Evidence map›Paper›PMID 33546023›Full record

ArticleMedicine2021

The therapeutic efficacy of Xuanfei Baidu Formula combined with conventional drug in the treatment of coronavirus disease 2019: A protocol for systematic review and meta-analysis.

Fan Li, Yajuan Li, Jingxia Zhang, Shasha Li, Ajuan Mao, Chongbo Zhao, Weifeng Wang, Fang Li

Abstract read
In one paragraph

Article in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  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.

Fan LiShaanxi Academy of Traditional Chinese Medicine, Xi'an, Shaanxi, China.
Yajuan LiPharmacy College, Shaanxi University of Chinese Medicine, Xianyang.
Jingxia ZhangPharmacy College, Shaanxi University of Chinese Medicine, Xianyang.
Shasha LiShaanxi Academy of Traditional Chinese Medicine, Xi'an, Shaanxi, China.
Ajuan MaoShaanxi Academy of Traditional Chinese Medicine, Xi'an, Shaanxi, China.
Chongbo ZhaoPharmacy College, Shaanxi University of Chinese Medicine, Xianyang.
Weifeng WangShaanxi Academy of Traditional Chinese Medicine, Xi'an, Shaanxi, China.
Fang LiShaanxi Academy of Traditional Chinese Medicine, Xi'an, Shaanxi, China.ORCID 0000-0001-8871-956

Funding

the National Natural Science Foundation of China No.81803732
6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) is a new acute espiratory infectious disease that has been in a public health emergency of international concern. In China, the combination of Xuanfei Baidu Formula (XBF) and conventional drug is used in the clinical treatment of patients with new coronary pneumonia, However, there is no comprehensive and systematic evidence on the effectiveness and safety of XBF. MATERIALS AND

methodsWe search for research in PubMed, China National Knowledge Infrastructure, Wan-fang Database, China Biomedical Database, and Chinese Science Citation Database. For "Xuanfei Baidu Formula" and "COVID-19," we screened suitable articles without language restrictions on keywords, Review Manager 5.3 and STATA 14.2 software was used for the data analysis.

resultsThe systematic review and meta-analysis will evaluate the efficacy and safety of XBF combined with conventional drug in the treatment of COVID-19.

conclusionWe will provide evidence of XBF for the treatment on COVID-19 patients. INPLASY REGISTRATION NUMBER: INPLASY2020120011.

Indexed as

COVID-19 Drug TreatmentDrugs, Chinese HerbalMedicine, Chinese TraditionalHumansMeta-Analysis as TopicSystematic Reviews as TopicDrugs, Chinese Herbal

Identifiers

PMID33546023
PMCPMC7837860

What OpenQuestion holds

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LicenceCC BY
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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.