Methods: A total of 7180 STEMI male patients from the National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry for the years 2006-2013 were enrolled. In the development of univariate and multivariate logistic regression model for the STEMI patients, Bayesian Markov Chain Monte Carlo (MCMC) simulation approach was applied. The performance of the model was assessed through convergence diagnostics, overall model fit, model calibration and discrimination.

Results: A set of six risk factors for cardiovascular death among STEMI male patients were identified from the Bayesian multivariate logistic model namely age, diabetes mellitus, family history of CVD, Killip class, chronic lung disease and renal disease respectively. Overall model fit, model calibration and discrimination were considered good for the proposed model.

OBJECTIVES: To identify the risk factors associated with mortality for each gender and compare differences, if any, among ST-elevation myocardial infarction (STEMI) patients.

DESIGN: Retrospective analysis.

SETTINGS: Hospitals across Malaysia.

PATIENTS AND METHODS: We analyzed data on all STEMI patients in the National Cardiovascular Database-Acute coronary syndrome (NCVD-ACS) registry for the years 2006 to 2013 (8 years). We collected demographic and risk factor data (diabetes mellitus, hypertension, smoking status, dyslipidaemia and family history of CAD). Significant variables from the univariate analysis were further analysed by a multivariate logistic analysis to identify risk factors and compare by gender.

MAIN OUTCOME MEASURES: Differential risk factors for each gender.

RESULTS: For the 19484 patients included in the analysis, the mortality rate over the 8 years was significantly higher in females (15.4%) than males (7.5%) (P < .001). The univariate analysis showed that the majority of male patients < 65 years while females were >=65 years. The most prevalent risk factors for male patients were smoking (79.3%), followed by hypertension (54.9%) and diabetes mellitus (40.4%), while the most prevalent risk factors for female patients were hypertension (76.8%), followed by diabetes mellitus (60%) and dyslipidaemia (38.1%). The final model for male STEMI patients had seven significant variables: Killip class, age group, hypertension, renal disease, percutaneous coronary intervention and family history of CVD. For female STEMI patients, the significant variables were renal disease, smoking status, Killip class and age group.

CONCLUSION: Gender differences existed in the baseline characteristics, associated risk factors, clinical presentation and outcomes among STEMI patients. For STEMI females, the rate of mortality was twice that of males. Once they reach menopausal age, when there is less protection from the estrogen hormone and there are other risk factors, menopausal females are at increased risk for STEMI.