Bayesian probabilistic network modeling of remifentanil and propofol interaction on wakeup time after closed-loop controlled anesthesia.

Objective: Until now, the knowledge of combining anesthetics to obtain an adequate level of anesthesia and to economize wakeup time has been empirical and difficult to represent in quantitative models. Since there is no reason to expect that the effect of non-opioid and opioid anesthetics can be modeled in a simple linear manner, the use of a new computational approach with Bayesian belief network software is demonstrated.

Methods: A data set from a pharmacodynamic study was used where remifentanil was randomly given in three fixed target concentrations (2, 4, and 8 ng/ml) to 62 subjects.

Oxygen consumption after hypothermic cardiopulmonary bypass: the effect of continuing a propofol infusion postoperatively.

Objective: To evaluate the effect of a fixed rate of infusion of propofol on total body oxygen consumption during the postoperative rewarming phase after cardiopulmonary bypass.

Design: Prospective, randomized, controlled study.

Setting: Cardiac intensive care unit, university hospital.