ECG morphological variability in beat space for risk stratification after acute coronary syndrome.

ABSTRACT:

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

SUBMITTER: Liu Y 

PROVIDER: S-EPMC4309066 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature