Evidence map›Paper›PMID 39510790›Full record

ArticleBMJ open2024

Validity of data extraction in acupuncture meta-analysis: a reproducibility study protocol.

Yuting Duan, Pinge Zhao, Yuening Deng, Wenting Luo, Zewei Chen, Shujuan Liu, Jinjin Zhou, Ziwen Xu, Binbin Tang, Lin Yu

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yuting DuanEvidence-based Medicine Center, The Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China yul@gzhmu.edu.cn duanyt@gzhmu.edu.cn.ORCID http://orcid.org/0000-0002-9453-0592
Pinge ZhaoDepartment of Integrated Chinese and Western Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0002-5028-9901
Yuening DengEvidence-based Medicine Center, The Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Wenting LuoEvidence-based Medicine Center, The Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Zewei ChenDepartment of Integrated Chinese and Western Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Shujuan LiuEvidence-based Medicine Center, The Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Jinjin ZhouThe Affiliated Guangzhou Hospital of TCM of Guangzhou University of Chinese Medicine, Guangzhou, P. R. China, Guangzhou, Guangdong, China.
Ziwen XuClinical School of Integrated Traditional Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, Guangdong, China.
Binbin TangClinical School of Integrated Traditional Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, Guangdong, China.
Lin YuEvidence-based Medicine Center, The Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China yul@gzhmu.edu.cn duanyt@gzhmu.edu.cn.ORCID http://orcid.org/0000-0002-3924-4569

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSystematic review and meta-analysis occupy the apex of the evidence pyramid, serving as the most comprehensive and reliable form of evidence-based assessment. Data extraction is a crucial juncture in meta-analysis, establishing the underpinnings for the outcomes and deductions drawn from systematic reviews (SRs). However, the frequency of data extraction errors in meta-analysis is quite significant. Data extraction errors can lead to biased study results, affect the credibility of study results and even mislead clinical practice. The quantity of acupuncture randomised controlled trials and SRs has expanded rapidly recently, yet the validity of data extraction remains unexplored. Hence, our study aims to investigate the validity of data extraction errors in acupuncture SRs, the effect of data extraction errors on results and the relevant guidelines used erroneous results. METHODS AND ANALYSIS: Four databases including MEDLINE, Web of Science, Cochrane linbrary and EMBASE will be searched from 1 January 2019 to 31 December 2023 for acupuncture SRs. Two researchers will independently extract data from the meta-analysis and the original study into a standardised data extraction table. A senior investigator, who did not participate in the data extraction process, will verify the results. In cases of discrepancies, the senior researcher will conduct further extraction and consult with another senior researcher to determine the final results. We will analyse the frequency and type of data extraction errors and data estimation errors and evaluate the effect of data extraction errors on results. Quantile regression will be used to explore the factors influencing data extraction error frequency at 25th, 50th and 75th percentiles. Finally, we will further search for guidelines used erroneous results. ETHICS AND DISSEMINATION: Ethical approval is not necessary for this study. This protocol has been registered in Open Science Framework Registries. REGISTRATION DOI: https://doi.org/10.17605/OSF.IO/CHMPA.

Indexed as

Acupuncture TherapyHumansMeta-Analysis as TopicReproducibility of ResultsResearch DesignSystematic Reviews as TopicAcupunctureMeta-analysisSystematic review

Identifiers

PMID39510790
PMCPMC11552605

What OpenQuestion holds

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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 OpenQuestion graph.