A Comprehensive Approach to TB Control in Diabetic Populations

1. Background

• Type 2 Diabetes Mellitus (DM2) is a recognized risk factor for Tuberculosis (TB) due to impaired host immunity, especially in settings with high TB prevalence.

• Studying this relationship is complex because of global population heterogeneity, including differences in:

  • Age, access to medical care, glucose control levels.

  • Types and numbers of complications, and medications available.

2. Key Findings

• Military Personnel: Higher prevalence and more rapid cumulative risk of recurrent TB in those with DM2 compared to those without.

• Geographic and Occupational Risks: In resource-limited settings (e.g., Peru), military personnel with DM2 may face additional risk due to fieldwork exposure.

• Sex-Based Differences: DM is associated with a higher TB recurrence risk in men, potentially due to factors like smoking and impaired immunity, though no significant association in women.

• Glycemic Control: Poor glycemic control, higher fasting plasma glucose (FPG), and elevated HbA1c levels are associated with cavity formation, sputum positivity, and extensive lesions in TB-DM patients.

3. Risk Factors and Confounders

• Risk Factors: Age, sex, and glycemic control at admission influence cavity formation. FPG levels at admission and discharge are associated with lesion location and HbA1c levels.

• Confounders: Smoking, alcohol use, and chronic obstructive pulmonary disease (COPD) may exacerbate TB severity and recurrence, particularly among male DM patients.

4. Screening and Cost Efficiency

• Mass Screening: While feasible, mass TB screening among persons with diabetes (PWD) may not be cost-efficient due to low detection rates. High costs are largely driven by diabetes management rather than TB-related expenses.

• Targeted Screening: More efficient in populations with high TB incidence (≥100 cases per 100,000). A risk-stratified approach could be practical in low to medium TB burden areas.

• Symptom Screening: Insufficient alone, necessitating comprehensive methods to detect TB among PWD.

5. TB Control Frameworks and Strategies

• DOTS (Directly Observed Treatment, Short-Course):

  • A public health strategy that includes:

    • Political commitment, case detection, short-course chemotherapy with patient support, reliable drug supplies, and standardized outcome reporting.

• MDG Framework:

  • Focuses on DOTS with case detection and treatment success metrics, along with broader impact measures (incidence, prevalence, deaths).

  • Emphasizes comprehensive TB control and epidemiological evaluation beyond DOTS.

• Comprehensive TB Approach:

  • Prevention and improved patient care, especially among patients with HIV or drug-resistant TB.

  • Integration of new technologies and optimization of existing tools.

6. Regional Challenges and DOTS Expansion

• Regional Challenges: Africa and Eastern Europe face unique TB challenges due to HIV/AIDS and drug resistance, requiring tailored solutions.

• DOTS Limitations: By 2003, DOTS had nearly exhausted its public health utility, necessitating adaptations for non-public facilities and professional healthcare expansion to underserved areas.

7. Mortality and Incidence Measurement

• Mortality Statistics: Accurate TB death records are often unavailable in low-income countries due to inadequate vital registration systems.

• Incidence Rates: Rarely measured directly; usually estimated from population surveys or surveillance system assessments, though these methods have accuracy limitations.

Sources:

1. Alvarado-Valdivia, N.T., Flores, J.A., Inolopú, J.L. and Rosales-Rimache, J.A., 2024. Type 2 diabetes mellitus and recurrent Tuberculosis: A retrospective cohort in Peruvian military workers. Journal of Clinical Tuberculosis and Other Mycobacterial Diseases, 35, p.100432.

2. Dye, C., Watt, C.J., Bleed, D.M., Hosseini, S.M. and Raviglione, M.C., 2005. Evolution of tuberculosis control and prospects for reducing tuberculosis incidence, prevalence, and deaths globally. Jama, 293(22), pp.2767-2775. 

3. Liu, Q., You, N., Wen, J., Wang, J., Ge, Y., Shen, Y., Ding, X., Lu, P., Chen, C., Zhu, B. and Zhu, L., 2023. Yield and efficiency of a population-based mass tuberculosis screening intervention among persons with diabetes in Jiangsu Province, China. Clinical Infectious Diseases, 77(1), pp.103-111. 

4. Meng F, Lan L, Wu G, Ren X, Yuan X,Yang M, Chen Q, Peng X and Liu D (2023). Impact of diabetes itself and glycemic control status on tuberculosis. Front. Endocrinol. 14:1250001.

5. Eksombatchai, D., Jeong, D., Mok, J., Jeon, D., Kang, H.Y., Kim, H.J., Kim, H.S., Choi, H. and Kang, Y.A., 2023. Sex differences in the impact of diabetes mellitus on tuberculosis recurrence: a retrospective national cohort study. International Journal of Infectious Diseases, 127, pp.1-10.

See also: https://tbreadingnotes.blogspot.com/2024/10/impact-of-diabetes-itself-and-glycemic.html

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