Evidence map›Paper›PMID 33350792›Full record

ArticleMedicine2020

The efficacy of Tuina for asthma: A protocol for a systematic review and meta-analysis.

Changhong Wang, Yong Jiang, Zhipeng Fan, Mao Zhao, Yuchang Jiang, Zhaodi Wang, Zhaoxing Chen

Abstract read
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. 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

7 authors.

Changhong WangSchool of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Yong Jiang
Zhipeng Fan
Mao Zhao
Yuchang Jiang
Zhaodi Wang
Zhaoxing Chen

Funding

National Natural Science Foundation of China 61801058
6 · The paper itself

Abstract

backgroundAsthma is one of the most common chronic diseases in the world, with ∼100 million asthma patients worldwide. China has become one of the countries with the highest asthma death rate in the world. Asthma is a chronic airway inflammatory disease. Patients with this disease may have symptoms such as cough, wheezing, and difficulty breathing. For many years, Western medicine has mainly used anti-inflammatory, anti-bronchial spasm, asthma, cough, and oxygen to treat this disease, but the effect is not good. Tuina is a common treatment for asthma in China. But at present, there is no systematic evaluation report on its therapeutic effectiveness and safety. This protocol aims to reveal the efficacy and safety of Tuina for treating asthma.

methodsThe following databases will be searched by electronic methods: PubMed, EBASE, WHO International Clinical Trials Registry Platform, Embase, the Chinese Biomedical Literature Database (CBM), Wan-fang Data (WANFANG), the China National Knowledge Infrastructure (CNKI), and other sources from inception to November 2020. Bias risk, subgroup analysis, data synthesis, and meta-analyses will be assessed with RevMan V.5.3 software if the data is met inclusion conditions.

resultsThis study will present a quality evidence of Tuina for the treatment of astma patients.

conclusionThe systematic review will present reliable evidence to judge whether or not Tuina is a safe and effective intervention for asthma patients. International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) registration number: INPLASY2020110100.

Indexed as

AsthmaHumansMassageMedicine, Chinese TraditionalMeta-Analysis as TopicPhysical Therapy ModalitiesResearch DesignSystematic Reviews as Topic

Identifiers

PMID33350792
PMCPMC7769308

What OpenQuestion holds

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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.