ArticleScientific reports2019
Analytical Exploration of Potential Pathways by which Diabetes Mellitus Impacts Tuberculosis Epidemiology.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed, 17 citations in OpenAlex.
- Molecular Epidemiology ofMicroorganisms · 2025Review
- Prior tuberculosis, radiographic lung abnormalities and prevalent diabetes in rural South Africa.BMC infectious diseases · 2024Article
- Differential Role of Type 2 Diabetes as a Risk Factor for Tuberculosis in the Elderly versus Younger Adults.Pathogens (Basel, Switzerland) · 2022Article
- Increased Risk of Incident Diabetes Among Individuals With Latent Tuberculosis Infection.Diabetes care · 2022Article
- The Interaction of Diabetes and Tuberculosis: Translating Research to Policy and Practice.Tropical medicine and infectious disease · 2021Review
- Proteomic profile of vitreous in patients with tubercular uveitis.Tuberculosis (Edinburgh, Scotland) · 2021Article
- Association between economic development level and tuberculosis registered incidence in Shandong, China.BMC public health · 2020Article
- Forecasting the impact of diabetes mellitus on tuberculosis disease incidence and mortality in India.Journal of global health · 2019Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We aimed to develop a conceptual framework of diabetes mellitus (DM) effects on tuberculosis (TB) natural history and treatment outcomes, and to assess the impact of these effects on TB-transmission dynamics. The model was calibrated using TB data for India. A conceptual framework was developed based on a literature review, and then translated into a mathematical model to assess the impact of the DM-on-TB effects. The impact was analyzed using TB-disease incidence hazard ratio (HR) and population attributable fraction (PAF) measures. Evidence was identified for 10 plausible DM-on-TB effects. Assuming a flat change of 300% (meaning an effect size of 3.0) for each DM-on-TB effect, the HR ranged between 1.0 (Effect 9-Recovery) and 2.7 (Effect 2-Fast progression); most effects did not have an impact on the HR. Meanwhile, TB-disease incidence attributed directly and indirectly to each effect ranged between -4.6% (Effect 7-TB mortality) and 34.5% (Effect 2-Fast progression). The second largest impact was for Effect 6-Disease infectiousness at 29.9%. In conclusion, DM can affect TB-transmission dynamics in multiple ways, most of which are poorly characterized and difficult to assess in epidemiologic studies. The indirect (e.g. onward transmission) impacts of some DM-on-TB effects are comparable in scale to the direct impacts. While the impact of several effects on the HR was limited, the impact on the PAF was substantial suggesting that DM could be impacting TB epidemiology to a larger extent than previously thought.
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