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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.

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.

Objectives: We sought to compare the likelihood of stroke in patients with anterior versus nonanterior myocardial infarction., Background: The association between anterior infarction and left ventricular thrombus has led to the assumption that embolization from thrombi is an important cause of stroke in patients with anterior infarction. We hypothesized that if anterior infarction is a cause of left ventricular thrombi, the number of strokes should be disproportionately higher in patients with anterior than nonanterior infarction., Methods: We performed a retrospective analysis of 2,466 patients randomized from day 3 to day 15 after infarction as part of a multicenter placebo-controlled study of diltiazem to prevent cardiac death or myocardial infarction. Any acute focal cerebral disorder resulting in localizing findings characterized as a stroke or transient ischemic attack was considered an event., Results: Of 91 events during a follow-up period of 12 to 52 months, 23 (3.2%) occurred in 724 patients with an anterior and 68 (3.9%) in 1,742 patients with a nonanterior myocardial infarction (relative risk 0.81; 95% confidence interval 0.51 to 1.30). Power analysis revealed that the negativity of the study was not the result of inadequate sample size. Life table analysis showed no difference in cumulative event rate (p = 0.42) according to site of infarction. Cox regression analysis showed that of 10 clinical covariates, only systolic blood pressure was predictive of stroke (p < 0.001). The use of warfarin did not contribute to the model. Finally, the addition of site of infarction (anterior vs. nonanterior) did not contribute significantly to the Cox model., Conclusions: Although there is a significant incidence of stroke after acute myocardial infarction, there is no relation between the occurrence of stroke and site of infarction. These data do not support the presumed causal relation between anterior myocardial infarction, thrombus and stroke.

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.

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.

Cornfield's test-based method of setting a confidence interval on a parameter associated with a two-by-two contingency table is adapted for use with the measure of agreement kappa. One-sided confidence intervals derived in this way are compared to other intervals proposed for kappa under two study designs. Both designs involve two ratings per subject on a dichotomous scale. In one design the same two raters make all evaluations; in the other, possibly different pairs of raters evaluate different subjects, or the same rater carries out a pair of independent assessments for each subject. It is shown through simulation that lower bounds based on Cornfield's test-based method attain the nominal coverage probability more often than other intervals proposed in the literature.

Objectives: This study was designed to assess factors affecting interobserver agreement in interpretation of planar thallium-201 stress imaging in the Multicenter Study on Silent Myocardial Ischemia (MSSMI)., Background: Five hundred fifty-six planar thallium-201 images were interpreted in 24 clinical centers and in a Radionuclide Core Laboratory. The trial's Coordinating and Data Center observed that the participating clinical centers interpreted a significantly greater number of thallium-201 stress studies as abnormal (i.e., myocardial ischemia or scar) than the Core Laboratory, and overall agreement was poor (kappa 0.27)., Methods: Agreement in image interpretation between clinical centers and the Radionuclide Core Laboratory was analyzed by kappa statistics. The reproducibility of the Core Laboratory results on 41 randomly selected test studies was excellent (kappa 0.77). In contrast, the reproducibility of interpretation in the clinical centers on their own studies was at best fair (kappa 0.45). It was hypothesized that the poor agreement and reproducibility in the clinical centers were caused by lack of standardization of image display and lack of objective criteria for image interpretation. To test the effect of standardization, 13 clinical investigators interpreted the same 41 test studies using 1) uniform image display, and 2) uniform quantification of images., Results: The agreement in interpretation between clinical investigators and the Radionuclide Core Laboratory improved modestly with uniformity of image display (kappa 0.57) but improved markedly (kappa 0.66) with quantitative circumferential profile analysis., Conclusions: Lack of standardization in image display and lack of objective criteria for interpretation of thallium-201 images are responsible for suboptimal reproducibility and poor interlaboratory agreement in the interpretation of thallium-201 stress imaging. The adoption of a uniformly accepted method for computer quantification of myocardial perfusion images is crucial to improve agreement in interpretation.

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.

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.

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%.

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)

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.

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)

In epidemiological studies using linear regression, it is often necessary for reasons of economy or unavailability of data to use as the independent variable not the variable ideally demanded by the hypothesis under study but some convenient practical approximation to it. We show that if the correlation coefficient between the "practical" and "ideal" variables can be obtained, then a range of uncertainty can be obtained within which the desired regression coefficient of dependent on "ideal" variable may lie. This range can be quite wide, even if the practical and ideal variables are fairly well correlated. These points are illustrated with data on observed regression coefficients from an air pollution epidemiological study, in which pollution measured at one station in a large metropolitan area (containing 40 aerometric stations) was used as the practical approximation to the city-wide average pollution. The uncertainties in the regression coefficients were found to exceed the regression coefficients themselves by large factors. The problem is one that may afflict application of linear regression in general, and suggests caution when selecting independent variables for regression analysis on the basis of convenience, rather than relevance to the hypotheses tested.

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)

A simple approximation is provided to the formula for the sample sizes needed to detect a difference between two binomial probabilities with specified significance level and power. The formula for equal sample sizes was derived by Casagrande, Pike and Smith (1978, Biometrics 34 , 483-486) and can be easily generalized to the case of unequal sample sizes. It is shown that over fairly wide ranges of parameter values and ratios of sample sizes, the percentage error which results from using the approximation is no greater than 1%. The approximation is especially useful for the inverse problem of estimating power when the sample sizes are given.

Some statistical techniques for analyzing the kinds of studies typically reported in Circulation Research are described. Particular emphasis is given to the comparison of means from more than two populations, the joint effect of several experimentally controlled variables, and the analysis of studies with repeated measurements on the same experimental units.

At least a dozen indexes have been proposed for measuring agreement between two judges on a categorical scale. Using the binary (positive-negative) case as a model, this paper presents and critically evaluates some of these proposed measures. The importance of correcting for chance-expected agreement is emphasized, and identities with intraclass correlation coefficients are pointed out.

The effects of random errors of measurement on a variety of basic multivariate procedures are discussed. For some procedures, the effect is one of attenuation (i.e., simply reducing the estimated strength of association). For others, the effect may be to alter the apparent direction of association. Some proposed solutions to the problems caused by errors of measurement are presented, and areas requiring further research are pointed out.

An investigator wishes to compare two independent proportions, based on perhaps unequal sample sizes, by means of the chi squared test with the Yates' correction. A simple approximation is given to the sample size(s) required for the Yates-corrected chi squared test to have specified power; it is then compared with other approximations and with the exact sample size for the equal sample case. In that case the proposed approximation is quite similar to the approximate formula recently put forward by Casagrande, Pike and Smith (1978, Biometrics 34, 483-486).

In animals, baroreflex sensitivity is inversely related to the likelihood of ventricular fibrillation during myocardial ischemia. After myocardial infarction in human patients, reduced baroreflex sensitivity is associated with increased mortality. A reduced standard deviation of normal RR intervals over a 24 h period is also associated with reduced survival after myocardial infarction. Therefore, 32 normotensive men who had survived their first myocardial infarction were studied to define the relation between baroreflex sensitivity assessed with phenylephrine injection and three Holter electrocardiographic measures of tonic vagal activity: the percent of successive normal RR intervals greater than 50 ms, the root mean square successive difference of normal RR intervals and the power in the high frequency energy of the normal RR interval power spectrum. Correlations among the Holter measures of heart period variability were greater than or equal to 0.94, indicating that these measures are so strongly correlated that any one of them can be used to represent the others. Baroreflex sensitivity showed weaker correlations with the three Holter variables (0.57 to 0.63), indicating that the Holter measures did not accurately predict baroreflex sensitivity. Baroreflex sensitivity showed a stronger correlation with the three Holter variables during the night than during the day. Baroreflex sensitivity and tonic vagal activity reflected by Holter variables were reduced more in patients with inferior myocardial infarction than in those with anterior infarction. The relative utility of baroreflex sensitivity and Holter measures of tonic vagal activity in predicting sudden cardiac death after myocardial infarction needs to be evaluated in a large prospective study.

This communication examines the pathways of geriatric psychiatric patients in New York and London from the time of onset of a psychiatric episode to hospitalization. Informants of 50 patients in each city were interviewed with a semi-structured interview covering the events and the patient's activities prior to hospitalization. The results show that the time from the onset of the episode to hospitalization is significantly shorter in London than it is in New York. The major portion of this difference is accounted for by the longer time spent London the doctor is significantly more involved in New York between episode onset and initial medical contact. In the decision to hospitalize. In New York the main reason for hospitalization is harmful behavior, while in London it is psychiatric symptoms.

The McNemar test for correlated proportions has been generalized to test for marginal homogeneity of either a 2c or an m2 contingency table. The tests for 2(3) and 3(2) tables turn out to be equivalent since each involves six non-diagonal elements; equal numbers of degrees of freedom in the associated chi square tests, m - 1 = c - 1 = 2; identical constraints on the fits to the non-diagonal elements; and identical measures of discrepancy between observed and fitted values to be optimized.