Statistical analysis of the DIAMOND MI study by the multipole method

Alterations in heart rate variability are associated with abnormal myocardial perfusion

BACKGROUND

Abnormalities in the autonomic nervous system may occur in ischemic heart disease, but the mechanisms by which they are linked are not fully defined. The risk of cardiac events is increased during morning hours. Studying the contributions of autonomic mechanisms may yield insights into risk stratification and treatment. We hypothesize that autonomic dysfunction, measured by decreased heart rate variability (HRV), associates with abnormal stress myocardial perfusion imaging (MPI).

METHODS

We performed a cross-sectional study of the association between abnormal myocardial stress perfusion with HRV using 276 middle-aged veteran twins without known ischemic heart disease. The primary independent variable was cardiac autonomic regulation measured with 24-hour electrocardiogram (ECG) monitoring, using linear and non-linear (multipole density, or Dyx) HRV metrics. The primary outcome was abnormal perfusion (>5% affected myocardium) during adenosine stress on [13N]-ammonia myocardial perfusion imaging with positron emission tomography.

RESULTS

The mean (SD) age was 53 (3) years and 55 (20%) had abnormal perfusion. HRV (by Dyx) was reduced during morning hours in subjects with abnormal perfusion. At 7 AM, each standard deviation (SD) decrease in Dyx was associated a 4.8 (95% CI, 1.5 - 15.8) odds ratio (OR) for abnormal MPI. With Dyx < 2.0, the 7 AM OR for abnormal MPI was 11.8 (95% CI, 1.2 - 111.4).

CONCLUSIONS

Autonomic dysfunction, measured by non-linear HRV in the morning hours, was associated with an increased OR of abnormal MPI. These results suggest a potentially important role of ECG-based biomarkers in risk stratification for individuals with suspected ischemic heart disease.

Heart Rate Variability for Risk Assessment of Myocardial Ischemia in Patients Without Known Coronary Artery Disease: The HRV-DETECT (Heart Rate Variability for the Detection of Myocardial Ischemia) Study

Background

Detecting significant coronary artery disease (CAD) in the general population is complex and relies on combined assessment of traditional CAD risk factors and noninvasive testing. We hypothesized that a CAD‐specific heart rate variability (HRV) algorithm can be used to improve detection of subclinical or early ischemia in patients without known CAD.

Methods and Results

Between 2014 and 2018 we prospectively enrolled 1043 patients with low to intermediate pretest probability for CAD who were screened for myocardial ischemia in tertiary medical centers in the United States and Israel. Patients underwent 1‐hour Holter testing, with immediate HRV analysis using the HeartTrends DyDx algorithm, followed by exercise stress echocardiography (n=612) or exercise myocardial perfusion imaging (n=431). The threshold for low HRV was identified using receiver operating characteristic analysis based on sensitivity and specificity. The primary end point was the presence of myocardial ischemia detected by exercise stress echocardiography or exercise myocardial perfusion imaging. The mean age of patients was 61 years and 38% were women. Myocardial ischemia was detected in 66 (6.3%) patients. After adjustment for CAD risk factors and exercise stress testing results, low HRV was independently associated with a significant 2‐fold increased likelihood for myocardial ischemia (odds ratio, 2.00; 95% CI, 1.41–2.89 [P=0.01]). Adding HRV to traditional CAD risk factors significantly improved the pretest probability for myocardial ischemia.

Conclusions

Our data from a large prospective international clinical study show that short‐term HRV testing can be used as a novel digital‐health modality for enhanced risk assessment in low‐ to intermediate‐risk individuals without known CAD.

Clinical Trial Registration

URL: http://www.ClinicalTrials.gov. Unique identifiers: NCT01657006, NCT02201017).

Heart Rate Variability Density Analysis (Dyx) and Prediction of Long-Term Mortality after Acute Myocardial Infarction

AIMS

The density HRV parameter Dyx is a new heart rate variability (HRV) measure based on multipole analysis of the Poincaré plot obtained from RR interval time series, deriving information from both the time and frequency domain. Preliminary results have suggested that the parameter may provide new predictive information on mortality in survivors of acute myocardial infarction (MI). This study compares the prognostic significance of Dyx to that of traditional linear and nonlinear measures of HRV.

METHODS AND RESULTS

In the Nordic ICD pilot study, patients with an acute MI were screened with 2D echocardiography and 24-hour Holter recordings. The study was designed to assess the power of several HRV measures to predict mortality. Dyx was tested in a subset of 206 consecutive Danish patients with analysable Holter recordings. After a median follow-up of 8.5 years 70 patients had died. Of all traditional and multipole HRV parameters, reduced Dyx was the most powerful predictor of all-cause mortality (HR 2.4; CI 1.5 to 3.8; P < 0.001). After adjustment for known risk markers, such as age, diabetes, ejection fraction, previous MI and hypertension, Dyx remained an independent predictor of mortality (P = 0.02). Reduced Dyx also predicted cardiovascular death (P < 0.01) and sudden cardiovascular death (P = 0.05). In Kaplan-Meier analysis, Dyx significantly predicted mortality in patients both with and without impaired left ventricular systolic function (P < 0.0001).

CONCLUSION

The new nonlinear HRV measure Dyx is a promising independent predictor of mortality in a long-term follow-up study of patients surviving a MI, irrespectively of left ventricular systolic function.

Comparison of the usefulness of heart rate variability versus exercise stress testing for the detection of myocardial ischemia in patients without known coronary artery disease

Heart rate variability (HRV) has been shown to be attenuated in patients with coronary artery disease (CAD) and may, therefore, be possibly used for the early detection of myocardial ischemia. We aimed to evaluate the diagnostic yield of a novel short-term HRV algorithm for the detection of myocardial ischemia in subjects without known CAD. We prospectively enrolled 450 subjects without known CAD who were referred to tertiary medical centers for exercise stress testing (EST) with single-photon emission computed tomography myocardial perfusion imaging (MPI). All subjects underwent 1-hour Holter testing with subsequent HRV analysis before EST with MPI. The diagnostic yield of HRV analysis was compared with EST, using MPI as the gold standard for the noninvasive detection of myocardial ischemia. All subjects had intermediate pretest probability for CAD. Mean age was 62 years, 38% were women, 51% had hypertension, and 25% diabetes mellitus. HRV analysis showed superior sensitivity (77%) compared with standard EST (27%). After multivariate adjustment, HRV was independently associated with an 8.4-fold (p <0.001) increased likelihood for the detection of myocardial ischemia by MPI, whereas EST did not show a statistically significant association with a positive MPI (odds ratio 2.1; p = 0.12). Of subjects who were referred for subsequent coronary angiography, the respective sensitivities of HRV and EST for the detection of significant CAD were 73% versus 26%. Our data suggest that HRV can be used as an important noninvasive technique for the detection of myocardial ischemia in subjects without known CAD, providing superior sensitivity to conventional EST in this population.

Heart rate variability density analysis (Dyx) for identification of appropriate implantable cardioverter defibrillator recipients among elderly patients with acute myocardial infarction and left ventricular systolic dysfunction

AIMS

Dyx is a new heart rate variability (HRV) density analysis specifically designed to identify patients at high risk for malignant ventricular arrhythmias. The aim of this study was to test if Dyx can improve risk stratification for malignant ventricular tachyarrhythmias and to test if the previously identified cut-off can be reproduced.

METHODS AND RESULTS

This study included 248 patients from the CARISMA study with ejection fraction ≤40% after an acute myocardial infarction and an analysable 24 h Holter recording. All patients received an implantable cardiac monitor, which was used to diagnose the primary endpoint of near-fatal or fatal ventricular tachyarrhythmias likely preventable by an implantable cardioverter defibrillator (ICD), during a period of 2 years. A Dyx ≤ 1.96 was considered abnormal. The secondary endpoint was cardiovascular death. At enrolment 59 patients (24%) had a Dyx ≤ 1.96 and 20 experienced a primary endpoint. A Dyx ≤ 1.96 was associated with a significantly increased risk for malignant arrhythmias [hazards ratio (HR) = 4.36 (1.81-10.52), P = 0.001] and cardiovascular death [HR = 3.47 (1.38-8.74), P = 0.008]. Compared with important clinical risk parameters (age >70 years and QRS > 120 ms), Dyx ≤ 1.96 significantly added predictive value (P = 0.0066).

CONCLUSIONS

Dyx was a better predictor of ventricular tachyarrhythmias than the traditional measures of HRV and heart rate turbulence, particularly in the elderly. Dyx might be a useful tool for better selection of ICD candidates in the elderly population, since a normal Dyx in this group was associated with a very low risk for malignant ventricular arrhythmias.ClinicalTrials.gov Identifier NCT00145119.

Multipole analysis of heart rate variability as a predictor of imminent ventricular arrhythmias in ICD patients

BACKGROUND

Contemporary implantable cardiac defibrillators (ICD) enable storage of multiple, preepisode R-R recordings in patients who suffered from ventricular tachyarrhythmia (VTA). Timely prediction of VTA, using heart rate variability (HRV) analysis techniques, may facilitate the implementation of preventive and therapeutic strategies.

AIM

To evaluate the novel multipole method of the HRV analysis in prediction of imminent VTAs in ICD patients.

METHODS

We screened patients from the Biotronik HAWAI Registry (Heart Rate Analysis with Automated ICDs). A total of 28 patients from the HAWAI registries (phase I and II), having medical records, who had experienced documented, verified VTA during the 2-year follow-up, were included in our analysis. HRV during preepisode recordings of 4,500 R-R intervals were analyzed using the Dyx parameter and compared to HRV of similar length recordings from the same patients that were not followed by arrhythmia.

RESULTS

Our study population consisted mainly of men 25 of 28 (89%), average age of 64.8 ± 9.4 years, 92% with coronary artery disease. HRV during 64 preevent recordings (2.3 events per patient on average) was analyzed and compared with 60 control recordings. The multipole method of HRV analysis showed 50% sensitivity and 91.6% specificity for prediction of ventricular tachycardia/ventricular fibrillation in the study population, with 84.5% positive predictive value. No statistically significant correlation was found between various clinical parameters and the sensitivity of imminent VTA predetection in our patients.

CONCLUSION

The multipole method of HRV analysis emerges as a highly specific, possible predictor of imminent VTA, providing an early warning allowing to prepare for an arrhythmic episode.

Heart rate variability indices for very short-term (30 beat) analysis. Part 1: survey and toolbox

Heart rate variability (HRV) analysis over very short (<60 s) periods may be useful for monitoring dynamic changes in autonomic nervous system activity where steady-state conditions are not maintained (e.g. during drug administration, or the start or end of exercise). From the 1980s there has been a wealth of HRV indices produced in the quest for better measures of the change in parasympathetic and sympathetic activity. Many of the indices have been sparingly used and have not been investigated for application to short-term use. This study surveyed published methods of HRV analysis searching for indices that could be applied to very short time HRV analysis. The survey included measures of time domain, frequency domain, respiratory sinus arrhythmia, Poincaré plot, and heart rate characteristics. Indices were tested with short segments of archived data to remove those that produced invalid results, or were mathematically equivalent to, but less well known than other indices. The survey identified a comprehensive list of 115 indices that were subsequently coded and screened. Of these, 70 were unique and produced a finite number with 60 s data, so are included in the Toolbox. These indices require validation against physiological data before they can be applied to short-term HRV analysis of cardiac autonomic nervous system activity.