ECG Morphological Variability in Beat Space for Risk Stratification After Acute Coronary Syndrome

Background Identification of patients who are at high risk of adverse cardiovascular events after an acute coronary syndrome ( ACS ) remains a major challenge in clinical cardiology. We hypothesized that quantifying variability in electrocardiogram ( ECG) morphology may improve risk stratification post‐ ACS . Methods and Results We developed a new metric to quantify beat‐to‐beat morphologic changes in the ECG : morphologic variability in beat space ( MVB ), and compared our metric to published ECG metrics (heart rate variability [ HRV ], deceleration capacity [ DC ], T‐wave alternans, heart rate turbulence, and severe autonomic failure). We tested the ability of these metrics to identify patients at high risk of cardiovascular death ( CVD ) using 1082 patients (1‐year CVD rate, 4.5%) from the MERLIN ‐ TIMI 36 (Metabolic Efficiency with Ranolazine for Less Ischemia in Non‐ ST ‐Elevation Acute Coronary Syndrome—Thrombolysis in Myocardial Infarction 36) clinical trial. DC , HRV/low frequency–high frequency, and MVB were all associated with CVD (hazard ratios [HRs] from 2.1 to 2.3 [ P <0.05 for all] after adjusting for the TIMI risk score [ TRS ], left ventricular ejection fraction [ LVEF ], and B‐type natriuretic peptide [ BNP ]). In a cohort with low‐to‐moderate TRS (N=864; 1‐year CVD rate, 2.7%), only MVB was significantly associated with CVD (HR, 3.0; P =0.01, after adjusting for LVEF and BNP ). Conclusions ECG morphological variability in beat space contains prognostic information complementary to the clinical variables, LVEF and BNP, in patients with low‐to‐moderate TRS . ECG metrics could help to risk stratify patients who might not otherwise be considered at high risk of CVD post‐ ACS .