Recursive identification of an arterial baroreflex model for the evaluation of cardiovascular autonomic modulation

Parametric analysis of an integrated cardio-respiratory model in preterm newborns during apnea

The analysis of the complex interactions involved in the acute physiological response to apnea-bradycardia events in preterm newborns remains a challenging task. This paper presents a novel integrated model of cardio-respiratory interactions, adapted to preterm newborns. A sensitivity analysis, based Morris' screening method, was applied to study the effects of physiological parameters on heart rate and desaturation, during the simulation of a 15-seconds apnea-bradycardia episode. The most sensitive parameters are associated with fundamental, integrative physiological mechanisms involving: (i) respiratory mechanics (intermediate airways and lung compliance), (ii) fraction of inspired oxygen, (iii) metabolic rates (oxygen consumption rate), (iv) heart rate regulation and (v) chemoreflex (gain). Results highlight the relevant influence of physiological variables, involved in preterm apnea-bradycardia events.

Modeling patient-specific desaturation patterns in sleep apnea

OBJECTIVE

The physiological mechanisms involved in cardio-respiratory responses to sleep apnea events are not yet fully elucidated. A model-based approach is proposed to analyse the acute desaturation response to obstructive apneas.

METHODS

An integrated model of cardio-respiratory interactions was proposed and parameters were identified, using an evolutionary algorithm, on a database composed of 107 obstructive apneas acquired from 10 patients (HYPNOS clinical study). Unsupervised clustering was applied to the identified parameters in order to characterize the phenotype of each response to obstructive apneas.

RESULTS

A close match was observed between simulated oxygen saturation (SaO2) and experimental SaO2 in all identifications (median RMSE = 1.3892%). Two clusters of parameters, associated with different dynamics related to sleep apnea and periodic breathing were obtained.

CONCLUSION AND SIGNIFICANCE

The proposed patient and event-specific model-based analysis provides understanding on specific desaturation patterns, consequent to apnea events, with potential applications for personalized diagnosis and treatment.

Parametric Analysis of an Integrated Model of Cardio-respiratory Interactions in Adults in the Context of Obstructive Sleep Apnea

An original integrated model of cardio-respiratory interactions is presented in this paper with the objective of studying the acute physiological responses evoked by obstructive sleep apnea events in adults. A comprehensive sensitivity analysis of the model is proposed during the simulation of a 20 s obstructive apnea episode using the Morris' screening method and local sensitivity analysis. The more relevant parameters are related to the following mechanisms of the physiology: (i) the fraction of oxygen in inspired air, (ii) metabolic rates (oxygen consumption rate, CO₂ production rate); (iii) chemoreflex (gains and time constants) (iv) respiratory mechanics (lung compliance and unstressed volume of air in the alveoli). These results highlight significant physiological variables that may be particularly useful for the development of novel diagnostic and therapeutic strategies, integrating a virtual patient approach.

Influence of nasal CPAP on cardiorespiratory control in healthy neonate

The present study aimed to further unravel the effects of nasal continuous positive airway pressure (nCPAP) on the cardiovascular and respiratory systems in the neonatal period. Six-hour polysomnographic recordings were first performed in seven healthy newborn lambs, aged 2-3 days, without and with nCPAP application at 6 cmH₂O (nCPAP-6), in randomized order. The effects of nCPAP-6 on heart rate variability, respiratory rate variability, and cardiorespiratory interrelations were analyzed using a semiautomatic signal processing approach applied to ECG and respiration recordings. Thereafter, a cardiorespiratory mathematical model was adapted to the experimental conditions to gain further physiological interpretation and to simulate higher nCPAP levels (8 and 10 cmH₂O). Results from the signal processing approach suggest that nCPAP-6 applied in newborns with healthy lungs: 1) increases heart rate and decreases the time and frequency domain indices of heart rate variability, especially those representing parasympathetic activity, while increasing the complexity of the RR-interval time series; 2) prolongs the respiratory cycle and expiration duration and decreases respiratory rate variability; and 3) slightly impairs cardiorespiratory interrelations. Model-based analysis revealed that nCPAP-6 increases the heart rate and decreases respiratory sinus arrhythmia amplitude, in association with a reduced parasympathetic efferent activity. These results were accentuated when simulating an increased CPAP level. Overall, our results provide a further understanding of the effects of nCPAP in neonates, in the absence of lung disease.NEW & NOTEWORTHY Application of nasal continuous positive airway pressure (CPAP) at 6 cmH₂O, a level very frequently used in newborns, alters heart and respiratory rate variability, as well as cardiorespiratory interrelations in a full-term newborn model without lung disease. Moreover, whereas nasal CPAP at 6 cmH₂O decreases parasympathetic efferent activity, there is no change in sympathetic efferent activity.

A model-based analysis of autonomic nervous function in response to the Valsalva maneuver

The Valsalva maneuver (VM) is a diagnostic protocol examining sympathetic and parasympathetic activity in patients with autonomic dysfunction (AD) impacting cardiovascular control. Because direct measurement of these signals is costly and invasive, AD is typically assessed indirectly by analyzing heart rate and blood pressure response patterns. This study introduces a mathematical model that can predict sympathetic and parasympathetic dynamics. Our model-based analysis includes two control mechanisms: respiratory sinus arrhythmia (RSA) and the baroreceptor reflex (baroreflex). The RSA submodel integrates an electrocardiogram-derived respiratory signal with intrathoracic pressure, and the baroreflex submodel differentiates aortic and carotid baroreceptor regions. Patient-specific afferent and efferent signals are determined for 34 control subjects and 5 AD patients, estimating parameters fitting the model output to heart rate data. Results show that inclusion of RSA and distinguishing aortic/carotid regions are necessary to model the heart rate response to the VM. Comparing control subjects to patients shows that RSA and baroreflex responses are significantly diminished. This study compares estimated parameter values from the model-based predictions to indices used in clinical practice. Three indices are computed to determine adrenergic function from the slope of the systolic blood pressure in phase II [α (a new index)], the baroreceptor sensitivity (β), and the Valsalva ratio (γ). Results show that these indices can distinguish between normal and abnormal states, but model-based analysis is needed to differentiate pathological signals. In summary, the model simulates various VM responses and, by combining indices and model predictions, we study the pathologies for 5 AD patients.NEW & NOTEWORTHY We introduce a patient-specific model analyzing heart rate and blood pressure during a Valsalva maneuver (VM). The model predicts autonomic function incorporating the baroreflex and respiratory sinus arrhythmia (RSA) control mechanisms. We introduce a novel index (α) characterizing sympathetic activity, which can distinguish control and abnormal patients. However, we assert that modeling and parameter estimation are necessary to explain pathologies. Finally, we show that aortic baroreceptors contribute significantly to the VM and RSA affects early VM.

Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increasing parasympathetic activity at peak effort and a decreasing vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS. The joint analysis of the extracted autonomic parameters and classic electrophysiological markers could improve BS risk stratification.

Analysis of a cardiovascular model for the study of the autonomic response of Brugada syndrome patients

This paper describes the integration of mathematical models of the cardiac electrical activity, the cardiovascular system and the baroreceptor reflex control of the autonomic nervous system, with a model representing a head-up tilt test. Sensitivity analyses are performed in order to determine those model parameters producing the greatest significant effects on heart rate and blood pressure. An optimization step is then applied to the most influential parameters in order to find the best model fit to real cardiac data obtained from a patient suffering from Brugada syndrome and a healthy subject, in supine and upright postures during a tilt test. Results show the feasibility of the model to generate realistic autonomic responses to head-up tilt testing in health and disease.