Evidence map›Paper›PMID 36309716›Full record

ArticleBiomedical engineering online2022

Comprehensive bibliometric and visualized analysis of research on fecal microbial transplantation published from 2000 to 2021.

Jing Ma, Ting Chen, Xiangxue Ma, Beihua Zhang, Jiaqi Zhang, Lin Xu, Yifan Wang, Jinke Huang, Zhihong Liu, Fengyun Wang and 1 more

Abstract read
In one paragraph

Article in Biomedical engineering online, 2022. 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

11 authors.

Jing Ma *Institute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Ting Chen *Institute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Xiangxue MaInstitute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Beihua ZhangInstitute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Jiaqi ZhangInstitute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Lin XuDepartment of Gastroenterology, Shenzhen Hospital of Traditional Chinese Medicine, Shenzhen, China.
Yifan WangDepartment of Gastroenterology, Peking University Traditional Chinese Medicine Clinical Medical School (Xiyuan), Beijing, China.
Jinke HuangInstitute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Zhihong LiuDepartment of Gastroenterology, Peking University Traditional Chinese Medicine Clinical Medical School (Xiyuan), Beijing, China.
Fengyun WangInstitute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China. wfy811@163.com.
Xudong TangInstitute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China. txdly@sina.com.

Funding

China Academy of Chinese Medical Sciences Innovation Fund CI2021A01012Inheritance and innovation team of Traditional Chinese Medicine for the treatment of Refractory Gastrointestinal Diseases ZYYCXTD-C-202010National Natural Science Foundation of China 81830118National Natural Science Foundation of China 82074420Young Elite Scientists Sponsorship Program by CAST 2019-QNRC1-02
6 · The paper itself

Abstract

backgroundFecal microbial transplantation has emerged in recent years as a method of treating disease by rebuilding the intestinal flora. However, few bibliometric analyses have systematically studied this area of research. We aimed to use bibliometric analysis to visualize trends and topical research in fecal microbial transplantation to help provide insight into future trends in clinical and basic research. MATERIALS AND

methodsArticles and reviews related to fecal microbial transplantation were collected from the Web of Science Core Collection. Significant information associated with this field was visually analyzed by using Biblioshiny and CtieSpace software.

resultsA total of 3144 articles and overviews were included. The number of publications related to fecal microbial transplantation significantly increased yearly. These publications mainly came from 100 countries, led by the US and China, and 521 institutions. The most prolific and influential author is KHORUTS A. The main disciplines and application fields of fecal microbial transplantation included molecular /biology/immunology and medicine/clinical medicine, and the research foundation of fecal microbial transplantation was molecular /biology/genetics and health/nursing/medicine. An alluvial flow visualization showed several landmark articles. New developments were identified in terms of reference and keyword citation bursts. Data analysis showed that different FMT preparation and delivery methods gradually appeared as research hotspots. The main research keywords in the last 3 years were chain fatty acids, Akkermansia muciniphila, and insulin sensitivity, other keywords were current and developing research fields.

conclusionResearch on fecal microbial transplantation is flourishing and many new applications of fecal microbial transplantation are emerging. Microbial metabolites such as short-chain fatty acids and the microbiota-gut-brain axis have become the focus of current research and are future research trends.

Indexed as

Biomedical ResearchBibliometricsChinaPublicationsBibliometricBiblioshinyCiteSpaceFecal microbial transplantationVisualized analysis

Identifiers

PMID36309716
PMCPMC9617244

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.