Use of serial changes in biomarkers vs. baseline levels to predict left ventricular remodelling after STEMI

Abstract

Aims: Cellular communication network factor 1 (CCN1) is an independent predictor of MACE after ACS and elevated levels correlated with infarct size after STEMI. We compared the prognostic accuracy of baseline levels of CCN1, NT-proBNP, hsTnT, and ST2 and changes in levels over time to predict the development of structural and functional alterations typical of LV remodelling. Methods: Serial 3-T cMRI scans were performed to determine LVEF, LVEDV, LVESV, infarct size, and relative infarct size, which were correlated with serial measurements of the four biomarkers. The prognostic significance of these biomarkers was assessed by multiple logistic regression analysis by examining their performance in predicting dichotomized cardiac MRI values 12 months after STEMI based on their median. For each biomarker three models were created using baseline (BL), the Δ value (BL to 6 months), and the two values together as predictors. All models were adjusted for age and renal function. Receiver operator curves were plotted with area under the curve (AUC) to discriminate the prognostic accuracy of individual biomarkers for MRI-based structural or functional changes. Results: A total of 44 predominantly male patients (88.6%) from the ETiCS (Etiology, Titre-Course, and Survival) study were identified at a mean age of 55.5 ± 11.5 (SD) years treated by successful percutaneous coronary intervention (97.7%) at a rate of 95.5% stent implantation within a median pain-to-balloon time of 260 min (IQR 124–591). Biomarkers hsTnT and ST2 were identified as strong predictors (AUC > 0.7) of LVEDV and LVEF. BL measurement to predict LVEF [hsTnT: AUC 0.870 (95% CI: 0.756–0.983), ST2: AUC 0.763 (95% CI: 0.615–0.911)] and the Δ value BL-6M [hsTnT: AUC 0.870 (95% CI: 0.756–0.983), ST2: AUC 0.809 (95% CI: 0.679–0.939)] showed a high prognostic value without a significant difference for the comparison of the BL model vs. the Δ-value model (BL-6M) for hsTnT (P = 1) and ST2 (P = 0.304). The combined model that included baseline and Δ value as predictors was not able to improve the ability to predict LVEF [hsTnT: AUC 0.891 (0.791–0.992), P = 0.444; ST2: AUC 0.778 (0.638–0.918), P = 0.799]. Baseline levels of CCN1 were closely associated with LVEDV at 12 months [AUC 0.708 (95% CI: 0.551–0.865)] and infarct size [AUC 0.703 (95% CI: 0.534–0.872)]. Conclusions: Baseline biomarker levels of hsTnT and ST2 were the strongest predictors of LVEF and LVEDV at 12 months after STEMI. The association of CCN1 with LVEDV and infarct size warrants further study into the underlying pathophysiology of this novel biomarker.