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

Abstract Background Blunted 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. Methods In 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. Results Among 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). Conclusions The predictive power of Acv for post‐AMI mortality is improved by considering its relation to sleep apnea severity estimated by Fcv.

To test this hypothesis, we conducted this study in three steps,

| Step 1: Analysis of polysomnographic data
To investigate the correlates of Acv, the associations between Acv, sleepapneaseverity,andO 2 desaturationwereexaminedusingadatabase of all-night polysomnograms in 862 participants. The study use of this database has been approved by the institutional review board of the Fujita Health University, Toyoake, Aichi, Japan (No. 09-008), and by the Ethics Review Committee of the Nagoya City University GraduateSchoolofMedicalSciences,Nagoya,Japan(No.390).

| Step 3: Application to post-AMI cohort data
Toexaminewhethertheconversiontopercentilevaluesimprovesthe mortalitypredictivepowerofAcv,weusedretrospectivecohortdata from a subset of patients from the Enhancing Recovery in Coronary HeartDisease(ENRICHD)study (Berkmanetal.,2003).Thedatacon-sistedofpatientswhohadanAMI,wereatelevatedpsychologicalrisk for adverse events because they were either depressed or had low social

| Measurement of Acv
ForallECGdatafromthethreedatabases,Acvwasmeasuredbythe methodofsignalaveragingaccordingtoourpreviouswork (Hayano etal.,2017).Briefly,foralldipsmeetingtherelaxedCVHRcriteria (excluding criterion 4 from the criteria for Fcv), N-N interval segments around the nadir point of the dips were aligned at the nadir points and averaged. Acv was measured as the dip depth of the signal-averagedintervalcurve,thatis,theverticaldistancefromthe nadirtothelineconnectingthelocalmaximaonbothsidesofthe dip. Because Acv was calculated for CVHR defined by the relaxed criteria,AcvcouldbecomputedeveninthecasesofzeroFcv.

| Statistical analysis
TheSASprogrampackage(SASInstitute)wasusedfortheseanalyses. The standard error of c-statistics was estimated by the bootstrap method with 1,000 random samplings. The significance of improvement in predictive performance was evaluated by the 95% confidenceintervalofcontinuousNRIthatwasalsoestimatedbythe bootstrap method with 1,000 random samplings. For all statistical analysis,p < .05 was considered significant.

AbbreviationsareexplainedinthefootnotetoTable1.
We therefore used percentile regression functions to characterize

CO N FLI C T O F I NTE R E S T S
The authors have no conflict of interest to declare.

Et h i c s
The study use of the all-night polysomnogram database has been approved by the institutional review board of the Fujita Health University,Toyoake,Aichi,Japan(No.09-008),andbytheEthics

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.