The Probability Distribution of Times to Awakening From Sevoflurane Anesthesia, Among a Homogeneous Group of Cases With the Same Age-Adjusted Minimum Alveolar Concentration Fraction.

Abstract

Background: Human studies of awakening from general anesthesia inform understanding of neural mechanisms underlying recovery of consciousness. Probability distributions of times for emergence from anesthesia provide mechanistic information on whether putative biological models are generalizable. Previously reported distributions involved nonhomogenous groups, unsuitable for scientific comparisons. We used a retrospective cohort to identify surgeon-procedure combinations of homogeneous groups of patients and anesthetics to assess the probability distribution of extubation times to inform scientific studies of awakening from anesthesia. We hypothesized an acceptable fit to a log-normal distribution.

Methods: Extubation times were recorded by anesthesia practitioners using an event button in the electronic health record. From 2011 through 2023, there were 182,374 cases with general anesthesia, not positioned prone, tracheal intubation after operating room entrance, interval from start to end of surgery ≥1 hour, and inhalational agent mean minimum alveolar concentration (MAC) fraction measured from case start through surgery end ≥0.6. We applied joint criteria of the same primary surgeon, surgical procedure, MAC fraction of each inhalational agent in 0.1 increments, and binary categories of adult, trainee finishing the anesthetic, bispectral index (BIS) monitor, N2O, sugammadex, and neostigmine. We considered all combinations of categories with ≥40 cases. We used Gas Man simulation to infer the probability distribution of volatile agent concentrations in the vessel-rich group (ie, brain).

Results: There were 48 cases among patients having oral surgery extractions by 1 surgeon, without anesthesia trainees, sevoflurane anesthesia with 0.3 MAC fraction at surgery end, without N2O, BIS monitor, or neuromuscular block reversal. Their extubation times followed a log-normal distribution (Shapiro-Wilk W = 0.98, P = .68). For the computer simulations, we assumed that patients differed solely in their binary threshold of vessel-rich group sevoflurane concentration at awakening (eg, patients with an awakening threshold of 0.26% would be unconscious for 0.1 to 14.8 minutes as sevoflurane is exhaled but the concentration remains ≥0.26%, and abruptly transition to consciousness at 15 minutes when the concentration reaches 0.25%). Expected awakening times would appear to be a log-normal distribution.

Conclusions: A homogeneous patient population had a log-normal distribution of extubation times. Generalizable models of awakening should have that distribution. Clinicians change awakening times by their choice of agent and its MAC fraction at surgery end. Simulation suggests that the normal distribution in the log time scale for awakening, among patients with similar conditions, can represent a relatively uniform distribution among patients in the vessel-rich group (brain) partial pressure when the abrupt transition to consciousness occurs.