Evidence map›Paper›PMID 35669895›Full record

ArticleRisk management and healthcare policy2022

Survival Analysis and Associated Factors for Pulmonary Tuberculosis Death: Evidence from the Information System of Tuberculosis Disease and Mortality Surveillance in China.

Kui Liu, Liyun Ai, Jin Pan, Fangrong Fei, Songhua Chen, Yu Zhang, Wei Wang, Qian Wu, Bin Chen, Junhang Pan and 1 more

Abstract read
In one paragraph

Article in Risk management and healthcare policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

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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.

Kui Liu *Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.ORCID 0000-0001-9833-1251
Liyun Ai *Hangzhou Municipal Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.ORCID 0000-0001-5484-1495
Jin PanDepartment of Non-Communicable Disease Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.
Fangrong FeiDepartment of Non-Communicable Disease Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.
Songhua ChenDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.
Yu ZhangDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.
Wei WangDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.
Qian WuDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.
Bin ChenDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.ORCID 0000-0002-3761-0465
Junhang PanDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.
Jieming ZhongDepartment of Non-Communicable Disease Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pulmonary tuberculosis (PTB) is a severe infection, and its factors that influence survival have not been explored in some developed regions. Therefore, this study aimed to identify the factors that influence TB survival in China. Methods: We acquired data of PTB deaths through matching two manage systems of PTB and mortality surveillance. The Kaplan-Meier method and Cox regression model were used to identify the significant factors under various survival times. Results: A total of 283 deaths were caused by PTB, in which 53.4% occurred during the first year. In the Cox regression model, regular sputum smear test could reduce the risk of PTB death from the result of one-, three-, and five-year survival; and history of PTB treatment could decline the risk of PTB death in the first year. Additionally, age of "75-90 years" and positive result of sputum smear test significantly increased the risk of PTB death for the findings of three- and five-year survival, while age of "60-75 years" could increase the probability of PTB death for five-year survival. Conclusion: To reduce PTB deaths, more attention should be paid to the older group especially in the first year. Regular sputum smear test could effectively reduce the mortality of PTB cases. More evidence-based interventions should be implemented to enhance the survival of patients with PTB.

Indexed as

influencing factorsurvival analysistuberculosis

Identifiers

PMID35669895
PMCPMC9166951

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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.