Combined 3D left ventricular-arterial coupling and 3D left atrial-ventricular coupling indices could better predict MACE in young patients with STEMI

Abstract Background Left ventricular arterial coupling index (VAC) proved to be a key determinant of cardiovascular performance. Previous trials also emphasized the prognostic value of left atrial-ventricular coupling index (LACI) that was independently associated with cardiovascular death and all-cause mortality. Both indices have been associated with disease severity and adverse outcomes. Purpose We aimed to evaluate the prognostic role of 3D VAC, 3D LACI and their combination assessed by 3D echocardiography in a cohort of young patients with STEMI. Patients and methods In this prospective study we enrolled 76 young consecutive patients (under 50 years old) with STEMI treated by primary PCI who underwent both 2D and 3D echocardiography. 3D VAC was calculated as the ratio between arterial elastance (EA) and end-systolic left ventricular elastance (EES), based on a formula proposed by Chen. 3D LACI was determined as the ratio between 3D left atrial end-diastolic volume (minimal atrial volume) and 3D left ventricular end-diastolic volume. Patients were followed up for one year after STEMI and the primary endpoint was the occurrence of MACE defined as death from cardiovascular causes, heart failure requiring hospital admission, or repeat revascularisation. Results Out of 76 patients, 15.8% had an adverse event during the 12 months follow up period. We divided the patients in two groups according to the presence or absence of MACE. Patients with MACE had higher VAC (2.15±0.62 vs. 1.25±0.29%, p<0.0001) and higher LACI (25.1±7.17% vs. 18.3±6.58%, p=0.002). In ROC analysis VAC and LACI combined had the best AUC for MACE prediction (AUC 0.961, p<0.0001), followed by VAC (AUC 0.922, P<0.0001), and then, LACI (AUC 0.772, P<0.001). For each variable we determined a cut off value. A value over 1.7 for VAC and 23.83% for LACI can predict unfavourable outcome with 83.3% sensitivity and 97.1% specificity for VAC and 67% sensitivity and 80% specificity for LACI. In both univariate and multivariate COX regression analysis, both VAC and LACI remained independent predictors for MACE. Moreover, their combination proved to have better predictive value for adverse events compared to each taken separately. We divided the study population into 4 groups: Group 1: VAC < 1.7 and LACI < 23.83%. Group 2: VAC <1.7 and LACI > 23.83%. Group 3: VAC > 1.7 and LACI < 23.83% and Group 4: VAC > 1.7 and LACI >0.23.83%. Kaplan Meier analysis shows significant differences among groups (log rank χ2 = 35.48, p < 0.0001). Calculation of Kaplan-Meier curves for the four groups indicated that the combination of the VAC > 1.7 and LACI > 23.83% had the strongest predictive power for MACE. Conclusion In conclusion 3D VAC and 3D LACI combined are better at predicting adverse events than each variable taken separately and could be used for a more accurate risk stratification in young patients with STEMI.