Evidence map›Paper›PMID 27369951›Full record

SynthesisJournal of orthopaedic surgery and research2016

Fifty top-cited fracture articles from China: a systematic review and bibliometric analysis.

Fang Dong, Mengpo Fan, Zhiwei Jia

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of orthopaedic surgery and research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

3 authors.

Fang DongDepartment of Orthopaedics, The Second People's Hospital of Liaocheng, Shandong, China.
Mengpo FanDepartment of Orthopaedics, The Second People's Hospital of Liaocheng, Shandong, China. sdfanmengpo@163.com.
Zhiwei JiaDepartment of Orthopaedics, The 306th Hospital of People's Liberation Army, Beijing, China. jiazhiweivip@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith more than 50,000 orthopaedic surgeons, China is having an increasing impact on fracture surgery research. However, the most influential Chinese articles on fracture surgery have not been determined. This study aimed to characterise the most-cited articles on fracture surgery by Chinese authors to provide insight into the fracture research in China.

methodsThe Web of Science was used to search for citations of fracture surgery articles that originated in China. The 50 most-cited articles were identified. The title, number of citations, year of publication, journal, article type, level of evidence, city, institution, and authors were recorded and evaluated.

resultsThe 50 top-cited papers were published between 1984 and 2012. The most prolific decade began in the year 2000. These articles received 28 to 209 citations (mean 52), were written in English, and published in 12 journals. Injury was the most popular journal, with the largest number of articles (11) on the top 50 list. The region with the largest number of published articles was Hong Kong (20), followed by Kaohsiung (8), Shanghai (8), and Taipei (7). Most were clinical studies (39), while the remaining studies were basic science articles (11). The hip was the most common topic in the clinical studies. The most popular level of evidence was IV.

conclusionsThis list of the top 50 publications identifies the most influential Chinese fracture surgery articles for the global community. This study presents insight into the historical contributions of Chinese researchers and the fracture surgery trends in China.

Indexed as

BibliometricsChinaFractures, BoneHumansOrthopedic ProceduresBibliometric analysisFracture surgery

Identifiers

PMID27369951
PMCPMC4929748

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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.