Richard C. Steinman

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 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.

Microvolt T-Wave Alternans Distinguishes Between Patients Likely and Patients Not Likely to Benefit From Implanted Cardiac Defibrillator Therapy A Solution to the Multicenter Automatic Defibrillator Implantation Trial (MADIT) II Conundrum

Background—In 2003, the Centers for Medicaid and Medicare Services recommended QRS duration as a means to identify MADIT II–like patients suitable for implanted cardiac defibrillator (ICD) therapy. We compared the ability of microvolt T-wave alternans and QRS duration to identify groups at high and low risk of dying among heart failure patients who met MADIT II criteria for ICD prophylaxis. Methods and Results—Patients with MADIT II characteristics and sinus rhythm had a microvolt T-wave alternans exercise test and a 12-lead ECG. Our primary end point was 2-year all-cause mortality. Of 177 MADIT II–like patients, 32% had a QRS duration >120 ms, and 68% had an abnormal (positive or indeterminate) microvolt T-wave alternans test. During an average follow-up of 20±6 months, 20 patients died. We compared patients with an abnormal microvolt T-wave alternans test to those with a normal (negative) test, and patients with a QRS >120 ms with those with a QRS ≤120 ms; the hazard ratios for 2-year mortality were 4.8 (P=0.020) and 1.5 (P=0.367), respectively. The actuarial mortality rate was substantially lower among patients with a normal microvolt T-wave alternans test (3.8%; 95% confidence interval: 0, 9.0) than the mortality rate in patients with a narrow QRS (12.0%; 95% confidence interval: 5.6, 18.5). The corresponding false-negative rates are 3.5% and 10.2%, respectively. Conclusion—Among MADIT II–like patients, a microvolt T-wave alternans test is better than QRS duration at identifying a high-risk group and also better at identifying a low-risk group unlikely to benefit from ICD therapy.

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.

Comparison of 24-hour parasympathetic activity in endurance-trained and untrained young men

OBJECTIVES This study compares 24-h parasympathetic activity in aerobically trained and untrained healthy young men. BACKGROUND Higher values of parasympathetic nervous system activity are associated with a low mortality rate in patients after myocardial infarction, but it remains uncertain what therapeutic interventions can be used to increase parasympathetic activity. Although it is thought that exercise training can increase parasympathetic activity, studies have reported conflicting results, perhaps because this variable was measured for only brief intervals and usually inferred from changes in reflex responses induced by pharmacologic blockade. METHODS Parasympathetic activity was assessed noninvasively from 24-h ECG recordings by calculating high frequency (0.15 to 0.40 Hz) beat to beat heart period variability in eight endurance-trained men (maximal oxygen consumption greater than or equal to 55 ml/kg per min) and eight age-matched (mean = 29 yr) untrained men (maximal oxygen consumption less than or equal to 40 ml/kg per min). The data were analyzed separately for sleeping hours when parasympathetic activity is dominant and also for waking hours. RESULTS The geometric mean of high frequency power was greater in the trained than in the untrained men during the day (852 vs. 177 ms2, p less than 0.005), during the night (1,874 vs. 427 ms2, p less than 0.005) and over the entire 24 h (1,165 vs. 276 ms2, p less than 0.001). CONCLUSIONS Parasympathetic activity is substantially greater in trained than in untrained men, and this effect is present during both waking and sleeping hours. These data suggest that exercise training may increase parasympathetic activity over the entire day and may therefore prove to be a useful adjunct or alternative to drug therapy in lessening the derangements of autonomic balance found in many cardiovascular diseases.

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.

Time course of recovery of heart period variability after myocardial infarction

Four components of the heart period power spectrum--ultra low frequency (less than 0.0033 Hz), very low frequency (0.0033 to less than 0.04 Hz), low frequency (0.04 to less than 0.15 Hz) and high frequency power (0.15 to 0.40 Hz)--plus total power (1.157 x 10(-5) to 0.4 Hz for a 24-h electrocardiographic [ECG] recording) all predict mortality after myocardial infarction. To determine the time course and magnitude of recovery for these measures of heart period variability, 68 patients in the Cardiac Arrhythmia Pilot Study (CAPS) placebo group who had 24-h ECG recordings at baseline, 3, 6 and 12 months after myocardial infarction were studied. The 24-h power spectral density was computed with use of fast Fourier transforms and divided into the four components listed previously. The values for the five frequency domain measures of heart period variability in the CAPS patients were similar to those found in 715 patients who participated in the Multicenter Post Infarction Program (MPIP), indicating that the CAPS sample is generally representative of postinfarction patients with respect to these measures. The values for the five measures were one third to one half of those found in 95 normal persons of similar age and gender. There was a substantial increase in all measures of heart period variability between the baseline 24-h ECG recording and the 3-month recording (p less than 0.001). Between 3 and 12 months, the values were quite stable for the group as a whole, as well as for individual patients (intraclass correlation coefficients greater than or equal to 0.66).(ABSTRACT TRUNCATED AT 250 WORDS)