Evidence map›Paper›PMID 34900894›Full record

ArticleFrontiers in public health2021

How to Effectively Identify Patients With Rifampin-Resistant Tuberculosis in China: Perspectives of Stakeholders Among Service Providers.

Qianhui Hua, Hong Xu, Xinyi Chen, Junhang Pan, Ying Peng, Wei Wang, Bin Chen, Jianmin Jiang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2021. 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, top 84% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

8 authors at 3 institutions in 1 country.

Qianhui HuaSchool of Medicine, Ningbo University, Ningbo, China.
Hong XuDepartment of Tuberculosis Control and Prevention, Xiaoshan District Center for Disease Control and Prevention, Hangzhou, China.
Xinyi ChenDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Junhang PanDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Ying PengDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Wei WangDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Bin ChenDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Jianmin JiangDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Zhejiang Center for Disease Control and Prevention · CNHangzhou Center for Disease Control and Prevention · CNNingbo University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To evaluate China's current rifampin-resistant tuberculosis (RR-TB) screening strategy from stakeholders' perspectives, the perceptions, attitudes, and interests of 245 stakeholders from three eastern, central, and western China provinces on RR-TB screening strategies, were investigated through stakeholder survey and interview. The attitudes toward three RR-TB screening strategies were statistically different: inclination to choose who to screen (

Indexed as

TuberculosisTuberculosis, Multidrug-ResistantHumansMass ScreeningRifampinRifampinattitudespolicyrifampin-resistant tuberculosisscreeningstakeholders

Identifiers

PMID34900894
PMCPMC8651999
OpenAlexW3217279641

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.