Incidence and predictors of perioperative myocardial infarction in patients undergoing non-cardiac surgery in a tertiary care hospital

Abstract

BackgroundThe stress in the perioperative period is compounded by unpredictable and un-physiological changes in sympathetic tone, cardiovascular performance, coagulation and inflammatory responses, all of which in turn lead to alterations in plaque morphology predisposing to perioperative myocardial infarction (PMI). PMI has a considerable morbidity and mortality in patients undergoing not only high risk surgery, but also even with minor surgical interventions. ObjectiveTo study the incidence of PMI and its predictors in patients undergoing non-cardiac surgery in a tertiary care hospital. Materials and methodsPatients undergoing non-cardiac surgery were included in this prospective single-center observational study. The revised cardiac risk index (RCRI) was used for risk stratification. ECG monitoring was done for all patients. For patients suggestive of acute myocardial ischemia, echocardiography and serum troponin were evaluated. The patient was labeled as having a PMI if there was raised troponin level along with any one evidence of myocardial ischemia (symptoms, ECG changes or imaging results) and in these patients the factors predisposing to PMI were evaluated. All patients in the study were followed up to 30 days. ResultsOf the 525 patients analyzed, 33 patients (6.28%) had a PMI. Twelve out of the 33 (36.36%) PMI patients died within 30 days following surgery. Patients undergoing high risk surgery, smokers and patients with a past history of ischemic heart disease (IHD) were found to be at higher risk of developing PMI. The ASA physical status classification and the RCRI proved to be good predictors of PMI. Most of the PMI events (72.7%) occurred within 48 hours of surgery. ConclusionPMI is a dreaded complication associated with a very high mortality. High risk surgery, smoking and past history of ischemic heart disease were independent predictors of PMI. The RCRI is a useful tool in pre-operative risk stratification of patients.