Association between serum osteocalcin and atherosclerosis in Type-2 diabetes mellitus: a cross-sectional study.

BACKGROUND: The past few decades have seen a marked increase in the macrovascular complications of Type-2 diabetes mellitus (T2DM) such as coronary heart disease, peripheral arterial disease, and cerebrovascular disease. This has been predominantly attributed to the increased atherosclerosis in these patients. Atherosclerosis usually remains an asymptomatic condition and this poses a significant challenge in its early diagnosis and timely intervention. Hence, there is an immediate need for exploring novel tools to aid in the early detection of atherosclerosis, especially in T2DM patients. Osteocalcin (OC), synthesized by osteoblasts, is a protein hormone found in the skeletal system. This protein is considered as a marker for bone density and in recent times has been gaining interest due to its protective role in cerebrovascular diseases(CVD). METHODS: We conducted a cross-sectional study and evaluated the association between serum OC levels and atherosclerosis in 113 T2DM patients. Carotid intima-media thickness (CC-IMT) was used as an estimate of atherosclerosis and patients were divided into two groups (CC-IMT < 0.9 and ≥ 0.9). Correlation of serum OC levels and glycemic parameters and lipid profiles were studied and compared between both groups. RESULTS: There is a significant negative correlation between the CC-IMT estimates and serum OC levels. CC-IMT also has a significant association with other biochemical parameters such as fasting blood sugar, glycated hemoglobin and high-density lipoprotein. CONCLUSION: Although the independent association of serum OC could not be established in the T2DM patient population, overall, the results favor low serum OC as a prognostic marker for atherosclerosis.

Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India.

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 microbiologically-confirmed 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.