Though more importance is being given to HIV-TB coinfection, we cannot overlook DM, which showed a significantly higher prevalence in pulmonary TB patients compared to HIV. The rising prevalence of DM in high TB burden countries may adversely affect TB control.

Summaryobjective To determine the frequency of underlying risk factors and the socio-economic impact based on occupation in the development of tuberculosis. results Diabetes mellitus (DM) (30.9%) was the most prevalent condition and significantly more common than other risk factors like smoking (16.9%), alcoholism (12.6%), HIV (10.6%), malignancy (5.8%), chronic liver diseases (3.9%), history of contact with TB (3.4%), chronic corticosteroid therapy (2.9%), chronic kidney diseases and malnourishment (1.5%). There were 82 patients (39.6%) with no underlying risk factor. Men (M:F = 3.7:1) and patients older than 40 years had a higher incidence of co-existing conditions. PTB was significantly more common in blue-collar (44%) and white-collar (27.1%) workers than household workers (12.1%), students (10.6%) and retired ⁄ unemployed people (6.3%).conclusion Pulmonary tuberculosis had a significant impact and predominated in male patients coexisting with DM. Patients with DM and suggestive pulmonary symptoms should be screened for tuberculosis. More stringent health education and awareness programme should be implemented at the grass root level. Although more focus is being given on TB-HIV coinfection as a major concern for public health, there are other underlying risk factors which compromise the immune status. Diabetes mellitus (DM) widely impairs neutrophil and macrophage functions (Ljubic et al. 2004) and thus can be a major aggravating risk factor for TB.

In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active pulmonary tuberculosis (ptB) screening when interpreted by human readers. However, they are challenging to scale due to hardware costs and the dearth of professionals available to interpret cXR in low-resource, high ptB burden settings. Recently, several computer-aided detection (cAD) programs have been developed to facilitate automated cXR interpretation. We conducted a retrospective case-control study to assess the diagnostic accuracy of a cAD software (qXR, Qure.ai, Mumbai, india) using microbiologically-confirmed PTB as the reference standard. To assess overall accuracy of qXR, receiver operating characteristic (Roc) analysis was used to determine the area under the curve (AUc), along with 95% confidence intervals (CI). Kappa coefficients, and associated 95% CI, were used to investigate inter-rater reliability of the radiologists for detection of specific chest abnormalities. In total, 317 cases and 612 controls were included in the analysis. The AUC for qXR for the detection of microbiologicallyconfirmed PTB was 0.81 (95% CI: 0.78, 0.84). Using the threshold that maximized sensitivity and specificity of qXR simultaneously, the software achieved a sensitivity and specificity of 71% (95% CI: 66%, 76%) and 80% (95% CI: 77%, 83%), respectively. The sensitivity and specificity of radiologists for the detection of microbiologically-confirmed PTB was 56% (95% CI: 50%, 62%) and 80% (95% CI: 77%, 83%), respectively. For detection of key PTB-related abnormalities 'pleural effusion' and 'cavity', qXR achieved an AUC of 0.94 (95% CI: 0.92, 0.96) and 0.84 (95% CI: 0.82, 0.87), respectively. For the other abnormalities, the AUC ranged from 0.75 (95% CI: 0.70, 0.80) to 0.94 (95% CI: 0.91, 0.96). The controls had a high prevalence of other lung diseases which can cause radiological manifestations similar to PTB (e.g., 26% had pneumonia, 15% had lung malignancy, etc.). In a tertiary hospital in india, qXR demonstrated moderate sensitivity and specificity for the detection of PTB. There is likely a larger role for cAD software as a triage test for ptB at the primary care level in settings where access to radiologists in limited. Larger prospective studies that can better assess heterogeneity in important subgroups are needed.