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Randall EB, Billeschou A, Brinth LS, Mehlsen J, Olufsen MS. A model-based analysis of autonomic nervous function in response to the Valsalva maneuver. J Appl Physiol (1985) 2019; 127:1386-1402. [PMID: 31369335 DOI: 10.1152/japplphysiol.00015.2019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
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.
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Affiliation(s)
- E Benjamin Randall
- Department of Mathematics, North Carolina State University, Raleigh, North Carolina
| | - Anna Billeschou
- Department of Clinical Physiology and Nuclear Medicine, Bispebjerg Frederiksberg Hospital, Frederiksberg, Denmark
| | - Louise S Brinth
- Department of Clinical Physiology and Nuclear Medicine, Bispebjerg Frederiksberg Hospital, Frederiksberg, Denmark
| | - Jesper Mehlsen
- Section of Surgical Pathophysiology, Juliane Marie Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Mette S Olufsen
- Department of Mathematics, North Carolina State University, Raleigh, North Carolina
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Recursive Model Identification for the Evaluation of Baroreflex Sensitivity. Acta Biotheor 2016; 64:469-478. [PMID: 27757742 DOI: 10.1007/s10441-016-9295-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 10/11/2016] [Indexed: 10/20/2022]
Abstract
A method for the recursive identification of physiological models of the cardiovascular baroreflex is proposed and applied to the time-varying analysis of vagal and sympathetic activities. The proposed method was evaluated with data from five newborn lambs, which were acquired during injection of vasodilator and vasoconstrictors and the results show a close match between experimental and simulated signals. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge and the obtained estimators of vagal and sympathetic activities were compared to traditional markers associated with baroreflex sensitivity. High correlations were observed between traditional markers and model-based indices.
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Le Rolle V, Beuchee A, Praud JP, Samson N, Pladys P, Hernández AI. Recursive identification of an arterial baroreflex model for the evaluation of cardiovascular autonomic modulation. Comput Biol Med 2015; 66:287-94. [PMID: 26453759 DOI: 10.1016/j.compbiomed.2015.09.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Revised: 09/07/2015] [Accepted: 09/16/2015] [Indexed: 11/28/2022]
Abstract
The evaluation of the time-varying vagal and sympathetic contributions to heart rate remains a challenging task because the observability of the baroreflex is generally limited and the time-varying properties are difficult to take into account, especially in non-stationnary conditions. The objective is to propose a model-based approach to estimate the autonomic modulation during a pharmacological challenge. A recursive parameter identification method is proposed and applied to a mathematical model of the baroreflex, in order to estimate the time-varying vagal and sympathetic contributions to heart rate modulation during autonomic maneuvers. The model-based method was evaluated with data from five newborn lambs, which were acquired during injection of vasodilator and vasoconstrictor drugs, on normal conditions and under beta-blockers, so as to quantify the effect of the pharmacological sympathetic blockade on the estimated parameters. After parameter identification, results show a close match between experimental and simulated signals for the five lambs, as the mean relative root mean squared error is equal to 0.0026 (± 0.003). The error, between simulated and experimental signals, is significantly reduced compared to a batch identification of parameters. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge and, as expected, it was possible to observe an alteration of the sympathetic response under beta-blockers. The simulated vagal modulation illustrates a response similar to traditional heart rate variability markers during the pharmacological maneuver. The model-based method, proposed in the paper, highlights the advantages of using a recursive identification method for the estimation of vagal and sympathetic modulation.
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Affiliation(s)
- Virginie Le Rolle
- INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France.
| | - Alain Beuchee
- INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France; CHU Rennes, Pole de pdiatrie mdico-chirurgicale et gntique clinique - Service de pdiatrie, Rennes F-35000, France
| | - Jean-Paul Praud
- Department of Pediatrics, University of Sherbrooke, QC, Canada J1H5N4
| | - Nathalie Samson
- Department of Pediatrics, University of Sherbrooke, QC, Canada J1H5N4
| | - Patrick Pladys
- INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France; CHU Rennes, Pole de pdiatrie mdico-chirurgicale et gntique clinique - Service de pdiatrie, Rennes F-35000, France
| | - Alfredo I Hernández
- INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France
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