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. © 2014 the authors.