 1.22, 95% CI: 1.13, 1.31) or in the acupuncture (ACU) group (RR = 1.21, 95% CI: 1.14, 1.28) and could significantly reduce the score of Pittsburgh Sleep Quality Index (P < 0.05). ACE resulted in better long-term efficacy compared to that in the EZ group (RR = 1.87, 95% CI: 1.58, 2.22) and ACU group (RR = 1.30, 95% CI: 1.14, 1.48). ACE could significantly reduce the incidence of adverse events (RR = 0.30, 95% CI: 0.15, 0.60) compared with that in the EZ group. Complex network analysis indicated that acupoints of BL23, SP6, PC6, BL15, BL20, BL18, and HT7 were the core acupoints selected in ACE for insomnia.

Conclusion: The clinical efficacy of ACE for insomnia is better than that of other interventions (EZ and ACU) in both short-term and long-term observations. Considering the efficacy and reduced visits to the clinic by ACE, the present study provides a practical and convenient complementary and alternative therapy for insomnia. This trial is registered with PROSPERO CRD 42020169866.

Conflict of interest statement

The authors declare that they have no conflicts of interest.

Copyright © 2020 Wanrong Li et al.

Figures

Figure 1
Figure 1
Flow chart of the study searching and selecting process.
Figure 2
Figure 2
Quality assessment of included studies.
Figure 3
Figure 3
The forest plot of quantitative analysis results. ACE group versus EZ group: (a) clinical therapeutic effect; (b) PSQI score; (c) the incidence of adverse events. ACE group versus ACU group: (d) clinical therapeutic effect; (e) PSQI score; (f) the incidence of adverse events.
Figure 4
Figure 4
Meta-analysis results of publication bias. (a) Funnel plot with pseudo 95% confidence limits (Cls) of clinical efficacy (ACE versus EZ). The horizontal line represents the summary effect estimates, and the dotted lines are pseudo 95% Cls. (b) Filled funnel plot of RR from studies that compared the clinical efficacy between ACE and EZ. The circles alone are real studies and the circles enclosed in boxes are “filled” studies. The horizontal line represents the summary effect estimates, and the diagonal lines represent pseudo 95% Cls. Based on the random-effect model, the number of missing studies was estimated using the Linear method after 6 iterations (diff = 0), and the result was 4. (c) Funnel plot with pseudo 95% Cls of clinical efficacy (ACE versus ACU). (d) Filled funnel plot of RR from studies that compared the clinical efficacy between ACE and ACU. Based on the fixed-effect model, the number of missing studies was estimated using the Linear method after 4 iterations (diff = 0), and the result was 6. (e) Funnel plot with pseudo 95% Cls of the reduction of the PSQI score (ACE versus EZ). (f) Funnel plot with pseudo 95% Cls of the reduction of the PSQI score (ACE versus ACU).
Figure 5
Figure 5
The core acupoints of ACE for insomnia analyzed by a complex network. This network contains 29 nodes and 137 edges. The higher the degree centrality value of the acupoint is, the larger the node is, the larger the font is, the redder the color of the node is, and the more important it is in the network. The thicker the edge is, the more frequently the acupoints are used together.

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