Evidence map›Paper›PMID 36575646›Full record

ReviewNursing open2023

What can we learn from the Baduanjin rehabilitation as COVID-19 treatment?: A narrative review.

Zhenggang Zhu, Xiaoyan Pan, Faping Zhong, Jun Tian, Marilyn Li Yin Ong

Open access · goldAbstract readReview
In one paragraph

Review in Nursing open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

5 citing papers in PubMed, 12 citations in OpenAlex.

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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

5 authors at 4 institutions in 3 countries.

Zhenggang ZhuExercise and Sports Science Programme, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.ORCID 0000-0003-4332-7225
Xiaoyan PanSchool of Nursing, Hunan University of Chinese Medicine, Changsha, Hunan, China.
Faping ZhongDepartment of Respiratory Medicine, The First Hospital Changde City of Traditional Chinese Medicine, Changde, Hunan, China.
Jun TianDepartment of Geriatric Medicine, Xiangya Hospital of Central South University, Changsha, Hunan, China.
Marilyn Li Yin OngExercise and Sports Science Programme, School of Health Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.ORCID 0000-0003-4608-8370
Universiti Sains Malaysia · MYCentral South University · CNHunan University of Traditional Chinese Medicine · CNThe First People's Hospital of Changde · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo understand Baduanjin rehabilitation therapy in mild COVID-19 patients.

designA narrative review.

methodsA literature search for COVID-19 and Baduanjin treatments was conducted on Chinese and English electronic databases: China National Knowledge Infrastructure, Wanfang Data, Embase, PubMed, Scopus, Science Direct, Ebscohost, SPORTDiscus and ProQuest.

resultsTwelve studies on the Baduanjin rehabilitation for COVID-19 patients have been included. We acknowledged the considerable published research and current clinical practice using Baduanjin for COVID-19 treatment in the following areas: anxiety, depression, insomnia, lung function rehabilitation, immunity and activity endurance.

conclusionThe use of Baduanjin as adjuvant therapy for COVID-19 patients' rehabilitation is still limited, therefore, more clinical studies are needed to confirm its efficacy.

Indexed as

COVID-19Exercise TherapyMedicine, Chinese TraditionalRehabilitationRespiratory Function TestsBaduanjinCOVID-19exerciserehabilitation

Identifiers

PMID36575646
PMCPMC9880712
OpenAlexW4312214493

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.