Evidence map›Paper›PMID 29506480›Full record

ArticleBMC infectious diseases2018

Treatment outcomes and factors affecting unsuccessful outcome among new pulmonary smear positive and negative tuberculosis patients in Anqing, China: a retrospective study.

Yufeng Wen, Zhiping Zhang, Xianxiang Li, Dan Xia, Jun Ma, Yuanyuan Dong, Xinwei Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
4.5field-weighted citation impact, top 4% 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

35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 68 citations in OpenAlex.

  1. Pooled it
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  3. Pooled it
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  17. Tuberculosis Treatment Outcomes in Brazil: Different Predictors for Each Type of Unsuccessful Outcome.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Observational
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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

7 authors at 1 institution in 1 country.

Yufeng WenSchool of Laboratory Medicine, Wannan Medical College, 22 West Wenchang Road, Wuhu, Anhui Province, 241002, People's Republic of China. wyf@wnmc.edu.cn.
Zhiping ZhangTuberculosis Prevention and Control Department, Anqing Center for Disease Control and Prevention, Anqing City, Anhui Province, 246003, People's Republic of China.
Xianxiang LiTuberculosis Prevention and Control Department, Anqing Center for Disease Control and Prevention, Anqing City, Anhui Province, 246003, People's Republic of China.
Dan XiaSchool of Laboratory Medicine, Wannan Medical College, 22 West Wenchang Road, Wuhu, Anhui Province, 241002, People's Republic of China.
Jun MaSchool of Laboratory Medicine, Wannan Medical College, 22 West Wenchang Road, Wuhu, Anhui Province, 241002, People's Republic of China.
Yuanyuan DongSchool of Laboratory Medicine, Wannan Medical College, 22 West Wenchang Road, Wuhu, Anhui Province, 241002, People's Republic of China.
Xinwei ZhangSchool of Laboratory Medicine, Wannan Medical College, 22 West Wenchang Road, Wuhu, Anhui Province, 241002, People's Republic of China.
Wannan Medical College · CN

Funding

College Students' Scientific Research Fund of Wannan Medical College WK2014S28Key Research and Development Program of Anhui Province of China 1704a0802154University Student Innovative Entrepreneurship Training Project of Anhui Province 201410368067University Student Innovative Entrepreneurship Training Project of Anhui Province 201510368036
6 · The paper itself

Abstract

backgroundMonitoring the treatment outcomes of tuberculosis and determining the specific factors associated with unsuccessful treatment outcome are essential to evaluate the effectiveness of tuberculosis control program. This study aimed to assess treatment outcomes and explore the factors associated with unsuccessful outcomes among new pulmonary smear positive and negative tuberculosis patients in Anqing, China.

methodsA nine-year retrospective study was conducted using data from Anqing Center for Diseases Prevention and Control. New pulmonary tuberculosis patients treated with two six-month regimens were investigated. Non-conditional logistic regression was performed to calculate odds ratios and 95% confidence intervals for factors associated with unsuccessful outcomes.

resultsAmong 22,998 registered patients (16,939 males, 6059 females), 64.54% were smear-positive patients. The treatment success rates was 95.02% for smear-positive patients and 95.00% for smear-negative patients. Characteristics associated with an higher risk of unsuccessful treatment among smear-positive patients included aged above 35 years, treatment management model of self-medication, full-course management and supervision in intensive phase, unchecked chest X-ray, cavity in chest X-ray, and miliary shadow in chest X-ray, while normal X-ray was negative factor. Unsuccessful treatment among smear-negative patients was significantly associated with age over 45 years, treatment management model of full-course management, unchecked chest X-ray, presence of miliary shadow in chest X-ray and delay over 51 days.

conclusionsTuberculosis treatment in Anqing area was successful and independent of treatment regimens. Special efforts are required for patients with unsuccessful outcomes.

Indexed as

AdolescentAdultAgedAntitubercular AgentsChinaFemaleHumansLogistic ModelsMaleMiddle AgedOdds RatioRetrospective StudiesSputumThoraxTreatment OutcomeTuberculosis, PulmonaryAntitubercular AgentsNew pulmonary tuberculosisRetrospective studyUnsuccessful treatment outcomes

Identifiers

PMID29506480
PMCPMC5836329
OpenAlexW2798031312

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.