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Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis
BACKGROUND: This Bayesian network meta-analysis investigated the available randomized control trials (RCTs) to point out which acupuncture protocol is the most effective for chronic aspecific low back pain (LBP). Efficacy was measured in terms of pain (Visual Analogic Scale, VAS) and disability (Rol...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208133/ https://www.ncbi.nlm.nih.gov/pubmed/35725480 http://dx.doi.org/10.1186/s13018-022-03212-3 |
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author | Baroncini, Alice Maffulli, Nicola Eschweiler, Jörg Molsberger, Friedrich Klimuch, Alexandra Migliorini, Filippo |
author_facet | Baroncini, Alice Maffulli, Nicola Eschweiler, Jörg Molsberger, Friedrich Klimuch, Alexandra Migliorini, Filippo |
author_sort | Baroncini, Alice |
collection | PubMed |
description | BACKGROUND: This Bayesian network meta-analysis investigated the available randomized control trials (RCTs) to point out which acupuncture protocol is the most effective for chronic aspecific low back pain (LBP). Efficacy was measured in terms of pain (Visual Analogic Scale, VAS) and disability (Roland Morris Disability Questionnaire, RMQ), Transcutaneous Electrical Nerve Stimulation (TENS). METHODS: PubMed, Google scholar, Embase, and Scopus were accessed in March 2022. All the RCTs comparing two or more acupuncture modalities for aspecific chronic LBP were accessed. Only studies which investigated the efficacy of acupuncture on patients with symptoms lasting a minimum of 1.5 months, or with at least three episodes in the previous 12 months, were considered eligible. The Review Manager Software (The Nordic Cochrane Collaboration, Copenhagen) was used for the methodological quality assessment. The STATA Software/MP, Version 14.1 (StataCorporation, College Station, Texas, USA), was used for the statistical analyses. The NMA was performed through the STATA routine for Bayesian hierarchical random-effects model analysis. RESULTS: Data from 44 RCTs (8338 procedures) were retrieved. 56% of patients were women. The mean age of the patients was 48 ± 10.6 years. The mean BMI was 26.3 ± 2.2 kg/m(2). The individual group (95% confidence interval (CI) 2.02, 7.98) and the standard combined with TENS (95% CI 2.03, 7.97) demonstrated the highest improvement of the RMQ. The VAS score was lower in the standard combined with TENS group (95% CI 3.28, 4.56). Considering the standard acupuncture group, different studies used similar protocols and acupuncture points and the results could thus be compared. The equation for global linearity did not find any statistically significant inconsistency in any of the network comparison. CONCLUSION: Verum acupuncture is more effective than sham treatment for the non-pharmacological management of LBP. Among the verum protocols, individualized acupuncture and standard acupuncture with TENS were the protocols that resulted in the highest improvement in pain and quality of life. LEVEL OF EVIDENCE: Level I, Bayesian network meta-analysis of RCTs. |
format | Online Article Text |
id | pubmed-9208133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92081332022-06-21 Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis Baroncini, Alice Maffulli, Nicola Eschweiler, Jörg Molsberger, Friedrich Klimuch, Alexandra Migliorini, Filippo J Orthop Surg Res Systematic Review BACKGROUND: This Bayesian network meta-analysis investigated the available randomized control trials (RCTs) to point out which acupuncture protocol is the most effective for chronic aspecific low back pain (LBP). Efficacy was measured in terms of pain (Visual Analogic Scale, VAS) and disability (Roland Morris Disability Questionnaire, RMQ), Transcutaneous Electrical Nerve Stimulation (TENS). METHODS: PubMed, Google scholar, Embase, and Scopus were accessed in March 2022. All the RCTs comparing two or more acupuncture modalities for aspecific chronic LBP were accessed. Only studies which investigated the efficacy of acupuncture on patients with symptoms lasting a minimum of 1.5 months, or with at least three episodes in the previous 12 months, were considered eligible. The Review Manager Software (The Nordic Cochrane Collaboration, Copenhagen) was used for the methodological quality assessment. The STATA Software/MP, Version 14.1 (StataCorporation, College Station, Texas, USA), was used for the statistical analyses. The NMA was performed through the STATA routine for Bayesian hierarchical random-effects model analysis. RESULTS: Data from 44 RCTs (8338 procedures) were retrieved. 56% of patients were women. The mean age of the patients was 48 ± 10.6 years. The mean BMI was 26.3 ± 2.2 kg/m(2). The individual group (95% confidence interval (CI) 2.02, 7.98) and the standard combined with TENS (95% CI 2.03, 7.97) demonstrated the highest improvement of the RMQ. The VAS score was lower in the standard combined with TENS group (95% CI 3.28, 4.56). Considering the standard acupuncture group, different studies used similar protocols and acupuncture points and the results could thus be compared. The equation for global linearity did not find any statistically significant inconsistency in any of the network comparison. CONCLUSION: Verum acupuncture is more effective than sham treatment for the non-pharmacological management of LBP. Among the verum protocols, individualized acupuncture and standard acupuncture with TENS were the protocols that resulted in the highest improvement in pain and quality of life. LEVEL OF EVIDENCE: Level I, Bayesian network meta-analysis of RCTs. BioMed Central 2022-06-20 /pmc/articles/PMC9208133/ /pubmed/35725480 http://dx.doi.org/10.1186/s13018-022-03212-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Systematic Review Baroncini, Alice Maffulli, Nicola Eschweiler, Jörg Molsberger, Friedrich Klimuch, Alexandra Migliorini, Filippo Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis |
title | Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis |
title_full | Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis |
title_fullStr | Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis |
title_full_unstemmed | Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis |
title_short | Acupuncture in chronic aspecific low back pain: a Bayesian network meta-analysis |
title_sort | acupuncture in chronic aspecific low back pain: a bayesian network meta-analysis |
topic | Systematic Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208133/ https://www.ncbi.nlm.nih.gov/pubmed/35725480 http://dx.doi.org/10.1186/s13018-022-03212-3 |
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