Author:
Vermeulen P. M.,Lerou J. G. C.,Dirksen R.,Booij L. H. D. J.,Borm G. F.
Abstract
Background
Previously, the authors described a physiologic model for closed-circuit inhalational anesthesia. The basic version of this system model was clinically validated for isoflurane. An extended version adopted nonpulmonary elimination causing a constant fraction of anesthetic to be irreversibly lost. This version improved the accuracy of the model for enflurane. The model's performance for other inhalational anesthetics that are not biochemically inert, such as halothane, remained to be evaluated.
Methods
The current study quantified the predictive performance of four versions of the model by comparison of the predicted and measured alveolar halothane concentration-time profiles in 53 patients. Version A did not incorporate nonpulmonary elimination, whereas version D adopted a nonlinear hepatic nonpulmonary elimination following Michaelis-Menten kinetics. A and D used fixed partition coefficients. Their counterparts, A' and D', were formulated to examine the impact of age-adjusted partition coefficients on the accuracy of our model. Each concentration measured by mass spectrometry was compared to four predicted concentrations calculated by four computer simulations (one per version). For each patient, the authors calculated the root mean squared error (rmse; typical error size), bias (systematic component), and scatter of the prediction errors.
Results
Fifty-three patients were anesthetized with 330 ml of liquid halothane via 426 bolus injections during more than 61 h; 21,890 alveolar concentrations (average 0.6 vol%) were measured. Version D' showed the best overall performance with an rmse of 19.6 +/- 7.2%, a bias of 0.5 +/- 15.9%, and a scatter of 13.2 +/- 3.5% (mean +/- SD).
Conclusions
The model incorporating nonpulmonary elimination and age-adjusted partition coefficients (D') is sufficiently reliable and accurate to represent halothane closed-circuit anesthesia. This system model, with its various versions, is a valuable tool to predict the dynamics of isoflurane, enflurane, and halothane for clinical, educational, and research purposes.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Anesthesiology and Pain Medicine
Cited by
7 articles.
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