Evidence mapPaperPMID 32015189Full record

SynthesisPostgraduate medical journal2020

Acupuncture versus sham acupuncture for simple obesity: a systematic review and meta-analysis.

Yu-Mei Zhong, Xiao-Chao Luo, Yang Chen, De-Li Lai, Wen-Ting Lu, Ya-Nan Shang, Lin-Lin Zhang, Hai-Yan Zhou

Registry-linked trialOpen access · greenAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Postgraduate medical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05075551 (Analyzing the Brain Alterations of Acupuncture on Patients With Chronic Prostatitis/Chronic Pelvic Pain Syndrome Evaluated by fMRI), which is not on this map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
8.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05075551 naunknown statusnot on this mapstarted 2022, after this paper: background citation

Analyzing the Brain Alterations of Acupuncture on Patients With Chronic Prostatitis/Chronic Pelvic Pain Syndrome Evaluated by fMRI: Study Protocol for a Randomized Trial

TypeinterventionalSponsorShanghai University of Traditional Chinese MedicineRan2022 to 2023Enrolled500ConditionsChronic Prostatitis With Chronic Pelvic Pain SyndromeArmsAcupuncture, Sham acupuncture, fMRI scan
3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 62 citations in OpenAlex.

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  18. Novel insights into weight loss: acupuncture combined with a very low-carbohydrate diet-a Swiss experience.Acupuncture in medicine : journal of the British Medical Acupuncture Society · 2023
    Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Yu-Mei ZhongAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Xiao-Chao LuoAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Yang ChenAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
De-Li LaiAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Wen-Ting LuAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Ya-Nan ShangAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Lin-Lin ZhangAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Hai-Yan ZhouAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China zhouhaiyan@cdutcm.edu.cn.ORCID http://orcid.org/0000-0003-1568-5287
Chengdu University of Traditional Chinese Medicine · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity is a growing chronic health problem worldwide. Studies about acupuncture for obesity treatment are many. But there are some doubts about the effectiveness of acupuncture versus sham acupuncture in treating obesity due to its lack of medical evidence. Therefore, the aim of this study is to assess the efficacy of acupuncture for obesity treatment and provide clinic evidence. Four English databases (PubMed, EMBASE, Web of Science and Cochrane Central Register of Controlled Trials) and four Chinese databases (China National Knowledge Infrastructure, Chinese BioMedical Database, Chinese Scientific Journal Database and Wan-Fang Data) were searched from their receptions to August 2019. Randomized controlled trials (RCTs) using the comparison between acupuncture and sham acupuncture to treat simple obesity were included. The primary outcome of body mass index (BMI) would be used to measure the effect of acupuncture on obesity. According to the trial data extraction form based on the Cochrane Handbook, two reviewers separately extracted the data. Risk of bias of the RCTs was assessed by the Cochrane Risk of Bias Tool. The study included 8 RCTs with 403 patients. When compared with sham acupuncture, acupuncture showed obviously effect in BMI reduction (MD=1.0kg/m2, 95% CI=0.6 to 1.4, P<0.001). There was also significant reduction in body weight (MD=1.85kg, 95%CI=0.82 to 2.88, p<0.001), WC (MD=0.97cm, 95%CI=0.24 to 1.71, p=0.01) and body fat mass percentage (MD=1.01, 95%CI=0.25 to 1.77, p<0.05). However, WHR (MD=0.01, 95%CI=0 to 0.03, p>0.05) was not statistically and significantly different between the acupuncture and control groups. Adverse effects were reported in 3 studies. The review suggests that acupuncture is an effective therapy for simple obesity rather than a placebo effect. This potential benefit needs to be further evaluated by longer-term and more rigorous RCTs.

Indexed as

ObesityPlacebosAcupuncture TherapyBody Mass IndexHumansTreatment OutcomePlaceboscomplementary medicineinformation managementpublic health

Identifiers

PMID32015189
PMCPMC7146934
OpenAlexW3004421879

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.