Fractal analysis of heart rate variability and mortality after an acute myocardial infarction

The recently developed fractal analysis of heart rate (HR) variability has been suggested to provide prognostic information about patients with heart failure. This prospective multicenter study was designed to assess the prognostic significance of fractal and traditional HR variability parameters in a large, consecutive series of survivors of an acute myocardial infarction (AMI). A consecutive series of 697 patients were recruited to participate 2 to 7 days after an AMI in 3 Nordic university hospitals. The conventional time-domain and spectral parameters and the newer fractal scaling indexes of HR variability were analyzed from 24-hour RR interval recordings. During the mean follow-up of 18.4 +/- 6.5 months, 49 patients (7.0%) died. Of all the risk variables, a reduced short-term fractal scaling exponent (alpha(1) <0.65), measured by detrended fluctuation analysis, was the most powerful predictor of mortality (univariate relative risk 5.05, 95% confidence intervals [CI] 2.87 to 8.89, p <0.001). A low scaling exponent alpha(1) predicted death in the patients with and without depressed left ventricular function (p <0.001 and p <0.01, respectively). Several other HR variability parameters also predicted mortality in univariate analyses, but in a multivariate analysis after adjustments for clinical variables and left ventricular ejection fraction, alpha(1) was the most significant independent HR variability index that predicted subsequent mortality (relative risk 3.90, 95% CI 2.03 to 7.49, p <0.001). Short-term fractal scaling analysis of HR variability is a powerful predictor of mortality among patients surviving an acute myocardial infarction.     

Prediction of sudden cardiac death by fractal analysis of heart rate variability in elderly subjects

OBJECTIVES: The aim of this study was to test the hypothesis that abnormal scaling characteristics of heart rate (HR) predict sudden cardiac death in a random population of elderly subjects. BACKGROUND: An abnormality in the short-term fractal scaling properties of HR has been observed to be related to a risk of life-threatening arrhythmias among patients with advanced heart diseases. The predictive power of altered short-term scaling properties of HR in general populations is unknown. METHODS: A random sample of 325 subjects, age 65 years or older, who had a comprehensive risk profiling from clinical evaluation, laboratory tests and 24-h Holter recordings were followed up for 10 years. Heart rate dynamics, including conventional and fractal scaling measures of HR variability, were analyzed. RESULTS: At 10 years of follow-up, 164 subjects had died. Seventy-one subjects had died of a cardiac cause, and 29 deaths were defined as sudden cardiac deaths. By univariate analysis, a reduced short-term fractal scaling exponent predicted the occurrence of cardiac death (relative risk [RR] 2.5, 95% confidence interval [CI], 1.9 to 3.2, p < 0.001) and provided even stronger prediction of sudden cardiac death (RR 4.1, 95% CI, 2.5 to 6.6, p < 0.001). After adjusting for other predictive variables in a multivariate analysis, reduced exponent value remained as an independent predictor of sudden cardiac death (RR 4.3, 95% CI, 2.0 to 9.2, p < 0.001). CONCLUSIONS: Altered short-term fractal scaling properties of HR indicate an increased risk for cardiac mortality, particularly sudden cardiac death, in the random population of elderly subjects.     

Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. TRACE Investigators. TRAndolapril Cardiac Evaluation

A number of new methods have been recently developed to quantify complex heart rate (HR) dynamics based on nonlinear and fractal analysis, but their value in risk stratification has not been evaluated. This study was designed to determine whether selected new dynamic analysis methods of HR variability predict mortality in patients with depressed left ventricular (LV) function after acute myocardial infarction (AMI). Traditional time- and frequency-domain HR variability indexes along with short-term fractal-like correlation properties of RR intervals (exponent alpha) and power-law scaling (exponent beta) were studied in 159 patients with depressed LV function (ejection fraction <35%) after an AMI. By the end of 4-year follow-up, 72 patients (45%) had died and 87 (55%) were still alive. Short-term scaling exponent alpha (1.07 +/- 0.26 vs 0.90 +/- 0.26, p <0.001) and power-law slope beta (-1.35 +/- 0.23 vs -1.44 +/- 0.25, p <0.05) differed between survivors and those who died, but none of the traditional HR variability measures differed between these groups. Among all analyzed variables, reduced scaling exponent alpha (<0.85) was the best univariable predictor of mortality (relative risk 3.17, 95% confidence interval 1.96 to 5.15, p <0.0001), with positive and negative predictive accuracies of 65% and 86%, respectively. In the multivariable Cox proportional hazards analysis, mortality was independently predicted by the reduced exponent alpha (p <0.001) after adjustment for several clinical variables and LV function. A short-term fractal-like scaling exponent was the most powerful HR variability index in predicting mortality in patients with depressed LV function. Reduction in fractal correlation properties implies more random short-term HR dynamics in patients with increased risk of death after AMI.     

Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction

BACKGROUND: Preliminary data suggest that the analysis of R-R interval variability by fractal analysis methods may provide clinically useful information on patients with heart failure. The purpose of this study was to compare the prognostic power of new fractal and traditional measures of R-R interval variability as predictors of death after acute myocardial infarction. METHODS AND RESULTS: Time and frequency domain heart rate (HR) variability measures, along with short- and long-term correlation (fractal) properties of R-R intervals (exponents alpha(1) and alpha(2)) and power-law scaling of the power spectra (exponent beta), were assessed from 24-hour Holter recordings in 446 survivors of acute myocardial infarction with a depressed left ventricular function (ejection fraction 相似文献   

Temporal changes and prognostic significance of measures of heart rate dynamics after acute myocardial infarction in the beta-blocking era

Previous studies have shown that indexes describing heart rate (HR) dynamics may predict subsequent deaths of patients after an acute myocardial infarction (AMI). Because beta-blocking (BB) drugs affect both mortality and HR dynamics, the prognostic power of measurements of HR dynamics may have changed in the current era of BB therapy. This study assessed the temporal changes and prognostic significance of time-domain, spectral, and fractal indexes of HR variability along with HR turbulence after an AMI among patients with optimized BB medication. SD of NN intervals, spectral indexes, the short-term fractal scaling exponent (alpha(1)), power-law slope (beta), and turbulence onset and slope were measured in 600 patients at 5 to 7 days after AMI and in 416 patients at 12 months after AMI. In the multivariate analysis, after adjusting for clinical variables, only reduced fractal HR indexes, alpha1 and beta (p <0.01 for both), turbulence onset, and slope (p <0.05 for both), measured at the convalescent phase after AMI, predicted subsequent cardiac death. All time-domain and spectral HR variability indexes and turbulence onset increased significantly during the 12-month period after AMI (p <0.001 for all), whereas the fractal indexes and turbulence slope remained unchanged. Late after AMI, reduced beta (p <0.05) and turbulence slope (p <0.01) were the only independent predictors of cardiac mortality. Traditional time-domain and spectral measurements of HR variability and turbulence onset improved significantly after AMI, whereas the fractal HR dynamics and turbulence slope remained stable. Fractal HR variability and HR turbulence retain their prognostic power in the BB era, when measured either at the convalescent or late phase after AMI.     

Measures of heart period variability as predictors of mortality in hospitalized patients with decompensated congestive heart failure

Depressed heart rate variability (HRV) is a powerful independent predictor of a poor outcome in patients with chronic and stable congestive heart failure (CHF). However, the prognostic value of HRV analysis in patients hospitalized for decompensated CHF is not known. The aim of this study was to investigate whether HRV parameters obtained during admission for decompensated CHF could predict survival after hospital discharge. We studied 199 patients (131 men, aged 60 +/- 14 years) with a previous diagnosis of New York Heart Association class III or IV CHF who were admitted to the hospital for decompensated CHF. Twenty-four-hour Holter recordings were obtained on admission, and measures of HRV were calculated in the time and frequency domain. During a mean follow-up of 312 +/- 150 days, 40 patients (21.1%) died. Kaplan-Meier analysis indicated that patients with SD of the RR intervals over a 24-hour period (p = 0.027), SD of all 5-minute mean RR intervals (p = 0.043), total power (p = 0.022), and ultra-low-frequency power (p = 0.008) in the lower tertile were at a higher risk of death. In a multivariate Cox regression model, the same indexes in the lower tertile were independent predictors of mortality: SD of the RR intervals over a 24-hour period (risk ratio [RR] 2.2, 95% confidence interval [CI] 1.05 to 4.3, p = 0.036), SD of all 5-minute mean RR intervals (RR 2.1, 95% CI 1.05 to 4.2, p = 0.04), total power (RR 2.2, 95% CI 1.08 to 4.2, p = 0.03), and ultra-low-frequency power (RR 2.6, 95% CI 1.3 to 5.3, p = 0.007). Therefore, the severity of autonomic perturbations during hospital admission for CHF decompensation, as reflected by measures of overall HRV, can predict survival after hospital discharge. Together with previous studies, our findings suggest that indexes of overall HRV provide useful prognostic information in the full spectrum of CHF severity.     

Prognostic Value of Heart Rate Variability in Time Domain Analysis in Congestive Heart Failure

AIMS: Analysis of heart rate variability is a noninvasive tool that allows to study autonomic control of the heart. Several studies have shown disturbed heart rate variability in patients with chronic heart failure (CHF). We sought to assess the prognostic value of time domain measures of heart rate variability in CHF. METHODS AND RESULTS: We prospectively enrolled 190 patients with CHF in sinus rhythm, mean age 61+/-12 years, 109 (57.4 %) in NYHA class II and 81 (42.6 %) in class III or IV, mean cardiothoracic ratio 57.6+/-6.4 % and mean left ventricular ejection fraction 28.2+/-8.8 %, 85 (45 %) with ischemic and 105 (55 %) with idiopathic dilated cardiomyopathy. Time domain measures of heart rate variability were obtained from 24 h Holter ECG recordings. During follow-up (22+/-18 months), 55 patients died. In multivariate analysis, independent predictors for all-cause mortality were: ischemic heart disease, cardiothoracic ratio > or =60 % and standard deviation of all normal RR intervals <67 ms (RR=2.5, 95 % CI 1.5--4.2). CONCLUSIONS: Depressed heart rate variability has independent prognostic value in patients with CHF.     

Heart rate dynamics before spontaneous onset of ventricular fibrillation in patients with healed myocardial infarcts

The traditional methods of analyzing heart rate (HR) variability have failed to predict imminent ventricular fibrillation (VF). We sought to determine whether new methods of analyzing RR interval variability based on nonlinear dynamics and fractal analysis may help to detect subtle abnormalities in RR interval behavior before the onset of life-threatening arrhythmias. RR interval dynamics were analyzed from 24-hour Holter recordings of 15 patients who experienced VF during electrocardiographic recording. Thirty patients without spontaneous or inducible arrhythmia events served as a control group in this retrospective case control study. Conventional time- and frequency-domain measurements, the short-term fractal scaling exponent (alpha) obtained by detrended fluctuation analysis, and the slope (beta) of the power-law regression line (log power - log frequency, 10(-4)-10(-2) Hz) of RR interval dynamics were determined. The short-term correlation exponent alpha of RR intervals (0.64 +/- 0.19 vs 1.05 +/- 0.12; p <0.001) and the power-law slope beta (-1.63 +/- 0.28 vs -1.31 +/- 0.20, p <0.001) were lower in the patients before the onset of VF than in the control patients, but the SD and the low-frequency spectral components of RR intervals did not differ between the groups. The short-term scaling exponent performed better than any other measurement of HR variability in differentiating between the patients with VF and controls. Altered fractal correlation properties of HR behavior precede the spontaneous onset of VF. Dynamic analysis methods of analyzing RR intervals may help to identify abnormalities in HR behavior before VF.     

Fractal correlation properties of heart rate dynamics and adverse events in patients with implantable cardioverter-defibrillators.

The aim of this study was to determine the prognostic significance of nonlinear and standard heart rate (HR) variability parameters in predicting future adverse events (AEs) in patients with implantable cardioverter-defibrillators. In postinfarction studies, nonlinear measures of HR variability obtained from long-term electrocardiographic recordings have been suggested to be better predictors of adverse outcomes than conventional HR variability measures. Fifty-five high-risk patients with reduced left ventricular function and an implantable cardioverter-defibrillator had a 10-minute, high-resolution electrocardiographic recording after which they were followed for 25 months on average. Implantable cardioverter-defibrillator shock or death was determined as the end point. The SD of all normal-to-normal RR intervals, the square root of the mean squared differences of successive normal-to-normal RR intervals, and the proportion of interval differences of successive normal-to-normal RR intervals >50 ms, low-frequency and high-frequency powers of the power spectrum and their ratio were calculated as conventional measures of HR variability. The short-term scaling exponent (alpha(1)) and approximate entropy were determined as nonlinear measures of HR variability. AEs occurred in 23 patients (42%). Patients with AEs had significantly lower alpha(1) than event-free patients: 0.81 +/- 0.29 (mean +/- SD) versus 1.01 +/- 0.30 (p = 0.02). None of the other HR variability parameters differed significantly between patients with and without AEs. In the Cox proportional-hazards model including age, gender, ejection fraction, occurrence of ventricular tachyarrhythmia before defibrillator implantation, beta-blocker usage, and alpha(1), only alpha(1) was an independent predictor of AEs: hazard ratio 1.20 (95% confidence interval 1.03 to 1.39) for every 0.10 decrease in alpha(1) (p = 0.020). In conclusion, alpha(1) obtained from a 10-minute electrocardiographic recording yields important prognostic information about the risk of AEs in patients with implantable cardioverter-defibrillators.     

Effects of Carvedilol on Heart Rate Dynamics in Patients with Congestive Heart Failure

Background: Patients with congestive heart failure (CHF) have alterations in the traditional and nonlinear indices of heart rate (HR) dynamics, which have been associated with an increased risk of mortality. This study was designed to test the effects of carvedilol, a nonselective beta‐blocker with alpha‐1 blocking properties, on HR dynamics in patients with CHF. Methods: We studied 15 patients with CHF secondary to ischemic or idiopathic cardiomyopathy who met the following inclusion criteria: NYHA functional class II‐III, optimal conventional medical therapy, normal sinus rhythm, left ventricular ejection fraction (LVEF) of < 40%, and resting systolic blood pressure greater than 100 mmHg. The 6‐minute corridor walk test, estimation of LVEF, and 24‐hour Holter recording were performed at baseline and after 12 weeks of therapy with carvedilol. Traditional time and frequency domain measures and short‐term fractal scaling exponent of HR dynamics were analyzed. Results: After 12 weeks of therapy with carvedilol, the mean LVEF improved significantly (from 0.27 ± 0.08 to 0.38 ± 0.08, P < 0.001). The average HR decreased significantly (from 86 ± 11 to 70 ± 8 beats/min, P < 0.001). The mean distance traveled in the 6‐minute walk test increased significantly (from 177 ± 44 to 273 ± 55 m, P < 0.01). The frequency‐domain indices (HF and LF), the time domain indices (rMSSD and PNN5), and the short‐term fractal scaling exponent increased significantly. The scaling exponent increased particularly among the patients with the lowest initial values (< 1.0), and the change in the fractal scaling exponent correlated with the change in ejection fraction (r = 0.63, P < 0.01). Conclusion: Carvedilol improves time and frequency domain indices of HR variability and corrects the altered scaling properties of HR dynamics in patients with CHF. It also improves LVEF and functional capacity. These specific changes in HR behavior caused by carvedilol treatment may reflect the normalization of impaired cardiovascular neural regulation of patients with CHF. A.N.E. 2002;7(2):133–138     

Prognostic value of iodine-123-metaiodobenzylguanidine myocardial uptake and heart rate variability in chronic congestive heart failure secondary to ischemic or idiopathic dilated cardiomyopathy

Autonomic nervous system dysfunction is common in congestive heart failure (CHF) and is believed to predispose patients to an increased risk of death. This study aimed to assess the prognostic significance of heart rate variability (HRV) measurements in conjunction with scintigraphic imaging using metaiodobenzylguanidine (MIBG) labeled with iodine-123 (I-123-MIBG), which detects abnormalities in autonomic nervous activity, in patients with stable CHF during optimal medical treatment. The study population included 52 patients (56 +/- 12 years of age) with a mean left ventricular ejection fraction of 31 +/- 12%. All underwent I-123-MIBG scanning and 24-hour ambulatory electrocardiographic monitoring for the analysis of HRV on entrance into the study. The heart/mediastinum MIBG uptake ratio was calculated. HRV analysis included the assessment of time- and frequency-domain variables. During the 2-year follow-up, 14 patients (27%) died. MIBG uptake at 1 hour was less (1.39 +/- 0.10) in nonsurvivors than in survivors (1.50 +/- 0.16; p = 0.013). In univariate Cox regression analysis, MIBG uptake was a significant prognostic factor (p = 0.038, hazard ratio [HR] 0.017, 95% confidence interval [CI] 0.00 to 0.79). Time- and frequency-domain variables were similar in survivors and nonsurvivors. However, high-frequency power was associated with an increased risk for sudden death (HR 0.310, 95% CI 0.101 to 0.954, p = 0.041) but not with all-cause mortality. In conclusion, cardiac I-123-MIBG imaging identifies patients with CHF at high risk of dying and may be a more reliable predictor of overall mortality than HRV.     

Heart Rate Variability in Risk Stratification of Cardiac Patients

Heart rate (HR) variability has been extensively studied in cardiac patients, especially in patients surviving an acute myocardial infarction (AMI) and also in patients with congestive heart failure (CHF) or left ventricular (LV) dysfunction. The majority of studies have shown that patients with reduced or abnormal HR variability have an increased risk of mortality within a few years after an AMI or after a diagnosis of CHF/LV dysfunction. Various measures of HR dynamics, such as time-domain, spectral, and non-linear measures of HR variability have been used in risk stratification. The prognostic power of various measures, except of those reflecting rapid R–R interval oscillations, has been almost identical, albeit some non-linear HR variability measures, such as short-term fractal scaling exponent have provided somewhat better prognostic information than the others. Abnormal HR variability predicts both sudden and non-sudden cardiac death. Because of remodeling of the arrhythmia substrate after AMI, early measurement of HR variability to identify those at high risk should likely be repeated later in order to assess the risk of fatal arrhythmia events. Future randomized trials using HR variability/turbulence as one of the pre-defined inclusion criteria will show whether routine measurement of HR variability/turbulence will become a routine clinical tool for risk stratification of cardiac patients.     

Fractal and complexity measures of heart rate variability

Heart rate variability has been analyzed conventionally with time and frequency domain methods, which measure the overall magnitude of RR interval fluctuations around its mean value or the magnitude of fluctuations in some predetermined frequencies. Analysis of heart rate dynamics by methods based on chaos theory and nonlinear system theory has gained recent interest. This interest is based on observations suggesting that the mechanisms involved in cardiovascular regulation likely interact with each other in a nonlinear way. Furthermore, recent observational studies suggest that some indexes describing nonlinear heart rate dynamics, such as fractal scaling exponents, may provide more powerful prognostic information than the traditional heart rate variability indexes. In particular, the short-term fractal scaling exponent measured by the detrended fluctuation analysis method has predicted fatal cardiovascular events in various populations. Approximate entropy, a nonlinear index of heart rate dynamics, that describes the complexity of RR interval behavior, has provided information on the vulnerability to atrial fibrillation. Many other nonlinear indexes, e.g., Lyapunov exponent and correlation dimensions, also give information on the characteristics of heart rate dynamics, but their clinical utility is not well established. Although concepts of chaos theory, fractal mathematics, and complexity measures of heart rate behavior in relation to cardiovascular physiology or various cardiovascular events are still far away from clinical medicine, they are a fruitful area for future research to expand our knowledge concerning the behavior of cardiovascular oscillations in normal healthy conditions as well as in disease states.     

Decreased spontaneous heart rate variability in congestive heart failure

Heart rate (HR) variability is a noninvasive index of the neural activity of the heart. Although also dependent on the sympathetic activity of the heart, HR variability is mainly determined by the vagal outflow of the heart. Several HR abnormalities have been described in patients with congestive heart failure (CHF); however, there are no data on HR variability in CHF patients. In the present study HR variability was assessed in 20 CHF patients and 20 control subjects from 24-hour Holter tapes. HR variability was evaluated by calculating the mean hourly HR standard deviation and by analyzing the 24-hour RR histogram. Mean hourly HR standard deviation was markedly and significantly reduced in CHF patients both over the 24-hour period (97.5 +/- 41 vs 233.2 +/- 26 ms, p less than 0.001) as well as during most of the individual hours examined. The 24-hour RR histogram of CHF patients had a different shape and had a decreased variation compared to control subjects (total variability 356 +/- 102 vs 757 +/- 156 ms, p less than 0.001). Thus, CHF patients with depressed ejection fraction (less than 30%) have a low HR variability compared to normal individuals. This result can be interpreted as adjunctive evidence for decreased parasympathetic activity to the heart during CHF.     

Chronic heart failure in the very elderly: clinical status, survival, and prognostic factors in 188 patients more than 70 years old.

BACKGROUND: Chronic heart failure (CHF) is a frequent disease with a dismal prognosis, but little is known about survival in the very elderly. There are no data on the prognostic value of cardiopulmonary exercise testing in this population. We aimed to assess exercise capacity, survival, and prognostic parameters in elderly patients with CHF. METHODS: We evaluated 188 patients with CHF >70 years old (mean 77 +/- 4 years, range 70-94 years) seen at our heart failure clinic between March 1992 and June 1998. A cardiopulmonary exercise test was performed in 102 patients (peak VO2 15.3 +/- 4.7, VE/VCO2 slope 39.6 +/- 15.01). All patients were followed up for at least 12 months. The prognostic end point of the study was all-cause mortality. RESULTS: At the end of follow-up (16 +/- 10 mo, range 12-41 mo), 67 patients (35.6%) had died (1-year mortality rate 26% [95% confidence interval 20-32]). In univariate analysis New York Heart Association class (NYHA) (relative risk [RR] = 2.56, P <.0001), VE/VCO2 (RR = 1.041, P <.0001), peak VO2 (RR = 0.87, P =.0007), and fractional shortening (RR = 0.95, P <.0001) predicted mortality. Peak VO2 predicted mortality independently of age, NYHA class, and left ventricular ejection fraction. A subgroup of 12 patients with dynamic left ventricular outflow tract obstruction during stress had an excellent outcome, with a 100% survival at the end of follow-up (mean 16 +/- 7 mo, range 12-39 mo). CONCLUSIONS: The prognosis in elderly patients with CHF is poor. Valid exercise testing results can be obtained in more than 50% of elderly patients with CHF. NYHA class and peak VO2 are the strongest prognostic factors in this population.     

Depressed low frequency power of heart rate variability as an independent predictor of sudden death in chronic heart failure.

AIMS: Identification of patients with chronic heart failure at risk for sudden death remains difficult. We sought to assess the prognostic value for all-cause and sudden death of time and frequency domain measures of heart rate variability in chronic heart failure. METHODS AND RESULTS: We prospectively enrolled 190 patients with chronic heart failure in sinus rhythm, mean age 61+/-12 years, 109 (57.4%) in NYHA class II and 81 (42.6%) in classes III or IV, mean cardiothoracic ratio 57.6+/-6.4% and mean left ventricular ejection fraction 28.2+/-8.8%, 85 (45%) with ischaemic and 105 (55%) with idiopathic dilated cardiomyopathy. Time and frequency domain measures of heart rate variability were obtained from 24 h Holter ECG recordings, spectral measures were averaged for calculation of daytime (1000h-1900h) and night-time (2300h-0600h) values. During follow-up (22+/-18 months), 55 patients died, 21 of them suddenly and two presented with a syncopal spontaneous sustained ventricular tachycardia. In multivariate analysis, independent predictors for all-cause mortality were: ischaemic heart disease, cardiothoracic ratio > or =60% and standard deviation of all normal RR intervals <67 ms (RR = 2.5, 95% CI 1.5-4.2). Independent predictors of sudden death were: ischaemic heart disease and daytime low frequency power <3.3 ln (ms(2)) (RR = 2.8, 95% CI 1.2-8.6). CONCLUSION: Depressed heart rate variability has independent prognostic value in patients with chronic heart failure; spectral analysis identifies an increased risk for sudden death in these patients.     

Symptoms in patients with heart failure are prognostic predictors: insights from COMET

BACKGROUND: Although functional status, as assessed by the New York Heart Association classification, is known to be a powerful prognostic marker in chronic heart failure (CHF), the significance of individual symptoms such as breathlessness and fatigue are unknown. OBJECTIVE: To assess the relative importance of self-reported severity of symptoms as predictors of outcomes in CHF. METHODS AND RESULTS: All 3029 patients randomized in the Carvedilol or Metoprolol European Trial (ie, COMET) study were included in the analysis. Mean follow-up was 58 months. Symptoms were assessed by 5-point scales. In a univariate analysis, worse scores for breathlessness, orthopnea and fatigue were all significantly related to increased mortality (all P < .0001) and development of worsening heart failure. In a multivariate Cox regression analysis including 16 baseline covariates, only the symptom of breathlessness remained significantly related to mortality (risk ratio [RR] 1.14 per unit: 95% CI 1.04-1.26; P = .01). Fatigue, but not breathlessness, remained a significant predictor for developing worsening heart failure (RR 1.09 per unit; 95% CI 1.02-1.18; P = .02). CONCLUSIONS: Fatigue and breathlessness, common symptoms in CHF, have important and independent long-term prognostic implications. Accordingly, symptoms need to be effectively evaluated not only because symptom alleviation is a target for treatment, but also because they guide prognosis in patients with CHF.     

Predictors of congestive heart failure mortality in elderly people from the general population

Congestive heart failure (CHF) is highly prevalent in the elderly. The aim of this study was to identify the predictors of CHF mortality in patients over 65 years of age who were free of CHF at initial screening. A total of 3,282 elderly subjects were recruited in a population-based frame and 12-year events were recorded. Continuous items were divided into tertiles and for each tertile adjusted the relative risk (RR) with 95% confidence intervals (CI) was derived in both genders from multivariate Cox analysis of CHF mortality. Age > or = 72 years ([RR]: 2.24; 95% CI 1.56 - 3.24), male gender ([RR]: 1.4; 95%CI 1.02 - 1.76), clinical history of coronary artery disease ([RR]: 1.25; 95% CI 1.02 - 1.76), pulse pressure > or = 79 mmHg ([RR]: 1.33; 95% CI 1.03 - 1.87), heart rate > or = 81 bpm ([RR]: 1.32; 95% CI 1.10 - 1.96), atrial fibrillation ([RR]: 1.82; 95% CI 1.18 - 2.81), left ventricular hypertrophy ([RR]: 1.42; 95% CI 1.01 - 2.02), diabetes ([RR]: 1.35; 95% CI 1.02 - 1.78), vital capacity < or = 81% of the theoretical value ([RR]: 2.50; 95% CI 1.88 - 3.32), forced expiratory volume in 1 second < or = 72% of the theoretical value ([RR]: 2.02; 95% CI 1.55 - 2.72) and serum sodium level < or = 139 mmol/L ([RR]: 1.95; 95% CI 1.44 - 2.63) predicted CHF mortality. This model is able to identify elderly people at increased risk of death from CHF.     

Chronic kidney disease: an independent risk factor of all-cause mortality for elderly Chinese patients with chronic heart failure

Objective

To evaluate the prognostic value of chronic kidney disease (CKD) in elderly Chinese patients with chronic heart failure (CHF).

Methods

The study consisted of 327 elderly patients with CHF. All-cause mortality was chosen as an endpoint over the median follow-up period of 345 days. Cox regression analysis was used to identify the risk factors of mortality.

Results

The median age of the entire cohort was 85 years (60–100 years). The mortality for 168 elderly patients with CHF and CKD (51.4% of entire cohort) was 39.9% (67 deaths), which was higher than the mortality for CHF patients without CKD [25.2% (40/159 deaths)] and the mortality for entire cohort with CHF [32.7% (107/327 deaths)]. The Cox regression analysis showed that old age [hazard ratio (HR): 1.033; 95% confidence interval (95% CI): 1.004–1.064], CKD (HR: 1.705; 95% CI: 1.132–2.567), CHF New York Heart Association (NYHA) class IV (HR: 1.913; 95% CI: 1.284–2.851), acute myocardial infarction (AMI) (HR: 1.696; 95% CI: 1.036–2.777), elevated resting heart rate (HR: 1.021; 95% CI: 1.009–1.033), and decreased plasma albumin (HR: 0.883; 95% CI: 0.843–0.925) were independent risk factors of mortality for elderly patients with CHF.

Conclusions

CKD was an independent risk factor of mortality for elderly Chinese patients with CHF.     

Prognostic significance of circadian variability of RR and QT intervals and QT dynamicity in patients with chronic heart failure

BACKGROUND: In patients with chronic heart failure (CHF), circadian variability of RR and QT intervals may be altered because of neurohumoral activation and functional and structural remodeling of the heart. OBJECTIVE: The aim of this study was to evaluate the prognostic significance of circadian variability of the RR and QT intervals and QT dynamicity (QT/RR slope) in CHF patients. METHODS: We prospectively enrolled 121 patients with stable CHF in sinus rhythm (age 67 +/- 14 years, mean +/- SD; range 34 to 87 years). The RR, QT, and rate-corrected QT (QTc) intervals and the QT/RR slope measured from 24-hour Holter electrocardiogram were fitted by cosine curves. RESULTS: During the follow-up period of 34 +/- 17 months, 40 (33%) patients died of cardiac causes, 10 of which were sudden. All patients showed significant circadian rhythms in the RR, QT, and QTc intervals and the QT/RR slope by cosine-curve fitting. In addition to the expected higher heart rate, longer QT interval, and steeper QT/RR slope, we found that patient who died of cardiac causes had reduced circadian variability of QT interval (10 +/- 10 ms vs 21 +/- 13 ms) and a later maximum RR interval (4.1 +/- 0.9 AM vs 2.3 +/- 2.1 AM) compared with survivors, among many other statistically significant circadian parameter differences. These 2 parameters were independent predictors of cardiac death in multivariate Cox proportional hazards regression analysis. CONCLUSION: Circadian variability analyses of Holter-derived RR and QT intervals may provide prognostic information beyond that provided by 24-hour averages of these parameters.