Short and Long-term Survival Rates following Myocardial Infarction and its Predictive Factors: A Study Using National Registry Data

Abstract

Background: Coronary artery disease is the most common cause of death worldwide as well as in Iran. The present study was designed to predict short and long-term survival rates after the first episode of myocardial infarction (MI). Methods: The current research is a retrospective cohort study. The data were collected from the Myocardial Infarction Registry of Iran in a 12-month period leading to March 20, 2014. The variables analyzed included smoking status, past medical history of chronic heart disease, hypertension, diabetes, hyperlipidemia, signs and symptoms during an attack, post-MI complications during hospitalization, the occurrence of arrhythmias, the location of MI, and the place of residence. Survival rates and predictive factors were estimated by the Kaplan–Meier method, the log-rank test, and the Cox model. Results: Totally, 21 181 patients with the first MI were studied. There were 15 328 men (72.4%), and the mean age of the study population was 62.10±13.42 years. During a 1-year period following MI, 2479 patients (11.7%) died. Overall, the survival rates at 28 days, 6 months, and 1 year were estimated to be 0.95 (95% CI: 0.95 to 0.96), 0.90 (95% CI: 0.90 to 0.91), and 0.88 (95% CI: 0.88 to 0.89). After the confounding factors were controlled, history of chronic heart disease (p<0.001), hypertension (p<0.001), and diabetes (p<0.001) had a significant relationship with an increased risk of death and history of hyperlipidemia (p<0.001) and inferior wall MI (p<0.001) had a significant relationship with a decreased risk of death. Conclusion: The results of this study provide evidence for health policy-makers and physicians on the link between MI and its predictive factors.

Keywords

• Cox Regression
• Myocardial infarction
• Survival rate
• Hypertension