Variabilität und Interaktion von Herzfrequenz und Blutdruck in der normotensiven und hypertensiven Schwangerschaft

During pregnancy, maternal cardiovascular regulation adapts to the changing support requirements for mother and child. The variability and interactions of heart rate and blood pressure were investigated to quantify these alterations. Within the framework of a clinical study, tests were conducted to determine how the behaviour of these variability parameters changes in pathological pregnancies and hence whether pre-eclampsia, the severe hypertensive pregnancy disorder, can be forecasted by their analysis. To estimate the complexity of heart rate and blood pressure time series, a method was developed that is based on the compressibility of the time series. To analyze the interdependence of these two measures a method using the concept of symbolic dynamics was developed. In comparison to standard parameters of heart rate and blood pressure variability, the new methods provide additional information and consider non-linear features. The clinical study showed that cardiovascular regulation in normotensive pregnancies is significantly changed when compared with that found in non- pregnant women, pregnancies with chronic hypertension, patients with pregnancy- induced hypertension and pregnancies with pre-eclampsia. Furthermore, significant changes during the second half of gestation could be shown in normotensive and chronic hypertensive pregnancies. The variability measures of normotensive pregnancies with pre-eclamptic outcome were significantly changed relative to those of normotensive pregnancies with normal outcome and indicate an early altered cardiovascular regulation. Using a multivariate statistical approach a classifier was developed that combines four variability parameters and enables pre-eclampsia forecasting with a specificity of 100 % and a sensitivity of about 60 %. This is a considerable improvement over ultrasound Doppler blood flow measurement in the uterine arteries, the current state of the art technique (specificity: 100 %; sensitivity: 20 %).Während der Schwangerschaft wird die maternale kardiovaskuläre Regulation auf die Bedürfnisse der Versorgung von Mutter und Kind angepasst. Die Analyse der Variabilität und Interaktion von Herzfrequenz und Blutdruck erlaubt eine Quantifizierung dieser Veränderungen. Im Rahmen einer klinischen Studie wurde geprüft, wie sich das Verhalten der Variabilitätsparameter bei pathologischen Schwangerschaftsverläufen ändert, und ob sich somit die besonders schwerwiegende hypertensive Schwangerschaftserkrankung Präeklampsie vorhersagen lässt. Zur Abschätzung der Komplexität der Herzfrequenz- und Blutdruckzeitreihen wurde ein Verfahren entwickelt, das auf der Komprimierbarkeit der Zeitreihen beruht. Für die erweiterte Interaktionsanalyse beider Messgrößen wurde ein auf dem Konzept der symbolischen Dynamik basierendes Verfahren eingeführt. Die neuen Methoden liefern im Vergleich zu den Standardparametern der Herzfrequenz- und Blutdruckvariabilität zusätzliche Informationen, wobei gleichzeitig nichtlineare Verhaltensweisen berücksichtigt werden. Die klinische Studie zeigte, dass das kardiovaskuläre Regulationsverhalten von normotensiven Schwangeren im Vergleich zu Nichtschwangeren, Schwangeren mit chronischer Hypertonie, Patientinnen mit schwangerschaftsinduzierter Hypertonie und Schwangeren mit Präeklampsie signifikant verändert ist. Des weiteren konnten bei normotensiven und chronisch hypertensiven Schwangeren signifikante Veränderungen im Verlauf der zweiten Schwangerschaftshälfte gezeigt werden. Die Variabilitätsparameter von normotensiven Schwangeren mit präeklamptischen Ausgang waren gegenüber denen von normotensiven Schwangeren mit komplikationsfreiem Ausgang signifikant verschieden und deuten auf ein frühzeitig verändertes Regulationsverhalten bei Schwangeren mit präeklamptischen Ausgang. Mit einem multivariaten statistischen Ansatz konnte aus der Kombination von vier Variabilitätsparametern ein Klassifizierer erstellt werden, der eine Früherkennung von Präeklampsie mit einer Spezifität von 100 % bei einer gleichzeitigen Sensitivität von ca. 60 % erlaubt, was einer deutlichen Verbesserung gegenüber dem derzeitigen Standardverfahren, der Ultraschall-Doppler-Blutflussmessung in den Uterinarterien (Spezifität: 100 %; Sensitivität: 20 %), entspricht

T Wave Amplitude Correction of QT Interval Variability for Improved Repolarization Lability Measurement

Objectives: The inverse relationship between QT interval variability (QTV) and T wave amplitude potentially confounds QT variability assessment. We quantified the influence of the T wave amplitude on QTV in a comprehensive dataset and devised a correction formula. Methods: Three ECG datasets of healthy subjects were analyzed to model the relationship between T wave amplitude and QTV. To derive a generally valid correction formula, linear regression analysis was used. The proposed correction formula was applied to patients enrolled in the Evaluation of Defibrillator in Non-Ischemic Cardiomyopathy Treatment Evaluation trial (DEFINITE) to assess the prognostic significance of QTV for all-cause mortality in patients with non-ischemic dilated cardiomyopathy. Results: A strong inverse relationship between T wave amplitude and QTV was demonstrated, both in healthy subjects (R2 = 0.68, p < 0.001) and DEFINITE patients (R2 = 0.20, p < 0.001). Applying the T wave amplitude correction to QTV achieved 2.5-times better group discrimination between patients enrolled in the DEFINITE study and healthy subjects. Kaplan-Meier estimator analysis showed that T wave amplitude corrected QTVi is inversely related to survival (p < 0.01) and a significant predictor of all-cause mortality. Conclusion: We have proposed a simple correction formula for improved QTV assessment. Using this correction, predictive value of QTV for all-cause mortality in patients with non-ischemic cardiomyopathy has been demonstrated

Scaling graphs of heart rate time series in athletes demonstrate the VLF, LF and HF regions

Scaling analysis of heart rate time series has emerged as an useful tool for assessment of autonomic cardiac control. We investigate the heart rate time series of ten athletes (five males and five females), by applying detrended fluctuation analysis (DFA). High resolution ECGs are recorded under standardized resting conditions over 30 minutes and subsequently heart rate time series are extracted and artefacts filtered. We find three distinct regions of scale-invariance, which correspond to the well-known VLF, LF, and HF bands in the power spectra of heart rate variability. The scaling exponents alpha are alphaHF: 1.15 [0.96-1.22], alphaLF: 0.68 [0.57-0.84], alphaVLF: 0.83[0.82-0.99]; p<10^-5). In conclusion, DFA scaling exponents of heart rate time series should be fitted to the VLF, LF, and HF ranges, respectively

Conventional QT variability measurement vs. template matching techniques: comparison of performance using simulated and real ECG

Increased beat-to-beat variability in the QT interval (QTV) of ECG has been associated with increased risk for sudden cardiac death, but its measurement is technically challenging and currently not standardized. The aim of this study was to investigate the performance of commonly used beat-to-beat QT interval measurement algorithms. Three different methods (conventional, template stretching and template time shifting) were subjected to simulated data featuring typical ECG recording issues (broadband noise, baseline wander, amplitude modulation) and real short-term ECG of patients before and after infusion of sotalol, a QT interval prolonging drug. Among the three algorithms, the conventional algorithm was most susceptible to noise whereas the template time shifting algorithm showed superior overall performance on simulated and real ECG. None of the algorithms was able to detect increased beat-to-beat QT interval variability after sotalol infusion despite marked prolongation of the average QT interval. The QTV estimates of all three algorithms were inversely correlated with the amplitude of the T wave. In conclusion, template matching algorithms, in particular the time shifting algorithm, are recommended for beat-to-beat variability measurement of QT interval in body surface ECG. Recording noise, T wave amplitude and the beat-rejection strategy are important factors of QTV measurement and require further investigation.Mathias Baumert, Vito Starc and Alberto Port

Baroreflex Coupling Assessed by Cross-Compression Entropy

Estimating interactions between physiological systems is an important challenge in modern biomedical research. Here, we explore a new concept for quantifying information common in two time series by cross-compressibility. Cross-compression entropy (CCE) exploits the ZIP data compression algorithm extended to bivariate data analysis. First, time series are transformed into symbol vectors. Symbols of the target time series are coded by the symbols of the source series. Uncoupled and linearly coupled surrogates were derived from cardiovascular recordings of 36 healthy controls obtained during rest to demonstrate suitability of this method for assessing physiological coupling. CCE at rest was compared to that of isometric handgrip exercise. Finally, spontaneous baroreflex interaction assessed by CCEBRS was compared between 21 patients suffering from acute schizophrenia and 21 matched controls. The CCEBRS of original time series was significantly higher than in uncoupled surrogates in 89% of the subjects and higher than in linearly coupled surrogates in 47% of the subjects. Handgrip exercise led to sympathetic activation and vagal inhibition accompanied by reduced baroreflex sensitivity. CCEBRS decreased from 0.553 ± 0.030 at rest to 0.514 ± 0.035 during exercise (p &lt; 0.001). In acute schizophrenia, heart rate, and blood pressure were elevated. Heart rate variability indicated a change of sympathovagal balance. The CCEBRS of patients with schizophrenia was reduced compared to healthy controls (0.546 ± 0.042 vs. 0.507 ± 0.046, p &lt; 0.01) and revealed a decrease of blood pressure influence on heart rate in patients with schizophrenia. Our results indicate that CCE is suitable for the investigation of linear and non-linear coupling in cardiovascular time series. CCE can quantify causal interactions in short, noisy and non-stationary physiological time series

L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging

Human sleep is cyclical with a period of approximately 90 minutes, implying long temporal dependency in the sleep data. Yet, exploring this long-term dependency when developing sleep staging models has remained untouched. In this work, we show that while encoding the logic of a whole sleep cycle is crucial to improve sleep staging performance, the sequential modelling approach in existing state-of-the-art deep learning models are inefficient for that purpose. We thus introduce a method for efficient long sequence modelling and propose a new deep learning model, L-SeqSleepNet, which takes into account whole-cycle sleep information for sleep staging. Evaluating L-SeqSleepNet on four distinct databases of various sizes, we demonstrate state-of-the-art performance obtained by the model over three different EEG setups, including scalp EEG in conventional Polysomnography (PSG), in-ear EEG, and around-the-ear EEG (cEEGrid), even with a single EEG channel input. Our analyses also show that L-SeqSleepNet is able to alleviate the predominance of N2 sleep (the major class in terms of classification) to bring down errors in other sleep stages. Moreover the network becomes much more robust, meaning that for all subjects where the baseline method had exceptionally poor performance, their performance are improved significantly. Finally, the computation time only grows at a sub-linear rate when the sequence length increases.Comment: 9 pages, 4 figures, updated affiliation

Nocturnal hypoxemic burden and micro- and macrovascular disease in patients with type 2 diabetes

Background Micro- and macrovascular diseases are common in patients with type 2 diabetes mellitus (T2D) and may be partly caused by nocturnal hypoxemia. The study aimed to characterize the composition of nocturnal hypoxemic burden and to assess its association with micro- and macrovascular disease in patients with T2D. Methods This cross-sectional analysis includes overnight oximetry from 1247 patients with T2D enrolled in the DIACORE (DIAbetes COhoRtE) study. Night-time spent below a peripheral oxygen saturation of 90% (T90) as well as T90 associated with non-specific drifts in oxygen saturation (T90non − specific), T90 associated with acute oxygen desaturation (T90desaturation) and desaturation depths were assessed. Binary logistic regression analyses adjusted for known risk factors (age, sex, smoking status, waist-hip ratio, duration of T2D, HbA1c, pulse pressure, low-density lipoprotein, use of statins, and use of renin-angiotensin-aldosterone system inhibitors) were used to assess the associations of such parameters of hypoxemic burden with chronic kidney disease (CKD) as a manifestation of microvascular disease and a composite of cardiovascular diseases (CVD) reflecting macrovascular disease. Results Patients with long T90 were significantly more often affected by CKD and CVD than patients with a lower hypoxemic burden (CKD 38% vs. 28%, p < 0.001; CVD 30% vs. 21%, p < 0.001). Continuous T90desaturation and desaturation depth were associated with CKD (adjusted OR 1.01 per unit, 95% CI [1.00; 1.01], p = 0.008 and OR 1.30, 95% CI [1.06; 1.61], p = 0.013, respectively) independently of other known risk factors for CKD. For CVD there was a thresholdeffect, and only severly and very severly increased T90non−specific was associated with CVD ([Q3;Q4] versus [Q1;Q2], adjusted OR 1.51, 95% CI [1.12; 2.05], p = 0.008) independently of other known risk factors for CVD. Conclusion While hypoxemic burden due to oxygen desaturations and the magnitude of desaturation depth were significantly associated with CKD, only severe hypoxemic burden due to non-specific drifts was associated with CVD. Specific types of hypoxemic burden may be related to micro- and macrovascular disease

QT interval variability in body surface ECG: measurement, physiological basis, and clinical value: position statement and consensus guidance endorsed by the European Heart Rhythm Association jointly with the ESCWorking Group on Cardiac Cellular Electrophysiology

This consensus guideline discusses the electrocardiographic phenomenon of beat-to-beat QT interval variability (QTV) on surface electrocardiograms. The text covers measurement principles, physiological basis, and clinical value of QTV. Technical considerations include QT interval measurement and the relation between QTV and heart rate variability. Research frontiers of QTV include understanding of QTV physiology, systematic evaluation of the link between QTV and direct measures of neural activity, modelling of the QTV dependence on the variability of other physiological variables, distinction between QTV and general T wave shape variability, and assessing of the QTV utility for guiding therapy. Increased QTV appears to be a risk marker of arrhythmic and cardiovascular death. It remains to be established whether it can guide therapy alone or in combination with other risk factors. QT interval variability has a possible role in non-invasive assessment of tonic sympathetic activity