Evidence map›Paper›PMID 39314789›Full record

ArticleFrontiers in public health2024

Spatiotemporal distribution and risk factors for patient and diagnostic delays among groups with tuberculous pleurisy: an analysis of 5-year surveillance data in eastern China.

Yang Li, Dan Luo, Yi Zheng, Kui Liu, Songhua Chen, Yu Zhang, Wei Wang, Qian Wu, Yuxiao Ling, Yiqing Zhou and 2 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 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

12 authors.

Yang Li *School of Public Health, Hangzhou Normal University, Hangzhou, Zhejiang, China.
Dan Luo *School of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Yi Zheng *Department of Tuberculosis Control and Prevention, Jiaxing Nanhu District Center for Disease Control and Prevention, Jiaxing, Zhejiang, China.
Kui LiuDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Songhua ChenDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Yu ZhangDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Wei WangDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Qian WuDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Yuxiao LingSchool of Public Health, Health Science Center, Ningbo University, Ningbo, Zhejiang, China.
Yiqing ZhouSchool of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Bin ChenDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Jianmin JiangDepartment of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To understand and analyze the factors relating to patient and diagnostic delays among groups with tuberculous pleurisy (TP), and its spatiotemporal distribution in Zhejiang Province. Methods: Data of all tuberculous pleurisy patients were collected from the existing Tuberculosis Information Management System. A time interval of > 2 weeks between first symptom onset and visit to the designated hospital was considered a patient delay, and a time interval of > 2 weeks between the first visit and a confirmed TP diagnosis was considered a diagnostic delay. Univariate and multivariate logistic regression analyses were used to explore factors influencing patient and diagnostic delays in patients with TP. Spatial autocorrelation and spatiotemporal scan analyses were used to identify hot spots and risk clusters, respectively. Results: In total, 10,044 patients with TP were included. The median time and interquartile range for patients seeking medical care and diagnosis were 15 (7-30) and 1 (0-8) days, respectively. The results showed that people aged > 65 years, retirees, and residents of Jinhua, Lishui, and Quzhou were positively correlated with patient delay, whereas retreatment patients, houseworkers, unemployed people, and residents of Zhoushan or Ningbo were positively correlated with diagnostic delay. Additionally, high-risk clusters of patient delays were observed in the midwestern Zhejiang Province. The most likely clusters of TP diagnostic delays were found in southeast Zhejiang Province. Conclusion: In summary, patient delay of TP in Zhejiang province was shorter than for pulmonary tuberculosis in China, while the diagnostic delay had no difference. Age, city, occupation, and treatment history were related to both patient and diagnostic delays in TP. Interventions in central and western regions of Zhejiang Province should be initiated to improve the early detection of TP. Additionally, the allocation of health resources and accessibility of health services should be improved in the central and eastern regions of Zhejiang Province.

Indexed as

Delayed DiagnosisSpatio-Temporal AnalysisTuberculosis, PleuralAdolescentAdultAgedChinaFemaleHumansMaleMiddle AgedRisk FactorsYoung Adultdiagnostic delaypatient delayrisk factorsspatiotemporal distributiontuberculous pleurisy

Identifiers

PMID39314789
PMCPMC11416949

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