Characteristics of heart beat intervals and prediction of death

Objective To assess the value for improving risk stratification of measures, unadjusted and adjusted for heart rate, of heart rate variability (HRV) and heart rate turbulence (HRT) based on 2- to 24-h ambulatory electrocardiographic recordings; and to relate this to the decision to use an implantable cardiac defibrillator (ICD) and the attendant consequences on effectiveness and cost-effectiveness. Background Risk stratification for high risk or low risk of lethal ventricular arrhythmic events, and hence for a decision about defibrillator implant, most commonly utilizes the left ventricular ejection fraction (LVEF). Electrocardiographic (ECG) approaches include 24-h ambulatory ECG recordings, with counts of ventricular premature contractions (VPCs), measures of heart rate variability (HRV), and heart rate turbulence (HRT). HRT has two components: turbulence onset (TO) and turbulence slope (TS). Methods and results We evaluated the qualifying ambulatory ECG recordings from 744 patients in the active treatment arms of the Cardiac Arrhythmia Suppression Trial (CAST). Beat characteristics, VPC counts, normal-to-normal beat intervals, and time-domain measures of HRV and HRT were calculated. Tachograms were rescaled to a heart rate of 75 and the resulting “normalized” measures evaluated as risk predictors for death, compared to unnormalized measures. Measures based on 2-h ECGs were also evaluated as risk predictors. The most powerful univariate predictor of survival was the normalized turbulence slope. The best multivariate prediction model had six components: history of angina, hypertension, diabetes, and absence of post-myocardial infarction revascularization, the log of LVEF, normalized TS, HR, and an interaction term of HR and normalized TS. Gains in effectiveness from use of this model cost between $0 and $4000 per year of life saved. Conclusions Turbulence slope substantially exceeded other ECG-based measures in improving prediction of subsequent death in models which included LVEF, and other clinical parameters. Use of this model would improve the effectiveness and cost-effectiveness of the ICD.