Evidence map›Paper›PMID 35538695›Full record

ArticleEpidemiology and health2022

Spatial analysis of tuberculosis treatment outcomes in Shanghai: implications for tuberculosis control.

Jing Zhang, Xin Shen, Chongguang Yang, Yue Chen, Juntao Guo, Decheng Wang, Jun Zhang, Henry Lynn, Yi Hu, Qichao Pan and 1 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Epidemiology and health, 2022. 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
0.4field-weighted citation impact, top 41% 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

4 citing papers in PubMed, 5 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

11 authors at 5 institutions in 3 countries.

Jing ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China.
Xin ShenDivision of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention and Shanghai Institutes of Preventive Medicine, Shanghai, China.
Chongguang YangDepartment of Epidemiology of Microbial Diseases, School of Public Health, Yale University, New Haven, CT, USA.
Yue ChenSchool of Epidemiology, Public Health and Preventive Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
Juntao GuoDivision of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention and Shanghai Institutes of Preventive Medicine, Shanghai, China.
Decheng WangMedical Science College, China Three Gorges University, Yichang, China.
Jun ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China.
Henry LynnDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China.
Yi HuDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China.
Qichao PanDivision of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention and Shanghai Institutes of Preventive Medicine, Shanghai, China.
Zhijie ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, China.
Fudan University · CNShanghai Municipal Center For Disease Control Prevention · CNChina Three Gorges University · CNUniversity of Ottawa · CAYale University · US

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2009 to 2018
$26.4M
NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

objectivesTuberculosis (TB) treatment outcomes are a key indicator in the assessment of TB control programs. We aimed to identify spatial factors associated with TB treatment outcomes, and to provide additional insights into TB control from a geographical perspective.

methodsWe collected data from the electronic TB surveillance system in Shanghai, China and included pulmonary TB patients registered from January 1, 2009 to December 31, 2016. We examined the associations of physical accessibility to hospitals, an autoregression term, and random hospital effects with treatment outcomes in logistic regression models after adjusting for demographic, clinical, and treatment factors.

resultsOf the 53,475 pulmonary TB patients, 49,002 (91.6%) had successful treatment outcomes. The success rate increased from 89.3% in 2009 to 94.4% in 2016. The successful treatment outcome rate varied among hospitals from 78.6% to 97.8%, and there were 12 spatial clusters of poor treatment outcomes during the 8-year study period. The best-fit model incorporated spatial factors. Both the random hospital effects and autoregression terms had significant impacts on TB treatment outcomes, ranking 6th and 10th, respectively, in terms of statistical importance among 14 factors. The number of bus stations around the home was the least important variable in the model.

conclusionsSpatial autocorrelation and hospital effects were associated with TB treatment outcomes in Shanghai. In highly-integrated cities like Shanghai, physical accessibility was not related to treatment outcomes. Governments need to pay more attention to the mobility of patients and different success rates of treatment among hospitals.

Indexed as

TuberculosisTuberculosis, PulmonaryChinaHumansSpatial AnalysisTreatment OutcomeChinaHospital effectPhysical accessibilitySpatial analysisTreatment outcomeTuberculosis

Identifiers

PMID35538695
PMCPMC9684007
OpenAlexW4280496280

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.