Characterization and interpretation of cardiovascular and cardiorespiratory dynamics in cardiomyopathy patients

Aplicat embargament des de la data de defensa fins el dia 20/5/2022The main objective of this thesis was to study the variability of the cardiac, respiratory and vascular systems through electrocardiographic (ECG), respiratory flow (FLW) and blood pressure (BP) signals, in patients with idiopathic (IDC), dilated (DCM), or ischemic (ICM) disease. The aim of this work was to introduce new indices that could contribute to characterizing these diseases. With these new indices, we propose methods to classify cardiomyopathy patients (CMP) according to their cardiovascular risk or etiology. In addition, a new tool was proposed to reconstruct artifacts in biomedical signals. From the ECG, BP and FLW signals, different data series were extracted: beat to beat intervals (BBI - ECG), systolic and diastolic blood pressure (SBP and DBP - BP), and breathing duration (TT - FLW). -Firstly, we propose a novel artifact reconstruction method applied to biomedical signals. The reconstruction process makes use of information from neighboring events while maintaining the dynamics of the original signal. The method is based on detecting the cycles and artifacts, identifying the number of cycles to reconstruct, and predicting the cycles used to replace the artifact segments. The reconstruction results showed that most of the artifacts were correctly detected, and physiological cycles were incorrectly detected as artifacts in fewer than 1% of the cases. The second part is related to the cardiac death risk stratification of patients based on their left ventricular ejection (LVEF), using the Poincaré plot analysis, and classified as low (LVEF > 35%) or high (LVEF = 35%) risk. The BBI, SBP, and IT series of 46 CMP patients were applied. The linear discriminant analysis and support vector machines (SVM) classification methods were used. When comparing low risk vs high risk, an accuracy of 98 12% was obtained. Our results suggest that a dysfunction in the vagal activity could prevent the body from correctly maintaining circulatory homeostasis Next, we studied cardio-vascular couplings based on heart rate (HRV) and blood pressure (BPV) variability analyses in order to introduce new indices for noninvasive risk stratification in IDC patients. The ECG and BP signals of 91 IDC patients, and 49 healthy subjects were used. The patients were stratified by their sudden cardiac death risk as: high risk (IDCHR), when after two years the subject either died or suffered complications, or low risk (IDCLR) otherwise. Several indices were extracted from the BBI and SBP, and analyzed using the segmented Poincaré plot analysis, the high-resolution joint symbolic dynamics, and the normalized short time partial directed coherence methods. SVM models were built to classify these patients based on their sudden cardiac death risk. The SVM IDCLR vs IDCHR model achieved 98 9% accuracy with an area under the curve (AUC) of 0.96. Our results suggest that IDCHR patients have decreased HRV and increased BPV compared to both the IDCLR patients and the control subjects, suggesting a decrease in their vagal activity and the compensation of sympathetic activity. Lastly, we analyzed the cardiorespiratory interaction associated with the systems related to ICM and DCM disease. We propose an analysis based on vascular activity as the input and output of the baroreflex response. The aim was to analyze the suitability of cardiorespiratory and vascular interactions for the classification of ICM and DCM patients. We studied 41 CMP patients and 39 healthy subjects. Three new sub-spaces were defined: 'up' for increasing values, 'down' for decreasing values, and 'no change' otherwise, and a three-dimensional representation was created for each sub-space that was characterized statistically and morphologically. The resulting indices were used to classify the patients by their etiology through SVM models achieving 92.7% accuracy for ICM vs DCM patients comparison. The results reflected a more pronounced deterioration of the autonomous regulation in DCM patients.El objetivo de esta tesis fue estudiar la variabilidad de los sistemas cardíaco, respiratorio y vascular a través de señales electrocardiográficas (ECG), de flujo respiratorio (FLW) y de presión arterial (BP), en pacientes con cardiopatía idiopática (IDC). dilatada (DCM) o isquémica (ICM). El objetivo de este trabajo fue introducir nuevos indices que contribuyan a caracterizar estas enfermedades. Proponemos métodos para clasificar pacientes con cardiomiopatía (CMP) de acuerdo con su riesgo cardiovascular o etiología. Además, se propuso una nueva herramienta para reconstruir artefactos en señales biomédicas. De las señales de ECG, BP y FLW, se extrajeron diferentes series temporales: intervalos latido-a-latido (BBI - ECG), presión arterial sistólica y diastólica (SBP y DBP - BP) y la duración de la respiración (TT - FLW). En primer lugar, proponemos un método de reconstrucción de artefactos aplicado a señales biomédicas. El proceso de reconstrucción usa la información de eventos vecinos manteniendo la dinámica de la señal. El método se basa en detectar ciclos y artefactos, en identificar el número de ciclos a reconstruir y en predecir los ciclos utilizados para reemplazar los artefactos. La mayoría de los artefactos probados fueron detectados y reconstruidos correctamente y los ciclos fisiológicos fueron detectados incorrectamente como artefactos en menos del 1% de los casos, La segunda parte está relacionada con la estratificación de riesgo de muerte cardiovascular en función de la fracción de eyección ventricular izquierda (FEVI), mediante el análisis de Poincaré, en bajo (FEVI > 35%) y alto riesgo (FEVI 5 35%). Se utilizaron las series BBI, SBP y TT de 46 pacientes con CMP. Se utilizaron para la clasificación el análisis discriminante lineal y las máquinas de soporte vectorial (SVM). Al comparar los pacientes de bajo y alto riesgo, se obtuvo una exactitud del 98%. Los resultados sugieren la disfunción de la actividad vagal en pacientes de alto riesgo. A continuación, estudiamos los acoplamientos cardiovasculares basados en el análisis de la variabilidad de la frecuencia cardiaca (HRV) y la presión arterial (BPV) para introducir nuevos índices de estratificación de riesgo en pacientes con IDC. Se utilizaron las señales de ECG y BP de 91 pacientes con IDC y 49 sujetos sanos. Los pacientes fueron estratificados por su riesgo cardíaco como: alto riesgo (IDCHR), cuando después de dos años el sujeto murió, o bajo riesgo (IDCLR) en otro caso. Se extrajeron indices utilizando el análisis de Poincaré segmentado, la dinámica simbólica articulada de alta resolución y la coherencia parcial dirigida a corto plazo normalizada. Se construyeron modelos SVM para clasificar a estos pacientes en función de su riesgo cardiovascular. El modelo IDCLR vs IDCHR logró una exactitud del 98% con un área bajo la curva de 0.96. Los resultados sugieren que los pacientes IDCHR tienen sus HRV y BPV disminuidos en comparación con los pacientes IDCLR, lo que sugiere una disminución en su actividad vagal y la compensación de la actividad simpática. Finalmente, analizamos la interacción cardiorrespiratoria asociada con los sistemas relacionados con ICM y DCM. Proponemos un análisis basado en la actividad vascular como entrada y salida de la respuesta baroreflectora. El objetivo fue analizar la capacidad de las interacciones cardiorrespiratorias y vasculares para la clasificación de pacientes con ICM y DCM. Estudiamos 41 pacientes con CMP y 39 sujetos sanos. Se definieron tres sub-espacios: 'up' para valores crecientes, 'down' para los decrecientes, y 'no-change' en otro caso, y se creó una representación tridimensional que se caracterizó estadística y morfológicamente. Los indices resultantes se usaron para clasificar a los pacientes por su etiología con modelos SVM que lograron una exactitud de 92% cuando los pacientes ICM y DCM fueron comparados. Los resultados reflejaron un deterioro más pronunciado de la regulación autónoma en pacientes con DCM.Postprint (published version

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

Multivariate assessment of linear and non-linear causal coupling pathways within the central-autonomic-network in patients suffering from schizophrenia

Im Bereich der Zeitreihenanalyse richtet sich das Interesse zunehmend darauf, wie Einblicke in die Interaktions- und Regulationsprozesse von pathophysiologischen- und physiologischen Zuständen erlangt werden können. Neuste Fortschritte in der nichtlinearen Dynamik, der Informationstheorie und der Netzwerktheorie liefern dabei fundiertes Wissen über Kopplungswege innerhalb (patho)physiologischer (Sub)Systeme. Kopplungsanalysen zielen darauf ab, ein besseres Verständnis dafür zu erlangen, wie die verschiedenen integrierten regulatorischen (Sub)Systeme mit ihren komplexen Strukturen und Regulationsmechanismen das globale Verhalten und die unterschiedlichen physiologischen Funktionen auf der Ebene des Organismus beschreiben. Insbesondere die Erfassung und Quantifizierung der Kopplungsstärke und -richtung sind wesentliche Aspekte für ein detaillierteres Verständnis physiologischer Regulationsprozesse. Ziel dieser Arbeit war die Charakterisierung kurzfristiger unmittelbarer zentral-autonomer Kopplungspfade (top-to-bottom und bottom to top) durch die Kopplungsanalysen der Herzfrequenz, des systolischen Blutdrucks, der Atmung und zentraler Aktivität (EEG) bei schizophrenen Patienten und Gesunden. Dafür wurden in dieser Arbeit neue multivariate kausale und nicht-kausale, lineare und nicht-lineare Kopplungsanalyseverfahren (HRJSD, mHRJSD, NSTPDC) entwickelt, die in der Lage sind, die Kopplungsstärke und -richtung, sowie deterministische regulatorische Kopplungsmuster innerhalb des zentralen-autonomen Netzwerks zu quantifizieren und zu klassifizieren. Diese Kopplungsanalyseverfahren haben ihre eigenen Besonderheiten, die sie einzigartig machen, auch im Vergleich zu etablierten Kopplungsverfahren. Sie erweitern das Spektrum neuartiger Kopplungsansätze für die Biosignalanalyse und tragen auf ihre Weise zur Gewinnung detaillierter Informationen und damit zu einer verbesserten Diagnostik/Therapie bei. Die Hauptergebnisse dieser Arbeit zeigen signifikant schwächere nichtlineare zentral-kardiovaskuläre und zentral-kardiorespiratorische Kopplungswege und einen signifikant stärkeren linearen zentralen Informationsfluss in Richtung des Herzkreislaufsystems auf, sowie einen signifikant stärkeren linearen respiratorischen Informationsfluss in Richtung des zentralen Nervensystems in der Schizophrenie im Vergleich zu Gesunden. Die detaillierten Erkenntnisse darüber, wie die verschiedenen zentral-autonomen Netzwerke mit paranoider Schizophrenie assoziiert sind, können zu einem besseren Verständnis darüber führen, wie zentrale Aktivierung und autonome Reaktionen und/oder Aktivierung in physiologischen Netzwerken unter pathophysiologischen Bedingungen zusammenhängen.In the field of time series analysis, increasing interest focuses on insights gained how the coupling pathways of regulatory mechanisms work in healthy and ill states. Recent advances in non-linear dynamics, information theory and network theory lead to a new sophisticated body of knowledge about coupling pathways within (patho)physiological (sub)systems. Coupling analyses aim to provide a better understanding of how the different integrated physiological (sub)systems, with their complex structures and regulatory mechanisms, describe the global behaviour and distinct physiological functions at the organism level. In particular, the detection and quantification of the coupling strength and direction are important aspects for a more detailed understanding of physiological regulatory processes. This thesis aimed to characterize short-term instantaneous central-autonomic-network coupling pathways (top-to-bottom and bottom to top) by analysing the coupling of heart rate, systolic blood pressure, respiration and central activity (EEG) in schizophrenic patients and healthy participants. Therefore, new multivariate causal and non-causal linear and non-linear coupling approaches (HRJSD, mHRJSD, NSTPDC) that are able to determine the coupling strength and direction were developed. Whereby, the HRJSD and mHRJSD approaches allow the quantification and classification of deterministic regulatory coupling patterns within and between the cardiovascular- the cardiorespiratory system and the central-autonomic-network were developed. These coupling approaches have their own unique features, even as compared to well-established coupling approaches. They expand the spectrum of novel coupling approaches for biosignal analysis and thus contribute in their own way to detailed information obtained, and thereby contribute to improved diagnostics/therapy. The main findings of this thesis revealed significantly weaker non-linear central-cardiovascular and central-cardiorespiratory coupling pathways, and significantly stronger linear central information flow in the direction of the cardiac- and vascular system, and a significantly stronger linear respiratory information transfer towards the central nervous system in schizophrenia in comparison to healthy participants. This thesis provides an enhanced understanding of the interrelationship of central and autonomic regulatory mechanisms in schizophrenia. The detailed findings on how variously-pronounced, central-autonomic-network pathways are associated with paranoid schizophrenia may enable a better understanding on how central activation and autonomic responses and/or activation are connected in physiology networks under pathophysiological conditions

HUMAN CARDIOVASCULAR RESPONSES TO SIMULATED PARTIAL GRAVITY AND A SHORT HYPERGRAVITY EXPOSURE

Orthostatic intolerance (OI), i.e., the inability to maintain stable arterial pressure during upright posture, is a major problem for astronauts after spaceflight. Therefore, one important goal of spaceflight-related research is the development of countermeasures to prevent post flight OI. Given the rarity and expense of spaceflight, countermeasure development requires ground-based simulations of partial gravity to induce appropriate orthostatic effects on the human body, and to test the efficacy of potential countermeasures. To test the efficacy of upright lower body positive pressure (LBPP) as a model for simulating cardiovascular responses to lunar and Martian gravities on Earth, cardiovascular responses to upright LBPP were compared with those of head-up tilt (HUT), a well-accepted simulation of partial gravity, in both ambulatory and cardiovascularly deconditioned subjects. Results indicate that upright LBPP and HUT induced similar changes in cardiovascular regulation, supporting the use of upright LBPP as a potential model for simulating cardiovascular responses to standing and moving in lunar and Martian gravities. To test the efficacy of a short exposure to artificial gravity (AG) as a countermeasure to spaceflight-induced OI, orthostatic tolerance limits (OTL) and cardiovascular responses to orthostatic stress were tested in cardiovascularly deconditioned subjects, using combined 70º head-up tilt and progressively increased lower body negative pressure, once following 90 minutes AG exposure and once following 90 minutes of -6º head-down bed rest (HDBR). Results indicate that a short AG exposure increased OTL of cardiovascularly deconditioned subjects, with increased baroreflex and sympathetic responsiveness, compared to those measured after HDBR exposure. To gain more insight into mechanisms of causal connectivity in cardiovascular and cardiorespiratory oscillations during orthostatic challenge in both ambulatory and cardiovascularly deconditioned subjects, couplings among R-R intervals (RRI), systolic blood pressure (SBP) and respiratory oscillations in response to graded HUT and dehydration were studied using a phase synchronization approach. Results indicate that increasing orthostatic stress disassociated interactions among RRI, SBP and respiration, and that dehydration exacerbated the disconnection. The loss of causality from SBP to RRI following dehydration suggests that dehydration also reduced involvement of baroreflex regulation, which may contribute to the increased occurrence of OI

Signal Information Prediction of Mortality Identifies Unique Patient Subsets after Severe Traumatic Brain Injury: A Decision-Tree Analysis Approach.

Nonlinear physiological signal features that reveal information content and causal flow have recently been shown to be predictors of mortality after severe traumatic brain injury (TBI). The extent to which these features interact together, and with traditional measures to describe patients in a clinically meaningful way remains unclear. In this study, we incorporated basic demographics (age and initial Glasgow Coma Scale [GCS]) with linear and non-linear signal information based features (approximate entropy [ApEn], and multivariate conditional Granger causality [GC]) to evaluate their relative contributions to mortality using cardio-cerebral monitoring data from 171 severe TBI patients admitted to a single neurocritical care center over a 10 year period. Beyond linear modelling, we employed a decision tree analysis approach to define a predictive hierarchy of features. We found ApEn (p = 0.009) and GC (p = 0.004) based features to be independent predictors of mortality at a time when mean intracranial pressure (ICP) was not. Our combined model with both signal information-based features performed the strongest (area under curve = 0.86 vs. 0.77 for linear features only). Although low "intracranial" complexity (ApEn-ICP) outranked both age and GCS as crucial drivers of mortality (fivefold increase in mortality where ApEn-ICP 60 years of age died, whereas those with higher ApEn-ICP and GCS ≥5 all survived. Yet, even with low initial intracranial complexity, as long as patients maintained robust GC and "extracranial" complexity (ApEn of mean arterial pressure), they all survived. Incorporating traditional linear and novel, non-linear signal information features, particularly in a framework such as decision trees, may provide better insight into "health" status. However, caution is required when interpreting these results in a clinical setting prior to external validation

Assessment Of Blood Pressure Regulatory Controls To Detect Hypovolemia And Orthostatic Intolerance

Regulation of blood pressure is vital for maintaining organ perfusion and homeostasis. A significant decline in arterial blood pressure could lead to fainting and hypovolemic shock. In contrast to young and healthy, people with impaired autonomic control due to aging or disease find regulating blood pressure rather demanding during orthostatic challenge. This thesis performed an assessment of blood pressure regulatory controls during orthostatic challenge via traditional as well as novel approaches with two distinct applications 1) to design a robust automated system for early identification of hypovolemia and 2) to assess orthostatic tolerance in humans. In chapter 3, moderate intensity hemorrhage was simulated via lower-body negative pressure (LBNP) with an aim to identify moderate intensity hemorrhage (-30 and -40 mmHg LBNP) from resting baseline. Utilizing features extracted from common vital sign monitors, a classification accuracy of 82% and 91% was achieved for differentiating -30 and -40 mmHg LBNP, respectively from baseline. In chapter 4, cause-and-effect relationship between the representative signals of the cardiovascular and postural systems to ascertain blood pressure homeostasis during standing was performed. The degree of causal interaction between the two systems, studied via convergent cross mapping (CCM), showcased the existence of a significant bi-directional interaction between the representative signals of two systems to regulate blood pressure. Therefore, the two systems should be accounted for jointly when addressing physiology behind fall. Further, in chapter 5, the potential of artificial gravity (2-g) induced via short-arm human centrifuge at feet towards evoking blood pressure regulatory controls analogous to standing was investigated. The observation of no difference in the blood pressure regulatory controls, during 2-g centrifugation compared to standing, strongly supported the hypothesis of artificial hypergravity for mitigating cardiovascular deconditioning, hence minimizing post-flight orthostatic intolerance

Concomitant evaluation of cardiovascular and cerebrovascular controls via Geweke spectral causality to assess the propensity to postural syncope

The evaluation of propensity to postural syncope necessitates the concomitant characterization of the cardiovascular and cerebrovascular controls and a method capable of disentangling closed loop relationships and decomposing causal links in the frequency domain. We applied Geweke spectral causality (GSC) to assess cardiovascular control from heart period and systolic arterial pressure variability and cerebrovascular regulation from mean arterial pressure and mean cerebral blood velocity variability in 13 control subjects and 13 individuals prone to develop orthostatic syncope. Analysis was made at rest in supine position and during head-up tilt at 60°, well before observing presyncope signs. Two different linear model structures were compared, namely bivariate autoregressive and bivariate dynamic adjustment classes. We found that (i) GSC markers did not depend on the model structure; (ii) the concomitant assessment of cardiovascular and cerebrovascular controls was useful for a deeper comprehension of postural disturbances; (iii) orthostatic syncope appeared to be favored by the loss of a coordinated behavior between the baroreflex feedback and mechanical feedforward pathway in the frequency band typical of the baroreflex functioning during the postural challenge, and by a weak cerebral autoregulation as revealed by the increased strength of the pressure-to-flow link in the respiratory band. GSC applied to spontaneous cardiovascular and cerebrovascular oscillations is a promising tool for describing and monitoring disturbances associated with posture modification

Altered causal coupling pathways within the central-autonomic-network in patients suffering from schizophrenia

The multivariate analysis of coupling pathways within physiological (sub)systems focusing on identifying healthy and diseased conditions. In this study, we investigated a part of the central-autonomic-network (CAN) in 17 patients suffering from schizophrenia (SZO) compared to 17 age–gender matched healthy controls (CON) applying linear and nonlinear causal coupling approaches (normalized short time partial directed coherence, multivariate transfer entropy). Therefore, from all subjects continuous heart rate (successive beat-to-beat intervals, BBI), synchronized maximum successive systolic blood pressure amplitudes (SYS), synchronized calibrated respiratory inductive plethysmography signal (respiratory frequency, RESP), and the power PEEG of frontal EEG activity were investigated for 15 min under resting conditions. The CAN revealed a bidirectional coupling structure, with central driving towards blood pressure (SYS), and respiratory driving towards PEEG. The central-cardiac, central-vascular, and central-respiratory couplings are more dominated by linear regulatory mechanisms than nonlinear ones. The CAN showed significantly weaker nonlinear central-cardiovascular and central-cardiorespiratory coupling pathways, and significantly stronger linear central influence on the vascular system, and on the other hand significantly stronger linear respiratory and cardiac influences on central activity in SZO compared to CON, and thus, providing better understanding of the interrelationship of central and autonomic regulatory mechanisms in schizophrenia might be useful as a biomarker of this diseas