Evidence map›Paper›PMID 36278116›Full record

ReviewHeliyon2022

A bibliometric analysis of research related Chinese Medicine in the prevention and treatment of corona virus disease 2019.

Zhong Dayuan, Li Lan, Xu Luhua, Li Huanjie, Chen Dahao, Luo Yumiao, Li Dingxiang, Deng Yihui

Abstract readReview
In one paragraph

Review in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
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

8 authors.

Zhong DayuanGuangdong Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Foshan, 528200, China.
Li LanHunan University of Chinese Medicine, Changsha, 410208, China.
Xu LuhuaShenzhen Baoan District Traditional Chinese Medicine Hospital, Shenzhen, 518133, China.
Li HuanjieFoshan Hospital of Traditional Chinese Medicine, Foshan, 528099, China.
Chen DahaoGuangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Luo YumiaoGuangdong Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Foshan, 528200, China.
Li DingxiangHunan University of Chinese Medicine, Changsha, 410208, China.
Deng YihuiHunan University of Chinese Medicine, Changsha, 410208, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To perform a bibliometric analysis of published research related to the use of traditional Chinese medicine (TCM) for the treatment of Coronavirus Disease 2019 (COVID-19). Methods: Research documents related to the use of TCM for prevention and treatment of COVID-19 published up to September 19, 2021, were retrieved from the Web of Science database. Bibliometrix R 4.0 software package was used to analyze data, including countries of publication, research institutions, journals, citations, and keywords. Further analysis was conducted to identify co-occurrence of keywords in the documents, including their titles and abstracts. Cooperative network analyses of authors, institutions, and countries of publication were also conducted. The classification types were statistically analyzed and the research progress of key TCMs was reviewed. Results: A total of 417 documents were included in our analysis. Of these, 85.13% originated in China. Of the 417 documents, 148 (35.5%) were published in journals with impact factors in quartile 1 and 164 (39.3%) in journals in quartile 2. The documents were mainly published in journals categorized as Medicine. The results of network analysis showed close cooperation between institutions and countries. Excluding disease- and drug-related keywords, the top four keywords were 'Systematic review', 'Network pharmacology', 'Medicine' and 'Molecular docking'. Keyword co-occurrence analysis showed 4 main keywords association groups. Statistical analysis of the TCM studies showed that Lianhua Qingwen capsule, Qingfei Paidu decoction, Shufeng Jiedu capsules and ReDuNing injection were the most studied Chinese medicines. Lianhua Qingwen capsules, Qingfei Paidu decoction, ReDuNing injection, and Shufeng Jiedu capsules were used in clinical, bioinformatics, and basic research. Toujie Quwen granule, Jinhua Qinggan granule, Shuanghuanglian oral liquid, Tanreqing injection, and Xuanfei Baidu decoction were used in clinical and bioinformatics research, although basic research on their mechanisms of action is lacking. Conclusion: Research intensity and recognition, as well as cooperation, in the field of Chinese medicine for the prevention and treatment of COVID-19 has increased. Research types are generally comprehensive, and investigated several TCM formulations that are specifically recommended by Chinese COVID-19 guidelines. However, comprehensive, in-depth research on their molecular mechanisms of action is still lacking. More basic research is thus needed to identify therapeutic mechanisms to standardize and validate the use of TCM in the prevention and treatment of COVID-19.

Indexed as

BibliometricsCoronavirus disease 2019COVID-19PreventionTraditional Chinese medicineTreatment

Identifiers

PMID36278116
PMCPMC9575316

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.