Key result
Novel Dystatis framework quantifies cardiac autonomic regulation across resting, exercise, and orthostatic states.
Why the study?
The quantitative assessment of autonomic regulation of the circulation is crucial for personalized medicine in cardiovascular diseases.
Introducing a theoretical, model-based framework for autonomic assessment may help resolve clinical inconsistences in parameters like heart rate variability and aid in managing cardiovascular and metabolic diseases.
Hypothesis-generating for autonomic assessment; prospective validation required before any clinical application.
Autonomic neural system (ANS) regulates the circulation to provide optimal perfusion of every organ in accordance with its metabolic needs, and the quantitative assessment of autonomic regulation is crucial for personalized medicine in cardiovascular diseases. In this paper, we propose the Dystatis to quantitatively evaluate autonomic regulation of the human cardiac system, based on homeostatis and probabilistic graphic model, where homeostatis explains ANS regulation while the probability graphic model systematically defines the regulation process for quantitative assessment. The indices and measurement methods for three well-designed scenarios are also illustrated to evaluate the proposed Dystatis: (1) heart rate variability (HRV), blood pressure variability (BPV), and respiration synchronization (Synch) in resting situation; (2) chronotropic competence indices (CCI) in graded exercise testing; and (3) baroreflex sensitivity (BRS), sympathetic nerve activity (SNA), and parasympathetic nerve activity (PNA) in orthostatic testing. The previous clinical results have shown that the proposed method and indices for autonomic cardiac system regulation have great potential in prediction, diagnosis, and rehabilitation of cardiovascular diseases, hypertension, and diabetes.
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Wu et al. (2019) studied Autonomic nervous system dysfunction. Dystatis methodology was evaluated. The proposed Dystatis methodology provides a quantitative probabilistic framework based on homeostasis to evaluate autonomic regulation of the cardiac system across resting, exercise, and orthostatic scenarios.
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