Linda M. Rolnitzky

Frequency domain measures of heart period variability and mortality after myocardial infarction.

BackgroundWe studied 715 patients 2 weeks after myocardial infarction to establish the associations between six frequency domain measures of heart period variability (HPV) and mortality during 4 years of follow-up. Methods and ResultsEach measure of HPV had a significant and at least moderately strong univariate association with all-cause mortality, cardiac death, and arrhythmic death. Power in the lower-frequency bands–ultra low frequency (ULF) and very low frequency (VLF) power–had stronger associations with all three mortality end points than power in the higher-frequency bands-low frequency (LF) and high frequency (HF) power. The 24-hour total power also had a significant and strong association with all three mortality end points. VLF power was the only variable that was more strongly associated with arrhythmic death than with cardiac death or all-cause mortality. In multivariate Cox regression models using a step-up approach to evaluate the independent associations between frequency domain measures of heart period variability and death of all causes, ULF power was selected first (i.e., was the single component with the strongest association). Adding VLF or LF power to the Cox regression model significantly improved the prediction of outcome. With both ULF and VLF power in the Cox regression model, the addition of the other two components, LF and HF power, singly or together, did not significantly improve the prediction of all-cause mortality. We explored the relation between the heart period variability measures and all-cause mortality, cardiac death, and arrhythmic death before and after adjusting for five previously established postinfarction risk predictors: age, New York Heart Association functional class, rales in the coronary care unit, left ventricular ejection fraction, and ventricular arrhythmias detected in a 24-hour Holter ECG recording ConclusionsAfter adjustment for the five risk predictors, the association between mortality and total, ULF, and VLF power remained significant and strong, whereas LF and HF power were only moderately strongly associated with mortality. The tendency for VLF power to be more strongly associated with arrhythmic death than with all-cause or cardiac death was still evident after adjusting for the five covariates. Adding measures of HPV to previously known predictors of risk after myocardial infarction identifies small subgroups with a 2.5-year mortality risk of approximately 50%.

The relationships among ventricular arrhythmias, left ventricular dysfunction, and mortality in the 2 years after myocardial infarction.

We examined the relationships among ventricular arrhythmias, left ventricular dysfunction, and mortality after the occurrence of myocardial infarction in 766 patients who enrolled in a nine-hospital study and underwent two special tests. Frequency and repetitiveness of ventricular premature depolarizations (VPDs) were determined by computer analysis of predischarge 24 hr electrocardiographic recordings. The left ventricular ejection fraction (LVEF) was determined by radionuclide ventriculography and dichotomized at its optimal value of 30%. Frequency of VPDs was divided into three categories: (1) less than one per hour, (2) one to 2.9 per hour, and (3) three or more per hour. Repetitiveness of VPDs was also divided into three categories: (1) no repetitive VPDs, (2) paired VPDs, and (3) VPD runs. These variables were related, one at a time and jointly, to total mortality and to deaths caused by arrhythmias. The hazard ratios for dying in the higher or highest risk stratum vs the lower or lowest stratum for each variable (adjusted for the effects of the others) were: LVEF below 30%, 3.5; VPD runs, 1.9; and VPD frequency of three or more per hour, 2.0. There were no significant interactions among the three variables with respect to effects on the risk of mortality. There was a suggestion of an interaction between each risk variable and time after infarction. LVEF below 30% was a better predictor of early mortality (less than 6 months) and the presence of ventricular arrhythmias was a better predictor of late mortality (after 6 months).(ABSTRACT TRUNCATED AT 250 WORDS)

Heart-rate turbulence after ventricular premature beats as a predictor of mortality after acute myocardial infarction.

BACKGROUND Identification of high-risk patients after acute myocardial infarction is essential for successful prophylactic therapy. The predictive accuracy of currently used risk predictors is modest even when several factors are combined. Thus, establishment of a new powerful method for risk prediction independent of the available stratifiers is of considerable practical value. METHODS The study investigated fluctuations of sinus-rhythm cycle length after a single ventricular premature beat recorded in Holter electrocardiograms, and characterised the fluctuations (termed heart-rate turbulence) by two numerical parameters, termed turbulence onset and slope. The method was developed on a population of 100 patients with coronary heart disease and blindly applied to the population of the Multicentre Post-Infarction Program (MPIP; 577 survivors of acute infarction, 75 deaths during a median follow-up of 22 months) and to the placebo population of the European Myocardial Amiodarone Trial (EMIAT; 614 survivors of acute myocardial infarction, 87 deaths during median follow-up of 21 months). Multivariate risk stratification was done with the new parameters and conventional risk factors. FINDINGS One of the new parameters (turbulence slope) was the most powerful stratifier of follow-up mortality in EMIAT and the second most powerful stratifier in MPIP: MPIP risk ratio 3.5 (95% CI 2.2-5.5, p<0.0001), EMIAT risk ratio 2.7 (1.8-4.2, p<0.0001). In the multivariate analysis, low left-ventricular ejection fraction and turbulence slope were the only independent variables for mortality prediction in MPIP (p<0.001), whereas in EMIAT, five variables were independent mortality predictors: abnormal turbulence onset, abnormal turbulence slope, history of previous infarction, low left-ventricular ejection fraction, and high mean heart rate (p<0.001). In both MPIP and EMIAT, the combination of abnormal onset and slope was the most powerful multivariate risk stratifier: MPIP risk ratio 3.2 (1.7-6.0, p<0.0001), EMIAT risk ratio 3.2 (1.8-5.6, p<0.0001). INTERPRETATION The absence of the heart rate turbulence after ventricular premature beats is a very potent postinfarction risk stratifier that is independent of other known risk factors and which is stronger than other presently available risk predictors.

The ability of several short-term measures of RR variability to predict mortality after myocardial infarction.

BACKGROUND We studied 715 patients 2 weeks after myocardial infarction to test the hypothesis that short-term power spectral measures of RR variability (calculated from 2 to 15 minutes of normal RR interval data) will predict all-cause mortality or arrhythmic death. METHODS AND RESULTS We performed power spectral analyses on the entire 24-hour RR interval time series. To compare with the 24-hour analyses, we selected short segments of ECG recordings from two time periods for analysis: 8 AM to 4 PM and midnight to 5 AM. The former corresponds to the time interval during which short-term measures of RR variability would most likely be obtained. The latter, during sleep, represent a period of increased vagal tone, which may simulate the conditions that exist when patients have a signal-averaged ECG recorded, ie, lying quietly in the laboratory. Four frequency domain measures were calculated from spectral analysis of heart period data over a 24-hour interval. We computed the 24-hour power spectral density and calculated the power within three frequency bands: (1) 0.0033 to < 0.04 Hz, very low frequency power, (2) 0.04 to < 0.15 Hz, low frequency power, and (3) 0.15 to 0.40 Hz, high frequency power. In addition, we calculated the ratio of low to high frequency power. These measures were calculated for 15-, 10-, 5-, and 2-minute segments during the day and at night. Mean power spectral values from short periods during the day and night were similar to 24-hour values, and the correlations between short segment values and 24-hour values were strong (many correlations were > or = 0.75). Using the optimal cutpoints determined previously for the 24-hour power spectral values, we compared the survival experience of patients with low values for RR variability in short segments of ECG recordings to those with high values. We found that power spectral measures of RR variability were excellent predictors of all-cause, cardiac, and arrhythmic mortality and sudden death. Patients with low values were 2 to 4 times as likely to die over an average follow-up of 31 months as were patients with high values. The power spectral measures of RR variability did not predict arrhythmic or sudden deaths substantially better than all-cause mortality. CONCLUSIONS Power spectral measures of RR variability calculated from short (2 to 15 minutes) ECG recordings are remarkably similar to those calculated over 24 hours. The power spectral measures of RR variability are excellent predictors of all-cause mortality and sudden cardiac death.

RR Variability in Healthy, Middle-Aged Persons Compared With Patients With Chronic Coronary Heart Disease or Recent Acute Myocardial Infarction

BACKGROUND The purpose of this investigation was to establish normal values of RR variability for middle-aged persons and compare them with values found in patients early and late after myocardial infarction. We hypothesized that presence or absence of coronary heart disease, age, and sex (in this order of importance) are all correlated with RR variability. METHODS AND RESULTS To determine normal values for RR variability in middle-aged persons, we recruited a sample of 274 healthy persons 40 to 69 years old. To determine the effect of acute myocardial infarction RR variability, we compared measurements of RR variability made 2 weeks after myocardial infarction (n = 684) with measurements made on age- and sex-matched middle-aged subjects with no history of cardiovascular disease (n = 274). To determine the extent of recovery of RR variability after myocardial infarction, we compared measurements of RR variability made in the group of healthy middle-aged persons with measurements made in 278 patients studied 1 year after myocardial infarction. We performed power spectral analyses on continuous 24-hour ECG recordings to quantify total power, ultralow-frequency (ULF) power, very-low-frequency (VLF) power, low-frequency (LF) power, high-frequency (HF) power, and the ratio of LF to HF (LF/HF) power. Time-domain measures also were calculated. All measures of RR variability were significantly and substantially lower in patients with chronic or subacute coronary heart disease than in healthy subjects. The difference from normal values was much greater 2 weeks after myocardial infarction than 1 year after infarction, but the fractional distribution of total power into its four component bands was similar for the three groups. In healthy subjects, ULF power did not change significantly with age; VLF, LF, and HF power decreased significantly as age increased. Patients with chronic coronary heart disease showed little relation between power spectral measures of RR variability and age. Patients with a recent myocardial infarction showed a strong inverse relation between VLF, LF, and HF power and age and a weak inverse relation between ULF power and age. ULF power best separates the healthy group from either of the two coronary heart disease groups. Differences in RR variability between men and women were small and inconsistent among the three groups. CONCLUSIONS All measures of RR variability were significantly and substantially higher in healthy subjects than in patients with chronic or subacute coronary heart disease. The difference between healthy middle-aged persons and those with coronary heart disease was much greater 2 weeks after myocardial infarction than 1 year after infarction, but the fractional distribution of total power into its four component bands was similar for the healthy group and the two coronary heart disease groups. Values of RR variability previously reported to predict death in patients with known chronic coronary heart disease are rarely (approximately 1%) found in healthy middle-aged individuals. Thus, when measures of RR variability are used to screen groups of middle-aged persons to identify individuals who have substantial risk of coronary deaths or arrhythmic events, misclassification of healthy middle-aged persons should be rare.

Correlations among time and frequency domain measures of heart period variability two weeks after acute myocardial infarction

Seven hundred fifteen participants from a multicenter natural history study of acute myocardial infarction were studied (1) to determine the correlations among time and frequency domain measures of heart period variability, (2) to determine the correlations between the measures of heart period variability and previously established post-infarction risk predictors, and (3) to determine the predictive value of time domain measures of heart period variability for death during follow-up after acute myocardial infarction. Twenty-four hour electrocardiographic recordings obtained 11 +/- 3 days after acute myocardial infarction were analyzed and 11 measures of heart period variability were computed. Each of 4 bands in the heart period power spectrum had 1 or 2 corresponding variables in the time domain that correlated with it so strongly (r greater than or equal to 0.90) that the variables were essentially equivalent: ultra low frequency power with SDNN* and SDANN index,* very low frequency power and low-frequency power with SDNN index,* and high-frequency power with r-MSSD* and pNN50.* As expected from theoretical considerations, SDNN and the square root of total power were almost perfectly correlated. Correlations between the time and frequency domain measures of heart period variability and previously identified postinfarction risk predictors, e.g., left ventricular ejection fraction and ventricular arrhythmias, are remarkably weak. Time domain measures of heart period variability, especially those that measure ultra low or low-frequency power, are strongly and independently associated with death during follow-up. * Defined in Table II.

Power Law Behavior of RR-Interval Variability in Healthy Middle-Aged Persons, Patients With Recent Acute Myocardial Infarction, and Patients With Heart Transplants

BACKGROUND The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

Stability over time of variables measuring heart rate variability in normal subjects

Abstract Both time and frequency domain measures of heart rate (HR) variability have been used to assess autonomic tone in a variety of clinical conditions. Few studies in normal subjects have been performed to determine the stability of HR variability over time, or the correlation between and within time and frequency domain measures of HR variability. Fourteen normal subjects aged 20 to 55 years were studied with baseline and placebo 24-hour ambulatory electrocardiograms performed 3 to 65 days apart to assess the reproducibility of the following time domain measures of cycle length variability: the standard deviation of all normal cycle intervals; mean normal cycle interval; mean day normal cycle interval; night/day difference in mean normal cycle interval; root-mean-square successive cycle interval difference; percentage of differences between adjacent normal cycle length intervals that are >50 ms computed over the entire 24-hour electrocardiographic recording (proportion of adjacent intervals >50 ms); and the frequency domain measures of high (0.15 to 40 Hz), low (0.003 to 0.15) and total (0.003 to 0.40) power. The mean and standard deviations of these measures were virtually identical between placebo and baseline measurements and within the studied time range. Variables strongly dependent on vagal tone (high-frequency, low-frequency and total power, root-mean-square successive difference, and percentage of differences between adjacent normal cycle intervals >50 ms computed over the entire 24-hour electrocardiographic recording) were highly correlated (r > 0.8). It is concluded that measures of HR variability are stable over short periods of time. Certain time and frequency domain variables are highly correlated and may serve as surrogates for each other, and no placebo effect on these variables is evident.

Prevalence, characteristics and significance of ventricular tachycardia (three or more complexes) detected with ambulatory electrocardiographic recording in the late hospital phase of acute myocardial infarction

A 24 hour electrocardiographic recording was performed before hospital discharge in 430 patients who survived the cardiac care unit phase of acute myocardial infarction. Fifty patients (11.6 percent) had ventricular tachycardia, that is, three or more consecutive ventricular complexes. In 25 (50 percent) of these 50 patients, there was only one episode of ventricular tachycardia and, in 15 patients (30 percent), the longest run of ventricular tachycardia was only three consecutive ventricular premature depolarizations. The average rate of tachycardia was 119/min. Tachycardia rarely started with R on T ventricular premature complexes (4 of 1,370 episodes in 50 patients). There was no difference between the groups with and without ventricular tachycardia with respect to age and sex, but the patients with tachycardia had a significantly greater prevalence of previous myocardial infarction, left ventricular failure in the cardiac care unit, atrial fibrillation, ventricular tachycardia or ventricular fibrillation in the cardiac care unit and significantly more frequent use of digitalis and diuretic and antiarrhythmic drugs at the time of hospital discharge. The group with tachycardia had a 38.0 percent 1 year mortality rate compared with the rate of 11.6 percent in the group without tachycardia. Ventricular tachycardia had a strong association with 1 year mortality (odds ratio = 4.7). Although ventricular tachycardia had a significantly association with many other postinfarction risk factors, it was still significantly associated with the 1 year mortality (p less than 0.05) when other important risk variables were controlled statistically using a multiple logistic regression model. The 36 month cumulative mortality rate was 54.0 percent in the group with ventricular tachycardia compared with 19.4 percent in the group without tachycardia.

Effect of atenolol and diltiazem on heart period variability in normal persons

Several time and frequency domain measures of heart period variability are reduced 1 to 2 weeks after myocardial infarction, and a reduced standard deviation of normal RR intervals over a 24 h period (SDNN) is associated with increased mortality. The predictive accuracy of heart period variability may be reduced by drugs used to treat patients after myocardial infarction. Accordingly, a randomized, three period, placebo-controlled, crossover (Latin square) design was used to determine the effect of atenolol and diltiazem on time and frequency measures of heart period variability calculated from 24 h continuous electrocardiographic recordings during treatment with atenolol, diltiazem and placebo in 18 normal volunteers. During atenolol treatment, the 24 h average normal RR (NN) interval increased 24% (p less than 0.001). The three measures of tonic vagal activity were significantly increased (p less than 0.001) during atenolol treatment: percent of successive normal RR intervals greater than 50 ms = 69%, root mean square successive difference of normal RR intervals = 61% and high frequency power in the heart period power spectrum = 84%. Low frequency power also increased 45% (p less than 0.01), indicating that this variable also is an indicator of tonic vagal activity over 24 h. Diltiazem had no significant effect on the 24 h average NN interval or on any measure of heart period variability. The decreased mortality rate after myocardial infarction associated with beta-adrenergic blocker but not calcium channel blocker therapy may be attributed in part to an increase in vagal tone caused by beta-blockers.