Myocardial global performance index as a predictor of in-hospital cardiac events in patients with first myocardial infarction.

摘要

OBJECTIVE: We sought to assess the ability of a Doppler index of global myocardial performance (MPI), measured at entry, to predict inhospital cardiac events in a series of patients with first acute myocardial infarction (AMI). METHODS: A complete 2-dimensional and Doppler echocardiographic examination was performed within 24 hours of arrival at the coronary care department in 96 patients (81 men and 15 women; mean age 58 +/- 9 years) with first AMI. Patients were divided a posteriori into 2 groups according to their inhospital course: group 1 comprised 75 patients with an uneventful course and group 2 comprised 21 patients with a complicated inhospital course (death, heart failure, arrhythmias, or post-AMI angina). RESULTS: There were no significant differences between the 2 groups with regard to history of hypertension, diabetes mellitus, hypercholesterolemia, site and size of infarction, and conventional parameters of diastolic function. However, patients with complications were significantly older (63 +/- 10 vs 55 +/- 8 years, P =.005) and had higher wall-motion score index and left ventricular end-systolic volume compared with patients without events (1.84 +/- 0.27 vs 1.52 +/- 0.30, P =.001; and 66 +/- 29 vs 47 +/- 21 mL, P =.009, respectively), whereas the ejection fraction was reduced (40 +/- 10% vs 52 +/- 10%, P =.0001). The mean value of the MPI was significantly higher in patients with cardiac events than in those without events (0.65 +/- 0.20 vs 0.43 +/- 0.16, P =.0001). A MPI >/= 0.47 showed a sensitivity of 90% and specificity of 68% for identifying patients with events, on the basis of the receiver operator curve. In a multivariable model, the MPI at admission remained independently predictive of inhospital cardiac events (odds ratio 15.6, 95% confidence interval 2.4-99, P =.003). CONCLUSION: These data suggest that in the acute phase of AMI, the MPI measured at entry may be useful to predict which patients are at high risk for inhospital cardiac events.