Predictive measure for Ischemic Heart Disease among Workers in Jakarta, Indonesia

Abstract

Ischemic Heart Disease (IHD) is one of the leading causes of morbidity and mortality in many countries, including Indonesia. Therefore, cardiovascular risk-prediction models are required in clinical practice for early detection in high-risk populations, including the worker population. This study intends to develop a predictive risk measure for early detection of IHD incidences among employees in Jakarta, Indonesia. Source of data was the database of 4,100 medical check-up (MCU) results of employees and entrepreneurs in Jakarta and surrounding areas in January to October 2019. Multivariate analysis showed that being aged >40 years (p=0.000; OR=5.329 (95% CI 2.621-10.833)), having a history of dyspnea (p=0.000; OR=5.699 (95% CI 2.524-12.871)), smoking (p=0.048; OR=2.007 (95% CI 1.924-4.359)) and HDL<50 mg/dL (p=0.049; OR=1.811 (95% CI 1.099-3.281)) were all good predictors to detect IHD in the worker population. The combination of these predictors results with a cut-off point of 2.5, showed accuracy (79.2% sensitivity and 66.3% specificity). Workers who have a score >2.5 are at high risk of developing IHD in the future. This scoring system can be used by workers or companies to take early preventive measures.