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Hypertensive pregnancy disorders are a leading cause of perinatal and maternal morbidity and mortality. Heart rate variability (HRV), blood pressure variability (BPV), and baroreflex sensitivity (BRS) are relevant predictors of cardiovascular risk in humans. The aim of the study was to evaluate whether HRV, BPV, and BRS differ between distinct hypertensive pregnancy disorders. Continuous heart rate and blood pressure recordings were performed in 80 healthy pregnant women as controls (CON), 19 with chronic hypertension (CH), 18 with pregnancy-induced hypertension (PIH), and 44 with pre-eclampsia (PE). The data were assessed by time and frequency domain analysis, nonlinear dynamics, and BRS. BPV is markedly altered in all three groups with hypertensive disorders compared to healthy pregnancies, whereby changes were most pronounced in PE patients. Interestingly, this increase in PE patients did not lead to elevated spontaneous baroreflex events, while BPV changes in both the other hypertensive groups were paralleled by alterations in baroreflex parameters. The HRV is unaltered in CH and PE but significantly impaired in PIH. We conclude that parameters of the HRV, BPV, and BRS differ between various hypertensive pregnancy disorders. Thus, distinct clinical manifestations of hypertension in pregnancy have different pathophysiological, regulatory, and compensatory mechanisms
Observational data of natural systems, as measured in medical measurements are typically quite different from those obtained in laboratories. Due to the peculiarities of these data, wellknown characteristics, such as power spectra or fractal dimension, often do not provide a suitable description. To study such data, we present here some measures of complexity, which are basing on symbolic dynamics. Firstly, a motivation for using symbolic dynamics and measures of complexity in data analysis based on the logistic map is given and next, two applications to medical data are shown. We demonstrate that symbolic dynamics is a useful tool for the risk assessment of patients after myocardial infarction as well as for the evaluation of th e architecture of human cancellous bone.
Baroreflex sensitivity (BRS) is an important parameter in the classification of patients with reduced left ventricular function. This study aimed at investigating BRS in patients with dilated cardiomyopathy (DCM) and in healthy subjects (controls), as well as comparing the values of BRS parameters with parameters of heart rate variability (HRV) and blood pressure variability (BPV). ECG, continuous blood pressure and respiration curves were recorded for 30 min in 27 DCM patients and 27 control subjects. The Dual Sequence Method (DSM) includes the analysis of spontaneous fluctuations in systolic blood pressure and the corresponding beat-to-beat intervals of heart rate to estimate bradycardic, opposite tachycardic and delayed baroreflex fluctuations. The number of systolic blood pressure/beat-to- beat interval fluctuations in DCM patients was reduced in comparison with controls (DCM patients: male, 154.4+/-93.9 ms/ mmHg; female, 93.7+/-40.5 ms/mmHg; controls: male, 245.5+/-112.9 ms/mmHg; female, 150.6+/-55.8 ms/mmHg, P<0.05). The average slope in DCM patients was lower than in controls (DCM, 5.3+/-1.9 ms/mmHg; controls, 8.0+/-5.4 ms/mmHg; P<0.05). Discriminant function analysis showed that, in the synchronous range of the standard sequence method, the DCM and control groups could be discriminated to only 76% accuracy, whereas the DSM gave an improved accuracy of 84%. The combination of six parameters of HRV, BPV and DSM gives an accuracy of classification of 96%, whereas six parameters of HRV and BPV could separate the two groups to only 88% accuracy. Thus the DSM leads to an improved characterization of autonomous regulation in order to differentiate between DCM patients and healthy subjects. BRS in DCM patients is significantly reduced and apparently less effective.
In the modern industrialized countries every year several hundred thousands of people die due to the sudden cardiac death. The individual risk for this sudden cardiac death cannot be defined precisely by common available, non-invasive diagnostic tools like Holter-monitoring, highly amplified ECG and traditional linear analysis of heart rate variability (HRV). Therefore, we apply some rather unconventional methods of nonlinear dynamics to analyse the HRV. Especially, some complexity measures that are basing on symbolic dynamics as well as a new measure, the renormalized entropy, detect some abnormalities in the HRV of several patients who have been classified in the low risk group by traditional methods. A combination of these complexity measures with the parameters in the frequency domain seems to be a promising way to get a more precise definition of the individual risk. These findings have to be validated by a representative number of patients.
Context: Placental and circulatory soluble fms-like tyrosine kinase 1 (sFlt1) has proven to be elevated in pregnant women with preeclampsia, a disease characterized by hypertension, proteinuria, and endothelial dysfunction. Recent studies also demonstrated an autoantibody against the angiotensin II type 1 (AT1) receptor (AT1-AA) in that disease. Objective: Both factors are discussed as key players in the etiology of preeclampsia. However, it has not yet been clarified whether these two circulating factors correlate and whether synergy determines the severity of pathology. Design: AT1-AA was retrospectively determined by a bioassay and sFlt1 by an ELISA. Patients: Serum from second-trimester pregnancies with normal or abnormal uterine perfusion and in women at term with or without pregnancy pathology was analyzed. Results: Most of the preeclamptic patients were characterized by high sFlt1 levels and the presence of AT1-AA, although the agonistic effects of the antibody did not correlate with the sFlt1 concentrations (P = 0.85). Although AT1- AA was also detected in second-trimester pregnancies evidencing abnormal uterine perfusion without later pathology, sFlt1 was not significantly elevated in these pregnancies, compared with those with normal uterine perfusion. However, whereas women with abnormal perfusion and later pregnancy pathology did not differ in AT1-AA, compared with those with normal outcome, sFlt1 was significantly increased. Again, the two factors did not correlate (P = 0.15). Conclusions: We conclude that AT1-AA bioactivity and sFlt1 concentrations do not correlate, are not mutually dependent, and are thus probably involved in distinct pathogenetic mechanisms. Both factors in combination may not be causative for the early impaired trophoblast invasion and pathological uterine perfusion
Despite many previous Studies on the association between hyperthyroidism and the hyperadrenergic state, controversies still exist. Detrended fluctuation analysis (DFA) is a well recognized method in the nonlinear analysis of heart rate variability (HRV), and it has physiological significance related to the autonomic nervous system. In particular, an increased short-term scaling exponent alpha 1 calculated from DFA is associated with both increased sympathetic activity and decreased vagal activity. No study has investigated the DFA of HRV in hyperthyroidism. This study was designed to assess the sympathovagal balance in hyperthyroidism. We performed the DFA along with the linear analysis of HRV in 36 hyperthyroid Graves' disease patients (32 females and 4 males; age 30 +/- 1 years, means +/- SE) and 36 normal controls matched by sex, age and body mass index. Compared with the normal controls, the hyperthyroid patients revealed a significant increase (P < 0.001) in alpha 1 (hyperthyroid 1.28 +/- 0.04 versus control 0.91 +/- 0.02), long-term scaling exponent alpha 2 (1.05 +/- 0.02 versus 0.90 +/- 0.01), overall scaling exponent alpha (1.11 +/- 0.02 versus 0.89 +/- 0.01), low frequency power in normalized units (LF%) and the ratio of low frequency power to high frequency power (LF/HF); and a significant decrease (P < 0.001) in the standard deviation of the R-R intervals (SDNN) and high frequency power (HF). In conclusion, hyperthyroidism is characterized by concurrent sympathetic activation and vagal withdrawal. This sympathovagal imbalance state in hyperthyroidism helps to explain the higher prevalence of atrial fibrillation and exercise intolerance among hyperthyroid patients.
The incidence of cardiovascular diseases increases with the growth of the human population and an aging society, leading to very high expenses in the public health system. Therefore, it is challenging to develop sophisticated methods in order to improve medical diagnostics. The question whether the normal heart rate is chaotic or not is an attempt to elucidate the underlying mechanisms of cardiovascular dynamics and therefore a highly controversial topical challenge. In this contribution we demonstrate that linear and nonlinear parameters allow us to separate completely the data sets of the three groups provided for this controversial topic in nonlinear dynamics. The question whether these time series are chaotic or not cannot be answered satisfactorily without investigating the underlying mechanisms leading to them. We give an example of the dominant influence of respiration on heart beat dynamics, which shows that observed fluctuations can be mostly explained by respiratory modulations of heart rate and blood pressure (coefficient of determination: 96%). Therefore, we recommend reformulating the following initial question: "Is the normal heart rate chaotic?" We rather ask the following: " Is the normal heart rate 'chaotic' due to respiration?"
The analysis of baroreflex sensitivity (BRS) and heart rate variability (HRV) leads to additional insights into patients' prognosis after cardiovascular events. The following study was performed to assess the differences in the post-operative recovery of autonomic regulation after mitral valve (MV) and aortic valve (AV) surgery with a heart lung machine. Among the 43 consecutive male patients enrolled in a prospective study, 26 underwent isolated AV surgery and 17 isolated MV surgery. Blood pressure as well as ECG signals were recorded the day before, 24 hours after and one week after surgery. BRS was calculated according to the dual sequence method, and HRV was calculated using standard linear as well as nonlinear parameters. There were no major differences between the two groups in the pre-operative values. At 24 hours a comparable depression of HRV and BRS in both groups was observed, while at 7 days there was partial recovery in AV patients, which was absent in MV patients: p(AV versus MV) < 0.001. While the response of the autonomic system to surgery is similar in AV and MV patients, there is obviously a decreased ability to recover in MV patients, probably attributed to traumatic lesions of the autonomic nervous system by opening the atria. Ongoing research is required for further clarification of the pathophysiology of this phenomenon and to establish strategies to restore autonomic function.
Objectives: Scoring sleep visually based on polysomnography is an important but time-consuming element of sleep medicine. Where-as computer software assists human experts in the assignment of sleep stages to polysomnogram epochs, their performance is usually insufficient. This study evaluates the possibility to fully automatize sleep staging considering the reliability of the sleep stages available from human expert sleep scorers. Methods: We obtain features from EEG, ECG and respiratory signals of polysomnograms from ten healthy subjects. Using the sleep stages provided by three human experts, we evaluate the performance of linear discriminant analysis on the entire polysomnogram and:only on epochs where the three experts agree in their-sleep stage scoring. Results: We show that in polysomnogram intervals, to which all three scorers assign the same sleep stage, our algorithm achieves 90% accuracy. This high rate of agreement with the human experts is accomplished with only a small set of three frequency features from the EEG. We increase-the performance to 93% by including ECG and respiration features. In contrast, on intervals of ambiguous sleep stage, the sleep stage classification obtained from our algorithm, agrees with the human consensus scorer in approximately 61%. Conclusions: These findings suggest that machine classification is highly consistent with human sleep staging and that error in the algorithm's assignments is rather a problem of lack of well-defined criteria for human experts to judge certain polysomnogram epochs than an insufficiency of computational procedures
Atrial natriuretic peptides (ANP) and brain natriuretic peptides (BNP) are powerful neurohormonal indicators of left-ventricular function and prognosis in heart failure (HF). Chagas disease (CD) caused by the protozoan Trypanosoma cruzi. remains a major cause of HF in Latin America. We assessed whether the plasma concentration of the third natriuretic peptide, C-type natnuretic peptide (CNP), also has diagnostic and prognostic properties in patients with CD or other dilated cardiomyopathies (DCM). Blood samples were obtained from 66 patients with CD, 50 patients with DCM from other causes, and 30 gender- and age-matched healthy subjects. Patients were subdivided according to the New York Heart Association (NYHA) class. The CNP concentration was determined by radioimmunoassay (Immundiagnostik, Bensheim, Germany). The main duration of follow-up was 31.4 months (range 13 to 54 months), 19 patients had died and 11 patients received a heart transplant. CNP concentrations were only significantly altered in patients with DCM or CD of the NYHA classes III and IV (P < 0.05). The Pearson correlation of echocardiographic data with CNP revealed an association only with the left-ventricular end systolic volume (P = 0.03) in patients with DCM. Furthermore, CNP did not predict mortality or the necessity for heart transplant. Our data are the first to demonstrate the raised levels of the third natriuretic peptide CNP in CD and other DCM Whereas ANP and BNP have a high predictive value for mortality in both diseases, CNP is without any predictive potency.
Standard time and frequency parameters of heart rate variability (HRV) describe only linear and periodic behaviour, whereas more complex relationships cannot be recognised. A method that may be capable of assessing more complex properties is the non-linear measure of 'renormalised entropy.' A new concept of the method, RE(AR), has been developed, based on a non-linear renormalisation of autoregressive spectral distributions. To test the hypothesis that renormalised entropy may improve the result of high-risk stratification after myocardial infarction, it is applied to a clinical pilot study (41 subjects) and to prospective data of the St George's Hospital post- infarction database (572 patients). The study shows that the new RE(AR) method is more reproducible and more stable in time than a previously introduced method (p<0.001). Moreover, the results of the study confirm the hypothesis that on average, the survivors have negative values of RE(AR) (-0.11+/-0.18), whereas the non-survivors have positive values (0.03+/-0.22, p<0.01). Further, the study shows that the combination of an HRV triangular index and RE(AR) leads to a better prediction of sudden arrhythmic death than standard measurements of HRV. In summary, the new RE(AR) method is an independent measure in HRV analysis that may be suitable for risk stratification in patients after myocardial infarction.
Ventricular tachycardia or fibrillation (VT-VF) as fatal cardiac arrhythmias are the main factors triggering sudden cardiac death. The objective of this study is to find early signs of sustained VT-VF in patients with an implanted cardioverter-defibrillator (ICD). These devices are able to safeguard patients by returning their hearts to a normal rhythm via strong defibrillatory shocks; additionally, they store the 1000 beat-to-beat intervals immediately before the onset of a life-threatening arrhythmia. We study these 1000 beat-to-beat intervals of 17 chronic heart failure ICD patients before the onset of a life-threatening arrhythmia and at a control time, i.e., without a VT-VF event. To characterize these rather short data sets, we calculate heart rate variability parameters from the time and frequency domain, from symbolic dynamics as well as the finite-time growth rates. We find that neither the time nor the frequency domain parameters show significant differences between the VT-VF and the control time series. However, two parameters from symbolic dynamics as well as the finite-time growth rates discriminate significantly both groups. These findings could be of importance in algorithms for next generation ICD's to improve the diagnostics and therapy of VT-VF.
The main intention of this contribution is to discuss different nonlinear approaches to heart rate and blood pressure variability analysis for a better understanding of the cardiovascular regulation. We investigate measures of complexity which are based on symbolic dynamics, renormalised entropy and the finite time growth rates. The dual sequence method to estimate the baroreflex sensitivity and the maximal correlation method to estimate the nonlinear coupling between time series are employed for analysing bivariate data. The latter appears to be a suitable method to estimate the strength of the nonlinear coupling and the coupling direction. Heart rate and blood pressure data from clinical pilot studies and from very large clinical studies are analysed. We demonstrate that parameters from nonlinear dynamics are useful for risk stratification after myocardial infarction, for the prediction of life-threatening cardiac events even in short time series, and for modelling the relationship between heart rate and blood pressure regulation. These findings could be of importance for clinical diagnostics, in algorithms for risk stratification, and for therapeutic and preventive tools of next generation implantable cardioverter defibrillators.
The investigation of foetal reaction to internal and external conditions and stimuli is an important tool in the characterization of the developing neural integration of the foetus. An interesting example of this is the study of the interrelationship between the foetal and the maternal heart rate. Recent studies have shown a certain likelihood of occasional heart rate synchronization between mother and foetus. In the case of respiratory-induced heart rate changes, the comparison with maternal surrogates suggests that the evidence for detected synchronization is largely statistical and does not result from physiological interaction. Rather, they simply reflect a stochastic, temporary stability of two independent oscillators with time-variant frequencies. We reanalysed three datasets from that study for a more local consideration. Epochs of assumed synchronization associated with short-term regulation of the foetal heart rate were selected and compared with synchronization resulting from white noise instead of the foetal signal. Using data-driven modelling analysis, it was possible to identify the consistent influence of the heartbeat duration of maternal beats preceding the foetal beats during epochs of synchronization. These maternal beats occurred approximately one maternal respiratory cycle prior to the affected foetal beat. A similar effect could not be found in the epochs without synchronization. Simulations based on the fitted models led to a higher likelihood of synchronization in the data segments with assumed foetal-maternal interaction than in the segment without such assumed interaction. We conclude that the data-driven model-based analysis can be a useful tool for the identification of synchronization.
Ventricular tachycardia or fibrillation (VT) as fatal cardiac arrhythmias are the main factors triggering sudden cardiac death. The objective of this recurrence quantification analysis approach is to find early signs of sustained VT in patients with an implanted cardioverter-defibrillator (ICD). These devices are able to safeguard patients by returning their hearts to a normal rhythm via strong defibrillatory shocks; additionally, they are able to store at least 1000 beat-to-beat intervals immediately before the onset of a life-threatening arrhythmia. We study the