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Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System
OBJECTIVE: Insomnia is a common and frequently occurring disease affecting the health of the population, which can seriously affect the work and life of patients. Drug treatment of insomnia has a rapid onset of action but has a large adverse reaction incidence rate. Traditional external treatment of...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578844/ https://www.ncbi.nlm.nih.gov/pubmed/36268156 http://dx.doi.org/10.1155/2022/1081713 |
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author | Zhuang, Jingqing Wu, Jian Fan, Liang Liang, Chongnan |
author_facet | Zhuang, Jingqing Wu, Jian Fan, Liang Liang, Chongnan |
author_sort | Zhuang, Jingqing |
collection | PubMed |
description | OBJECTIVE: Insomnia is a common and frequently occurring disease affecting the health of the population, which can seriously affect the work and life of patients. Drug treatment of insomnia has a rapid onset of action but has a large adverse reaction incidence rate. Traditional external treatment of traditional Chinese medicine (TCM) belongs to a type of non-drug therapy, the treatment of insomnia has a long history, but the methods of non-drug treatment of TCM are diverse, and the efficacy is also different. This study investigated the efficacy of TCM non-drug therapy in the treatment of insomnia by means of literature search and meta-analysis. METHODS: We searched Embase, Pubmed, OVid, WOS, CNKI, and CBM for randomized controlled trials (RCTs) on the use of TCM as a non-drug treatment for primary insomnia. After doing a literature search according to the inclusion and exclusion criteria, we used Cochrane rob v2.0 to assess the potential for bias in the studies that were included, and we did a combined analysis and assessment of the effectiveness of the therapy. RESULTS: 16 articles were included in this study for quantitative analysis, and a total of 1285 patients participated in the study, including 643 patients in the intervention group and 642 patients in the control group. Meta-analysis showed that non-drug therapy of TCM could improve the treatment response rate of insomnia patients [OR = 6.88, 95%CI (4.40,10.74), Z = 8.48, P < 0.0001], reduce post-treatment PSQI total score [MD = −3.42, 95%CI (−4.62, −2.22), Z = −5.60, P < 0.0001], and improved patient anxiety [SMD = −1.25, 95%CI (−2.13, −0.37), Z = −2.78, P=0.01] and degree of depression [SMD = −1.53, 95%CI (−2.84, −0.21), Z = −2.28, P=0.02]. The heterogeneity survey showed that treatment time was one of the sources of heterogeneity. Meta-regression analysis revealed that publication year, patient age, sample size, and intervention characteristics were not specific factors affecting the combined results. Discussion. TCM non-drug therapy (acupuncture, moxibustion, massage, and auricular point pressing beans) can significantly improve the PSQI score of patients after treatment and improve the degree of anxiety and depression of patients, with significant effect, which is worthy of clinical promotion. |
format | Online Article Text |
id | pubmed-9578844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-95788442022-10-19 Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System Zhuang, Jingqing Wu, Jian Fan, Liang Liang, Chongnan Comput Intell Neurosci Review Article OBJECTIVE: Insomnia is a common and frequently occurring disease affecting the health of the population, which can seriously affect the work and life of patients. Drug treatment of insomnia has a rapid onset of action but has a large adverse reaction incidence rate. Traditional external treatment of traditional Chinese medicine (TCM) belongs to a type of non-drug therapy, the treatment of insomnia has a long history, but the methods of non-drug treatment of TCM are diverse, and the efficacy is also different. This study investigated the efficacy of TCM non-drug therapy in the treatment of insomnia by means of literature search and meta-analysis. METHODS: We searched Embase, Pubmed, OVid, WOS, CNKI, and CBM for randomized controlled trials (RCTs) on the use of TCM as a non-drug treatment for primary insomnia. After doing a literature search according to the inclusion and exclusion criteria, we used Cochrane rob v2.0 to assess the potential for bias in the studies that were included, and we did a combined analysis and assessment of the effectiveness of the therapy. RESULTS: 16 articles were included in this study for quantitative analysis, and a total of 1285 patients participated in the study, including 643 patients in the intervention group and 642 patients in the control group. Meta-analysis showed that non-drug therapy of TCM could improve the treatment response rate of insomnia patients [OR = 6.88, 95%CI (4.40,10.74), Z = 8.48, P < 0.0001], reduce post-treatment PSQI total score [MD = −3.42, 95%CI (−4.62, −2.22), Z = −5.60, P < 0.0001], and improved patient anxiety [SMD = −1.25, 95%CI (−2.13, −0.37), Z = −2.78, P=0.01] and degree of depression [SMD = −1.53, 95%CI (−2.84, −0.21), Z = −2.28, P=0.02]. The heterogeneity survey showed that treatment time was one of the sources of heterogeneity. Meta-regression analysis revealed that publication year, patient age, sample size, and intervention characteristics were not specific factors affecting the combined results. Discussion. TCM non-drug therapy (acupuncture, moxibustion, massage, and auricular point pressing beans) can significantly improve the PSQI score of patients after treatment and improve the degree of anxiety and depression of patients, with significant effect, which is worthy of clinical promotion. Hindawi 2022-10-11 /pmc/articles/PMC9578844/ /pubmed/36268156 http://dx.doi.org/10.1155/2022/1081713 Text en Copyright © 2022 Jingqing Zhuang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Zhuang, Jingqing Wu, Jian Fan, Liang Liang, Chongnan Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System |
title | Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System |
title_full | Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System |
title_fullStr | Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System |
title_full_unstemmed | Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System |
title_short | Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System |
title_sort | observation on the clinical efficacy of traditional chinese medicine non-drug therapy in the treatment of insomnia: a systematic review and meta-analysis based on computer artificial intelligence system |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578844/ https://www.ncbi.nlm.nih.gov/pubmed/36268156 http://dx.doi.org/10.1155/2022/1081713 |
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