The Predictive Performance of a System Model for Enflurane Closed-circuit Inhalational Anesthesia
- 1 November 1993
- journal article
- research article
- Published by Wolters Kluwer Health in Anesthesiology
- Vol. 79 (5) , 932-942
- https://doi.org/10.1097/00000542-199311000-00010
Abstract
Previously, the authors described a system model for closed-circuit inhalational anesthesia, and demonstrated close agreement between end-tidal isoflurane concentrations measured in their clinical study and those predicted by the model. The predictive performance of their model has not, however, been tested for anesthetics featuring nonpulmonary elimination (NPE). The authors quantified the predictive performance of two versions (A and C) of the model in 50 patients by comparing the predicted and the measured alveolar concentration-time profiles after bolus injections of liquid enflurane into the expiratory limb of the closed system. Version A did not incorporate NPE, but version C emulated NPE by adopting the irreversible loss of a fraction of the enflurane present in the arterial hepatic blood flow (0.131, derived from a mass balance study performed by others). For each concentration measured by mass spectrometry, the authors used computer simulations of version A and C to calculate a predicted concentration for both versions. For each patient, the authors calculated the bias (indicating systematic over- or underprediction) and the scatter of the prediction errors (indicating typical error size). The authors administered a total of 379 ml of liquid enflurane via 466 injections. A total of 18,432 alveolar concentrations (one per 10-s period; average concentration = 0.96 vol%) were measured. The bias and the scatter, both given as mean (and SD), were 10.0 (13.1)% and 11.8 (3.9)% for version A and -0.8 (11.4)% and 11.4 (2.8)% for C. The bias for version C was closer to zero; the scatters were similar. Version C incorporating NPE performs better than version A. The accuracy that was obtained should encourage the use of version C for clinical, teaching, research, economic, and ecologic purposes.Keywords
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