The effect of diabetes mellitus on tuberculosis in eastern China: A decision‐tree analysis based on a real‐world study

Author:

Ling Yuxiao1,Chen Xinyi2,Zhou Meng3,Zhang Mengdie3,Luo Dan4,Wang Wei2,Chen Bin2,Jiang Jianmin25ORCID

Affiliation:

1. School of Public Health, Health Science Center Ningbo University Ningbo China

2. Department of Tuberculosis Control and Prevention Zhejiang Provincial Center for Disease Control and Prevention Hangzhou China

3. Zhejiang University School of Public Health Hangzhou China

4. Department of Public Health Hangzhou Medical College Hangzhou China

5. Key Laboratory of Vaccine Prevention and Control of Infectious Disease of Zhejiang Province Hangzhou China

Abstract

AbstractObjectivesThe public health system faces major challenges due to the double burden of diabetes mellitus (DM) and tuberculosis (TB) in China. We aimed to investigate the prevalence and impact of diabetes on patients with TB.MethodsStratified cluster sampling was used to select 13 counties as study sites in the Zhejiang province. Patients who visited designated TB hospitals in these areas participated in this study between 1 January 2017 and 28 February 2019. Multiple logistic regression models were performed to investigate the association between DM and bacteriological and imaging results. A decision tree was used to predict the bacteriology and imaging results under the influence of DM.ResultsOf 5920 patients with newly diagnosed pulmonary tuberculosis, 643 (12.16%) had DM. Patients with pulmonary TB and DM were more likely to have pulmonary cavities (adjusted odds ratio [aOR], 2.81; 95% confidence intervals [95% CI]: 2.35–3.37) and higher rates of positive bacteriological tests (aOR, 2.32; 95% CI:1.87–2.87). Decision‐tree analysis showed similar results.ConclusionsConcurrence of DM and pulmonary TB makes patients more likely to have positive bacteriological results and pulmonary cavities. Therefore, appropriate measures are necessary to promptly identify and manage patients with TB and DM.

Publisher

Wiley

Subject

Endocrinology, Diabetes and Metabolism

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