Background: Time to emergence from general anaesthesia is highly variable between individuals. This variability has been attributed to individual differences in anaesthetic sensitivity. However, this hypothesis has not been verified experimentally. We explicitly test this hypothesis by quantifying emergence from anaesthesia repeatedly in the same individuals over time.
Methods: Genetically identical adult (12-24 weeks old) male (n=40) and female (n=20) C57BL/6J mice were exposed to 2 h of isoflurane (0.90 vol%) on 10 separate occasions. Time to emergence was measured using the return of the righting reflex. Predictions of the standard effect-site pharmacokinetic-pharmacodynamic (PK-PD) model and neuronal dynamics model of stochastic fluctuations between the awake and anaesthetised states were fit to observed emergence times. Repeated steady-state assessments of the righting reflex obtained during the last 2 h of a 4-h exposure to 0.3, 0.4, 0.6, or 0.7 vol% isoflurane (n=20 per concentration) were used to determine individual probabilities of losing the righting reflex, which was defined as an individual's anaesthetic sensitivity.
Results: Emergence times varied by at least two orders of magnitude after identical anaesthetic exposure. We did not find consistent inter-individual differences in emergence times. Instead, we found that variability in emergence times across trials in each individual was as large as that between two different individuals. Emergence times were not correlated across time. Consistent with previous work, we identified large individual differences in anaesthetic sensitivity which persisted on a time scale of at least 1 week. A standard PK-PD model failed to reproduce inter-trial variability. In contrast, the neuronal dynamics model reproduced both population- and individual-level variability in emergence times.
Conclusions: Stochastic state switching contributes to inherent variability in emergence from general anaesthesia. Delayed emergence occurred in a small proportion of anaesthetic exposures in a genetically homogeneous population. The neuronal dynamics model predicts that anaesthetic emergence times will be probabilistically long, which might explain delayed emergence observed in clinical settings.
Keywords: emergence; mechanisms of anaesthesia; neuronal dynamics; pharmacodynamics; resistance to state transitions; return of consciousness; stochastic state switching.
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