Diabetes Mellitus Among Pulmonary Tuberculosis Patients From 4 Tuberculosis-endemic Countries: The TANDEM Study.

BACKGROUND: Diabetes mellitus (DM) increases active tuberculosis (TB) risk and worsens TB outcomes, jeopardizing TB control especially in TB-endemic countries with rising DM prevalence rates. We assessed DM status and clinical correlates in TB patients across settings in Indonesia, Peru, Romania, and South Africa. METHODS: Age-adjusted DM prevalence was estimated using laboratory glycated hemoglobin (HbA1c) or fasting plasma glucose in TB patients. Detailed and standardized sociodemographic, anthropometric, and clinical measurements were made. Characteristics of TB patients with or without DM were compared using multilevel mixed-effect regression models with robust standard errors. RESULTS: Of 2185 TB patients (median age 36.6 years, 61.2% male, 3.8% human immunodeficiency virus-infected), 12.5% (267/2128) had DM, one third of whom were newly diagnosed. Age-standardized DM prevalence ranged from 10.9% (South Africa) to 19.7% (Indonesia). Median HbA1c in TB-DM patients ranged from 7.4% (Romania) to 11.3% (Indonesia). Compared to those without DM, TB-DM patients were older and had a higher body mass index (BMI) (P value < .05). Compared to those with newly diagnosed DM, TB patients with diagnosed DM had higher BMI and HbA1c, less severe TB, and more frequent comorbidities, DM complications, and hypertension (P value < .05). CONCLUSIONS: We show that DM prevalence and clinical characteristics of TB-DM vary across settings. Diabetes is primarily known but untreated, hyperglycemia is often severe, and many patients with TB-DM have significant cardiovascular disease risk and severe TB. This underlines the need to improve strategies for better clinical management of combined TB and DM.

Implementing a socio-technical system for computer-aided tuberculosis diagnosis in Peru: A field trial among health professionals in resource-constraint settings.

A major challenge of tuberculosis diagnosis is the lack of universal accessibility to bacteriological confirmation. Computer-aided diagnostic interventions have been developed to address this gap and their successful implementation depends on many health systems factors. A socio-technical system to implement a computer-aided diagnostic tuberculosis diagnosis was preliminary tested in five primary health centers located in Lima, Peru. We recruited nurses (n = 7) and tuberculosis physicians (n = 5) from these health centers to participate in a field trial of an mHealth tool (eRx X-ray diagnostic app). From September 2018 to February 2019, the nurses uploaded images of chest X-rays using smartphones and the physicians reviewed those images on web-based platforms using tablets. Both completed weekly written feedback about their experience. Each nurse participated for a median duration of 12 weeks (interquartile range = 7.5-15.5), but image upload was only possible at a median of 58 percent (interquartile range = 35.1%-84.4%) of those weeks. Each physician participated for a median duration of 17 weeks (interquartile range = 12-17), but X-ray image review was only possible at a median of 52 percent (interquartile range = 49.7%-57.4%) of those weeks. Heavy workload was most frequently provided as the reason for missing data. Several infrastructural and technological challenges impaired the effective implementation of the mHealth tool, irrespective of its diagnostic accuracy.