Robust closed-loop control of induction and maintenance of propofol anesthesia in children.

BACKGROUND During closed-loop control, a drug infusion is continually adjusted according to a measure of clinical effect (e.g., an electroencephalographic depth of hypnosis (DoH) index). Inconsistency in population-derived pediatric pharmacokinetic/pharmacodynamic models and the large interpatient variability observed in children suggest a role for closed-loop control in optimizing the administration of intravenous anesthesia. OBJECTIVE To clinically evaluate a robustly tuned system for closed-loop control of the induction and maintenance of propofol anesthesia in children undergoing gastrointestinal endoscopy. METHODS One hundred and eight children, aged 6-17, ASA I-II, were enrolled. Prior to induction of anesthesia, NeuroSENSE™ sensors were applied to obtain the WAVCNS DoH index. An intravenous cannula was inserted and lidocaine (0.5 mg·kg(-1) ) administered. Remifentanil was administered as a bolus (0.5 μg·kg(-1) ), followed by continuous infusion (0.03 μg·kg(-1) ·min(-1) ). The propofol infusion was closed-loop controlled throughout induction and maintenance of anesthesia, using WAVCNS as feedback. RESULTS Anesthesia was closed-loop controlled in 102 cases. The system achieved and maintained an adequate DoH without manual adjustment in 87/102 (85%) cases. Induction of anesthesia (to WAVCNS  ≤ 60) was completed in median 3.8 min (interquartile range (IQR) 3.1-5.0), culminating in a propofol effect-site concentration (Ce ) of median 3.5 μg·ml(-1) (IQR 2.7-4.5). During maintenance of anesthesia, WAVCNS was measured within 10 units of the target for median 89% (IQR 79-96) of the time. Spontaneous breathing required no manual intervention in 91/102 (89%) cases. CONCLUSIONS A robust closed-loop system can provide effective propofol administration during induction and maintenance of anesthesia in children. Wide variation in the calculated Ce highlights the limitation of open-loop regimes based on pharmacokinetic/pharmacodynamic models.