Risk stratification after acute myocardial infarction by amplitude-frequency mapping of cyclic variation of heart rate.

Abstract

BackgroundBlunted cyclic variation of heart rate (CVHR), measured as a decrease in CVHR amplitude (Acv), predicts mortality risk after acute myocardial infarction (AMI). However, Acv also can be reduced in mild sleep apnea with mild O2 desaturation. We investigated whether Acv's predictive power for post‐AMI mortality could be improved by considering the effect of sleep apnea severity.MethodsIn 24‐hr ECG in 265,291 participants of the Allostatic State Mapping by Ambulatory ECG Repository project, sleep apnea severity was estimated by the frequency of CVHR (Fcv) measured by an automated algorithm for auto‐correlated wave detection by adaptive threshold (ACAT). The distribution of Acv on the Acv–Fcv relation map was modeled by percentile regression, and a function converting Acv into percentile value was developed. In the retrospective cohort of the Enhancing Recovery in Coronary Heart Disease (ENRICHD) study, consisting of 673 survivors and 44 non‐survivors after AMI, the mortality predictive power of percentile Acv calculated by the function was compared with that of unadjusted Acv.ResultsAmong the ALLSTAR ECG data, low Acv values appeared more likely when Fcv was low. The logistic regression analysis for mortality in the ENRICHD cohort showed c‐statistics of 0.667 (SE, 0.041), 0.817 (0.035), and 0.843 (0.030) for Fcv, unadjusted Acv, and the percentile Acv, respectively. Compared with unadjusted Acv, the percentile Acv showed a significant net reclassification improvement of 0.90 (95% CI, 0.51–1.42).ConclusionsThe predictive power of Acv for post‐AMI mortality is improved by considering its relation to sleep apnea severity estimated by Fcv.