ArticleJournal of clinical laboratory analysis2022
Metformin promotes smear conversion in tuberculosis-diabetes comorbidity and construction of prediction models.
Article in Journal of clinical laboratory analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- The role of metformin in tuberculosis control among TB and diabetes mellitus comorbid individuals.Frontiers in microbiology · 2025Review
- The Complex Relationship Between Tuberculosis and Hyperglycemia.Diagnostics (Basel, Switzerland) · 2024Review
- The advances in adjuvant therapy for tuberculosis with immunoregulatory compounds.Frontiers in microbiology · 2024Review
- Metformin promotes smear conversion in tuberculosis-diabetes comorbidity and construction of prediction models.Journal of clinical laboratory analysis · 2022Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe 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.
methodsPatients 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.
resultsA 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%).
conclusionThis retrospective study of a large population from southwestern China provides strong clinical evidence for the positive effects of metformin in TB-DM. Metformin is associated with a better therapeutic outcome and promising for the adjuvant therapy of TB-DM. Furthermore, a combination of support vector machine and LR models is recommended to discriminate the patients with poor treatment outcomes.
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