Metformin promotes smear conversion in tuberculosis‐diabetes comorbidity and construction of prediction models

作者：Yili Wang, Yanbing Zhou, Liyu Chen, Yuhui Cheng, Hongli Lai, Mengyuan Lyu, Jiongjiong Zeng, Yao Zhang, Ping Feng, Binwu Ying · 发表于：Journal of Clinical Laboratory Analysis · 年份：2022 · DOI：10.1002/jcla.24755 · 被引用次数：8 · 研究领域：Tuberculosis Research and Epidemiology、Metabolism, Diabetes, and Cancer、Diagnosis and treatment of tuberculosis

BACKGROUND: The comorbidity of tuberculosis (TB) and diabetes mellitus (DM) is a global health concern. Metformin is commonly used in DM but the potential effectiveness in comorbid patients is uncertain. This retrospective study aims to investigate the effect of metformin on TB-DM comorbidity and construct prediction models. METHODS: Patients diagnosed with TB-DM in West China Hospital were retrospectively enrolled from Nov 2013 to Sep 2019. Electronic health records of patients were extracted. Two-month smear conversion (2SC) was considered an outcome indicator of TB. Univariate and multivariate logistic regression (LR) were used to assess the role of metformin and other independent predictors. Meanwhile, prediction models were built by LR, elastic net regression, support vector machine, k-nearest neighbors, and random forest. RESULTS: A total of 927 individuals were recruited, among which 408 (44.01%) were metformin-exposed patients. A higher 2SC rate was observed in the metformin users. Other impact factors such as smoking, glucose, and creatinine levels were also identified. Multivariable models were then constructed using filtered variables. The support vector machine model yields the highest AUC (0.808, 95% CI: 0.767-0.849) and specificity (83.24%). LR model outperformed others in terms of sensitivity (69.71%). CONCLUSION: This retrospective study of a large population from southwestern China provides strong clinical evidence for the positive effects of metformin in TB-...