Smoking cessation in adolescents: the role of nicotine dependence, stress, and coping methods.

OBJECTIVES: To compare perceived reasons for continued smoking and withdrawal symptoms between current smokers and quitters in an inner-city adolescent population. To examine the relationship of nicotine dependence, stress, and coping methods between smokers and quitters and, using the Transtheoretical Model of Change, among adjacent smoking cessation stages. DESIGN: A cross-sectional study using a self-administered questionnaire. PARTICIPANTS: The study comprised 354 clinic patients between the ages of 12 and 21 years who reported past or present smoking. MAIN OUTCOME MEASURES: Demographic characteristics, smoking status, perceived reasons for continued smoking, attempts to quit, and withdrawal symptoms, as well as standardized scales assessing nicotine dependence, stress, and coping methods. RESULTS: The overall prevalence of smoking in this population was 26%. Smokers were significantly more likely to report smoking more cigarettes per day as well as higher levels of physical addiction (P<.01), greater levels of perceived stress (P<.02), and less use of cognitive coping methods (P<.02) than quitters (P<.005). However, comparison of consecutive stages revealed a significant difference only between precontemplation and contemplation in cognitive coping methods (P<.01). Three of 20 withdrawal symptoms (cravings, difficulty dealing with stress, and anger) were reported more frequently among current smokers who had attempted to quit in the last 6 months than among former smokers (P<.01). CONCLUSION: Interventions for inner-city adolescents who smoke should be designed to target those with the highest levels of nicotine dependence, stress, and decreased use of cognitive coping methods because they are the least likely to quit on their own, rather than developing stage-specific models.

Changes in sample size and length of follow-up to maintain power in the coronary artery bypass graft (CABG) patch trial.

The CABG Patch Trial is testing the hypothesis that prophylactic use of implantable cardiac defibrillators (ICDs) will improve survival in high-risk coronary heart disease patients undergoing CABG surgery. The original design called for 800 patients to be randomized to ICD prophylaxis or to no therapy and followed for 2 to 6.5 years (average, 40 months) to a common termination date. Since the ICD pulse generators used in this trial lasted about 42 months, the original design required ICD replacement in many patients. At its first two meetings in 1993, the Data and Safety Monitoring Board (DSMB) formalized a plan to adjust sample size in October 1994 if the control group mortality rate was lower than expected. In June 1994, an unanticipated and unique event--a subpoena from the Office of the Inspector General (OIG)--made it impossible to replace about half of the ICD generators and threatened to shorten follow-up substantially. If follow-up had been stopped on the date originally planned, but without replacing ICDs, the average follow-up would have fallen from 40 months to about 33 months. Also, in October 1994, the control group mortality rate was found to be somewhat lower than expected. Together, the abbreviated follow-up and lower control group mortality threatened to reduce power substantially. The DSMB reviewed several options for restoring power. Because mortality rates in the first month after CABG surgery were about seven times as high as thereafter and because ICD therapy did not reduce surgical mortality (death during the first 30 days), extending the follow-up benefits power more than does increasing the sample size. However, the limit on extending follow-up was 42 months (the expected battery life of the ICD). Data from the ICD-treated group was not reviewed or considered in making the decision. After reviewing many options for restoring power, the DSMB recommended that the sample size be increased from 800 to 900 patients and that almost all patients be followed for 42 months. This recommendation extended follow-up for 2 years beyond the original termination date planned for the trial and dictated that patients close out after 42 months rather than on a common termination date.

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.

Vagal modulation of RR intervals during head-up tilt and the infusion of isoproterenol.

The objective of this study was to characterize the autonomic effects of 2 interventions, head-up tilt and isoproterenol infusion, which alter autonomic balance by different mechanisms but produce the same RR intervals. We compared the effect of head-up tilt with the effect of isoproterenol on autonomic balance as measured by power spectral analysis of RR variability. Fifteen normal subjects had baseline measurements and then underwent head-up tilt. After return to baseline supine values, isoproterenol was infused at a rate of 1 microgram/min (low-dose isoproterenol), which was then increased to 2.1 +/- 0.5 microgram/min (high-dose isoproterenol). All subjects underwent a second tilt during high-dose isoproterenol, and 9 subjects completed this second tilt study. During the experiment, normal RR intervals were recorded and 5-minute segments were used to calculate power spectra. High-frequency (HF) power (0.15 to 0.40 Hz) was used as a measure of vagal activity. The effects of head-up tilt were compared with the effects of low-dose isoproterenol. Despite nearly identical mean RR intervals (784 ms with tilt vs 792 ms with low-dose isoproterenol, p = NS), there was significantly (p < 0.05) less HF power during head-up tilt in the drug-free state (172 ms2) than during low-dose isoproterenol in the supine position (307 ms2). A second head-up tilt was performed during the infusion of high-dose isoproterenol. During high-dose isoproterenol, tilt caused a decrease in RR intervals (from 573 to 491 ms; p < 0.01) and a decrease in HF power (from 68 to 28 ms2; p < 0.05).(ABSTRACT TRUNCATED AT 250 WORDS)

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.

Predicting mortality after myocardial infarction from the response of RR variability to antiarrhythmic drug therapy.

OBJECTIVES: This study was designed to test the hypothesis that antiarrhythmic drugs that decrease RR variability will predict all-cause mortality during follow-up after myocardial infarction. BACKGROUND: RR variability, a noninvasive indicator of autonomic nervous system activity, predicts death after acute myocardial infarction independently of other risk predictors and changes substantially in response to some drugs. A previous study in patients with chronic heart disease and frequent ventricular premature complexes reported that flecainide decreased vagal modulation of RR intervals but amiodarone did not. The investigators of that study speculated that changes in RR variability during antiarrhythmic drug therapy predict an increased mortality rate during long-term drug treatment. To explore this hypothesis further, we compared the effects of encainide and flecainide, which increase long-term mortality substantially, on RR variability with the effects of placebo and moricizine, which have no significant effect on mortality during long-term treatment of unsustained ventricular arrhythmias after myocardial infarction. METHODS: The 24-h power spectral density was computed from the baseline electrocardiographic recordings and drug evaluation tapes, and six frequency domain measures of RR variability were calculated: ultra-low frequency (< 0.0033 Hz), very low frequency (0.0033 to < 0.04 Hz), low frequency (0.04 to < 0.15 Hz) and high frequency power (0.15 to < 0.40 Hz), plus total power (< 0.40 Hz) and the ratio of low to high frequency power. Changes in power spectral measures were related to drug treatment and to mortality. RESULTS: In the placebo group, values for RR interval and RR variability increased because of recovery from the effects of acute myocardial infarction. Contrasting placebo treatment with all three active antiarrhythmic drug treatments taken together showed that of all the measures of RR variability, only NN50, pNN50 and low frequency power changed significantly during drug treatment (Bonferroni adjusted p value < 0.025); these variables all decreased during drug therapy. Contrasting encainide and flecainide with moricizine, we found that the encainide and flecainide groups taken together showed a larger decrease in dLF than moricizine, but the difference was of borderline significance (Bonferroni adjusted p value < 0.08). Survival was significantly worse in the groups treated with encainide and flecainide than in the groups treated with placebo or moricizine (relative risk > 2.0, adjusted p < 0.05). The antiarrhythmic drug-induced change in measures of RR variability was not a significant predictor of all-cause mortality during a year of follow-up after myocardial infarction. CONCLUSIONS: Encainide, flecainide and moricizine all caused a decrease in RR variability in patients studied approximately 1 month after acute myocardial infarction. Encainide and flecainide caused a significant increase in mortality rates; placebo and moricizine did not. Baseline measurements of RR variability also predicted all-cause mortality after myocardial infarction. The decrease in RR variability produced by the three antiarrhythmic drugs did not predict mortality during follow-up.

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.

Effects of digoxin and enalapril on heart period variability and response to head-up tilt in normal subjects.

To test the effects of digitalis and angiotensin-converting enzyme inhibition on the RR interval variability in an electrocardiogram, 20 normal subjects were given digoxin 0.25 mg, enalapril 10 mg, and placebo twice daily in a randomized, double-blind, crossover study. Continuous 24-hour electrocardiographic recordings obtained on day 5 of each treatment were analyzed and several time domain and power spectral measures of heart period variability were calculated. Digoxin markedly increased (up to 51%) indexes of vagal modulation of heart period without changing mean RR interval. Enalapril did not change any measure of heart period variability despite a modest hypotensive effect. To determine the effect of each treatment on the response to orthostatic stress, 10 subjects also underwent 15 minutes of 60 degrees head-up tilt; power spectra were calculated for 15 minutes at 0 degree and at 60 degrees of tilt. Neither active treatment affected the response to head-up tilt.

Frequency domain measures of heart period variability to assess risk late after myocardial infarction.

OBJECTIVES: To determine whether spectral measures of heart period (RR) variability predict death when measured late after infarction, we studied patients in the Cardiac Arrhythmia Pilot Study (CAPS) who survived for 1 year and had a 24-h electrocardiographic (ECG) recording made after the CAPS drug was washed out. BACKGROUND: Four components of the heart period power spectrum--ultra low frequency (< 0.0033 Hz), very low frequency (0.0033 to < 0.04 Hz), low frequency (0.04 to < 0.15 Hz) and high frequency power (0.15 to < 0.40 Hz)--plus total power (1.157 x 10(-5) to < 0.40 Hz) and the ratio of low to high frequency power predict mortality when measured < 30 days after myocardial infarction. However, these variables increase to steady state values by 3 months after infarction and the prognostic significance of recovery values is unknown. METHODS: The 24-h power spectral density was computed from ECG recordings made 1 year after infarction using fast Fourier transforms and the six measures listed were calculated. The values were dichotomized at cut points that maximized the association with mortality. RESULTS: Each measure of RR variability had a strong and significant univariate association with mortality; the relative risks for these variables ranged from 2.5 to 5.6. After adjustment for age, New York Heart Association functional class, rales in the coronary care unit, left ventricular ejection fraction and ventricular arrhythmias, some measures of heart period variability still had a strong and significant independent association with all-cause mortality. CONCLUSIONS: Spectral measures of heart period variability, measured late after infarction, predict death.

Enrollment in clinical trials: institutional factors affecting enrollment in the cardiac arrhythmia suppression trial (CAST).

Recruitment and Enrollment Assessment in Clinical Trials (REACT), an NHLBI-sponsored substudy of the Cardiac Arrhythmia Suppression Trial (CAST), was conducted to assess factors associated with enrollment in clinical trials. We report on the relationships of institutional factors at CAST sites to patient enrollment. The proportion of CAST-eligible patients enrolling at each CAST site during the REACT study period was defined as the number of subjects enrolled divided by the sum of (1) the number enrolled plus (2) the number of eligibles who refused plus (3) the number of eligibles whose physicians refused to permit CAST personnel to attempt to enroll them. A questionnaire that included 78 questions regarding factors hypothesized to be associated with enrollment was completed between August 1988 and February 1990 by the nurse coordinators at all 112 CAST sites in the United States and Canada. Sixteen items were unanalyzable, and 37 of the remaining 62 were grouped into seven scales. The remaining items were analyzed individually. Enrollment proportions varied widely across the 112 CAST sites (mean 32.7% SD 22.6). Five variables or scales were included in the final multiple regression model (multiple R2 = .39). The most important of these was the proportion of eligible patients at a site cared for by medical staff other than private attending physicians (multiple R2 for this variable alone, .26). This proportion tended to be high in teaching hospitals. Other variables in this model that were associated with higher enrollment proportions included the number of days per week a nurse coordinator was present at the site, the number of nurse coordinator full-time equivalents at the site, fewer other clinical trials for which the nurse coordinator was responsible, and fewer perceived obstacles to enrollment. These findings indicate that enrollment was more successful at hospitals with higher proportions of eligible subjects cared for by fellows, housestaff, and service attending physicians and at institutions with the committed presence of a nurse-coordinator.

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.

Stability over time of heart period variability in patients with previous myocardial infarction and ventricular arrhythmias. The CAPS and ESVEM investigators.

To determine the reproducibility of frequency domain measures of heart period variability in patients with previous myocardial infarction, 2 random samples of 40 patients each (1 from the Cardiac Arrhythmia Pilot Study [CAPS] [unsustained ventricular arrhythmias], and 1 from the Electrophysiologic Studies Versus Electrocardiographic Monitoring [ESVEM] [sustained ventricular arrhythmias] trial) were studied. For each patient, two 24-hour continuous electrocardiographic recordings were analyzed, and the average normal RR interval, total power and 4 components of total power were calculated. Group means and standard deviations for each sample were virtually identical for the pairs of 24-hour recordings. Furthermore, measurements for individual patients were stable from day to day, as measured by the intraclass correlation coefficients and the standard errors of measurement. Reproducibility of heart period variability measurements is excellent in patients with previous myocardial infarction and ventricular arrhythmias, and is comparable to the high stability previously found in a small group of normal subjects. The stability of measures of heart period variability facilitates distinguishing real changes due to progression or regression of cardiac disease or to drug effects from apparent changes due to random variation.

The correlation between heart period variability and mean period length.

Heart rate variability and heart period variability are important indicators of the functioning of the autonomic nervous system and are strong predictors of survival after myocardial infarction. The standard deviation of a patient's series of normal heart periods (consecutive normal RR intervals) is positively and, in some populations, strongly correlated with the mean period length. This phenomenon has led some investigators to use the coefficient of variation as their measure of variability, because it correlates less strongly with the mean period length. Using data from a multicentre post-infarction natural history study, we show that the standard deviation of the instantaneous heart rates has, like the coefficient of variation, only a modest correlation with the mean period length. Unlike the coefficient of variation, however, this standard deviation is derivable from established statistical principles. We show further that the coefficient of variation, the standard deviation of heart rates, and the standard deviation of heart periods are approximately equally strong predictors of survival after myocardial infarction.

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

BACKGROUND: We 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 RESULTS: Each 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. CONCLUSIONS: After 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%.

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)

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

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 greater than 50 ms computed over the entire 24-hour electrocardiographic recording (proportion of adjacent intervals greater than 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 greater than 50 ms computed over the entire 24-hour electrocardiographic recording) were highly correlated (r greater than 0.8). It is concluded that measures of HR variability are stable over short periods of time.(ABSTRACT TRUNCATED AT 250 WORDS)

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.

Relation between beta-adrenergic blocker use, various correlates of left ventricular function and the chance of developing congestive heart failure. The Multicenter Diltiazem Post-Infarction Research Group.

This study examined the relations among beta-adrenergic blocker use, various correlates of left ventricular function and the chance of developing congestive heart failure in patients after myocardial infarction. The study was performed with the placebo group of the Multicenter Diltiazem Post-Infarction Trial. Ejection fraction data were available in 1,084 patients; of these, 557 were receiving a beta-blocker and 527 were not. In addition to ejection fraction, other correlates of left ventricular function included the presence or absence of pulmonary rales, chest X-ray film evidence of pulmonary congestion and the presence of an S3 gallop. Beta-blocker use was less frequent in patients with an ejection fraction less than 30%, rales, an S3 gallop and pulmonary congestion on chest X-ray film. Twenty-one percent of patients with an ejection fraction less than 30%, 42% of patients with rales, 28% of patients with an S3 gallop and 28% of patients with pulmonary congestion were receiving beta-blocker therapy. For every correlate of left ventricular function, the chance of developing congestive heart failure was greater in patients with diminished left ventricular function than in those without. For each level of left ventricular function, the chance of developing congestive heart failure requiring treatment was greater in patients not taking a beta-blocker.(ABSTRACT TRUNCATED AT 250 WORDS)