A large body of evidence indicates that sleep-disordered breathing leads to abnormally elevated sympathetic tone and impaired vagal activity, and that these factors in turn promote hypertension and cardiometabolic disease. Thus, low-cost but accurate monitoring of autonomic function is useful for the aggressive management of patients with sleep apnea. However, the mechanistic information that can be derived from conventional noninvasive techniques, such as heart rate variability, is limited by the univariate nature of the underlying analyses. This article reviews the development and application of multivariate dynamic biophysical models that enable the causal dependencies among respiration, blood pressure, heart rate variability and peripheral vascular resistance to be quantified. The markers derived from these “minimal models” can be used in conjunction with heart rate variability to increase the sensitivity with which abnormalities in autonomic cardiovascular control are detected in subjects with sleep-disordered breathing.
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