Instantaneous assessment of autonomic cardiovascular control during general anesthesia

Abstract

We present a comprehensive probabilistic point process framework to estimate and monitor the instantaneous heartbeat dynamics as related to specific cardiovascular control mechanisms and hemodynamics. Assessment of the model's statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR) structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR), heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and baroreceptor-cardiac reflex (BRS), can be rigorously derived within a parametric framework and instantaneously updated with an adaptive algorithm. Instantaneous metrics of nonlinearity, such as the bispectrum of heartbeat intervals, can also be derived. We have applied the proposed point process framework to experimental recordings from healthy subjects in order to monitor cardiovascular regulation under propofol anesthesia. Results reveal interesting dynamic trends across different pharmacological interventions, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, noninvasive assessment of general anesthesia.

Figure 1

Tracking results of various instantaneous indices for Subject 15. Three transient periods (level 0–>1, level 1–>2, level 2–>3) are shown.

Figure 2

Tracking results of various instantaneous indices for Subject 9. The two dashed lines (~ 2010 s and ~3000 s) mark the drug concentration level 0–>1, (i.e., propofol administration onset time) and level 1–>2, respectively. The dotted dashed line (~2960 s) marks the time when phenylephrine was administered; and the dotted line (~3125 s) marks the time of hand ventilation.

Figure 3

Estimates of the instantaneous indices for six drug concentration levels (0–5) for Subject 9.