Key result
Model-based analysis of the Valsalva maneuver showed that respiratory sinus arrhythmia and baroreflex responses were significantly diminished in 5 autonomic dysfunction patients vs 34 controls.
Why the study?
Direct measurement of sympathetic and parasympathetic activity is costly and invasive, prompting indirect assessment of autonomic dysfunction via heart rate and blood pressure response patterns during the Valsalva maneuver.
Observational (n=39)
A novel mathematical model incorporating respiratory sinus arrhythmia and baroreflex mechanisms can predict patient-specific autonomic function during the Valsalva maneuver, differentiating pathological signals better than standard indices alone.
Should not yet alter clinical autonomic testing; leaves open validation of model-based Valsalva analysis in larger cohorts.
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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Randall et al. (2019) conducted an observational in Autonomic dysfunction (n=39). Valsalva maneuver with model-based analysis vs. Control subjects was evaluated on Sympathetic and parasympathetic dynamics (heart rate and blood pressure response patterns). Model-based analysis of the Valsalva maneuver showed that respiratory sinus arrhythmia and baroreflex responses were significantly diminished in 5 autonomic dysfunction patients vs 34 controls.
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