Abstract
Background: Autoregressive modeling with exogenous input of middle latency auditory evoked potentials (A-Line autoregressive index [AAI]) has been proposed for monitoring depth of anesthesia in adults. The aim of this study was to evaluate the performance of the AAI during induction of anesthesia with sevoflurane and remifentanil in pediatric patients. Methods: Twenty preschool children were ...
Abstract
Background: Autoregressive modeling with exogenous input of middle latency auditory evoked potentials (A-Line autoregressive index [AAI]) has been proposed for monitoring depth of anesthesia in adults. The aim of this study was to evaluate the performance of the AAI during induction of anesthesia with sevoflurane and remifentanil in pediatric patients. Methods: Twenty preschool children were anesthetized with sevoflurane and remifentanil. AAI, heart rate, and mean arterial pressure were compared for their ability to distinguish between different hypnotic states before inhalation induction and during sevoflurane anesthesia with and without remifentanil infusion. The prediction probability was calculated for discrimination between the predefined case milestones Awake, Spontaneous Eye Closure, and insertion of a laryngeal mask airway during general anesthesia (Laryngeal Mask Insertion). Results: The AAI (mean +/- SD) inAwake children was 79 +/- 10, declining to 59 22 at Spontaneous Eye Closure and 34 13 when anesthetized. AAI values significantly overlapped between anesthetic states. For the AAI, the prediction probabilities regarding the ability to discriminate the hypnotic state at the case milestones Awake versus Spontaneous Eye Closure and Awake versus Laryngeal Mask Insertion were 0.77 and 0.99, respectively. In terms of prediction probability values, heart rate and mean arterial pressure were not indicative for anesthetic states. Remifentanil did not influence the AAI. Conclusion: During induction of pediatric patients with sevoflurane, the AAI is of higher value in predicting anesthetic states than hemodynamic variables and reliably differentiates between the awake and anesthetized states. However, individual AAI values demonstrate significant variability and overlap between different clinical conditions.
Altmetric