Parametric versus nonparametric transfer function estimation of cerebral autoregulation from spontaneous blood-pressure oscillations.

Abstract

Cerebral autoregulation (CAR) is a control mechanism of the brain keeping cerebral blood flow constant albeit the arterial blood pressure varies. Impaired CAR may be associated with an increased risk of cerebral ischemic events in patients with obstructive cerebrovascular disease. Spontaneous blood pressure oscillations are analyzed using a nonparametric and two parametric transfer function estimators, i.e. the autoregressive-moving-average model with exogenous inputs or the vector-autoregressive model. Performance of the methods was compared using data from patients with unilateral stenosis or occlusion. We also analyzed reproducibility by comparing partitions of the data an with data from other patients which have been measured twice. Results show that there is no significant difference between methods (ANOVA, p > 0.27), and that CAR measurements can be performed reproducibly (Kendall's tau, p < 0.0016) by all three methods. In conclusion, CAR measurements by means of spontaneous oscillations can be obtained stably and the presented parametric approaches can serve for future online application of CAR measurement.