Evidence map›Paper›PMID 24223063›Full record

ReviewEvidence-based complementary and alternative medicine : eCAM2013

Systematic reviews and meta-analyses of traditional chinese medicine must search chinese databases to reduce language bias.

Xin-Yin Wu, Jin-Ling Tang, Chen Mao, Jin-Qiu Yuan, Ying Qin, Vincent C H Chung

Open access · hybridAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Evidence-based complementary and alternative medicine : eCAM, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 12 pooled it
3.0field-weighted citation impact, top 8% 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.

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

25 citing papers in PubMed, 12 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

Xin-Yin WuDivision of Epidemiology, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, 4/F, School of Public Health Building, Prince of Wales Hospital, Shatin, New Territories, Hong Kong ; Shenzhen Municipal Key Laboratory for Health Risk Analysis, Shenzhen Research Institute, The Chinese University of Hong Kong, 10 Yuexing Erdao, Nanshan District, Shenzhen, Guangdong Province, China.
Jin-Ling Tang
Chen Mao
Jin-Qiu Yuan
Ying Qin
Vincent C H Chung
Prince of Wales Hospital · CNChinese University of Hong Kong, Shenzhen · CNChinese University of Hong Kong · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systematic reviews (SRs) that fail to search non-English databases may miss relevant studies and cause selection bias. The bias may be particularly severe in SRs of traditional Chinese medicine (TCM) as most randomized controlled trials (RCT) in TCM are published and accessible only in Chinese. In this study we investigated how often Chinese databases were not searched in SRs of TCM, how many trials were missed, and whether a bias may occur if Chinese databases were not searched. We searched 5 databases in English and 3 in Chinese for RCTs of Chinese herbal medicine for coronary artery disease and found that 96.64% (115/119) eligible studies could be identified only from Chinese databases. In a random sample of 80 Cochrane reviews on TCM, we found that Chinese databases were only searched in 43 or 53.75%, in which almost all the included studies were identified from Chinese databases. We also compared SRs of the same topic and found that they may draw a different conclusion if Chinese databases were not searched. In conclusion, an overwhelmingly high percentage of eligible trials on TCM could only be identified in Chinese databases. Reviewers in TCM are suggested to search Chinese databases to reduce potential selection bias.

Identifiers

PMID24223063
PMCPMC3816048
OpenAlexW2105823414

What OpenQuestion holds

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Registered trials

None linked

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.