Society for Technology in Anesthesia, 2005 Annual Meeting Abstract:
Evaluation of a Device to Speed Emergence from Volatile Anesthetic Using a Computer Model

Joseph Orr, Ph.D., Nishant Gopalakrishnan B.S., Derek Sakata M.D., Dwayne Westenskow Ph.D., Noah Syroid M.S.
University of Utah, Department of Anesthesiology

Introduction: We used a computer model of anesthetic uptake and distribution to evaluate the expected emergence time reduction when using a rebreathing/absorber device. The computer model describes transport of anesthetic in multiple body tissue compartments as well as in the breathing circuit. We modified the model to simulate use of a rebreathing/absorber device. The modification allows the simulated patient to inhale CO₂ stored in the rebreathing hose from the previous breath and assumes that charcoal filter in the device will absorb all of the anesthetic gas so that none is inhaled during emergence. We also modified the model to alter cerebral blood flow according to the partial pressure of alveolar (end-tidal) CO₂ using the relationship published by Ide et al.

Methods: We simulated 9 combinations of patient size and anesthetic duration for each of four anesthetic gases. All simulated patients were 30-year-old males. Age and gender affect the modeled alveolar volume and the relative volume of lean and adipose tissue. The simulated patients include a small (weight 50 Kg., height 160 cm), medium (weight 70 kg, height 183 cm.) and obese patient (weight 150 kg, height 183 cm).

All simulated patients received 1 MAC of anesthetic for durations of 30 minutes, 2 hours, or 8 hours.

Maintenance conditions called for ventilating patients at 10 breaths per minute. Simulated tidal volume was set to maintain etCO₂ at 33 mm Hg. Fresh gas flow was set to 3 liters per minute. Fresh gas flow was increased to 10 liters per minute for both non-rebreathing and rebreathing emergence tests. In non-rebreathing emergence simulations, respiratory rate and tidal volume remained constant. In rebreathing simulations, respiratory rate was doubled and tidal volume was increased by 200 ml during emergence.

Results: Average percent decrease in emergence time was 54% for isoflurane, 45% for sevoflurane, 47% for desflurane and 59% for halothane. Overall, the greatest advantage is seen in the more soluble anesthetics (isoflurane and halothane). The smallest time reduction (36%) was seen when simulating a small patient, receiving desflurane for a 30 minute anesthetic. The results also show the total amount of anesthetic exhaled from the patient during the emergence process. The data shows that the average volume of anesthetic excreted during emergence using the rebreathing/absorber device is 3% less than the amount excreted during a normal (non-rebreathing) emergence.

Discussion: As in most computer models, this simulation does not account for inter-patient variability, which the model does not simulate. These variables include differences in metabolic rate, cardiac output, tissue volume variations etc. This model simulates metabolic production of CO₂ as a constant value that is determined according to patient weight. Our model does not consider variation in metabolic rate or cardiac output caused by surgical stimulation, pain, catecholamine release, etc. These variables may lead to variability in patients that the model will not simulate.

References

JG Lerou, RD Dirksen, HH Beneken Kolmer, LHDJ Booij: A system model for closed-circuit inhalation anesthesia, computer study; Anesthesiology 75:345-355, 1991

K Ide, M Eliasziw, MJ Poulin: Relationship between middle cerebral artery blood velocity and end-tidal PCO₂ in the hypocapnic/hypercapnic range in humans; J Appl Physiol 95:129-137, 2003