on November 19th, 2014 No Comments
Anesthesiologist Divya Chander, MD, PhD, is one of a leading group of neuroscientists and anesthesiologists who are using high-tech monitoring equipment in the operating room to explore the nature of consciousness – which isn’t quite as simple as on or off, asleep or awake.
Stanford Medicine magazine profiled Chander’s work last summer, but I came across it when the title of one of Chander’s recently published papers grabbed my eye: “Electroencephalographic Variation During End Maintenance and Emergence from Surgical Anesthesia.” Okay, that might not pique your curiosity, but when I spotted the words, “for the first time” in the abstract I was hooked. I read on to learn that Chander and her team attach electrodes to the foreheads of patients during surgery, measuring the brain’s electrical signals.
After a bit of scrambling you might expect when trying to get in touch with someone who spends her days in the operating room, I managed to reach Chander on the phone. Our conversation strayed far from the bounds of her paper:
In this work, what did you do for the first time?
It’s not that no one has ever used an EEG during anesthesia. During the middle of the 20th century, several anesthesiologists attempted to record brain activity under increasing levels of anesthesia, just as many neuroscientists were using the EEG to characterize the stages of sleep. The process of recording EEG was really cumbersome back then, unlike today when you can stick a frontal set of leads on a patient’s forehead in the OR in a matter of seconds. Certain general stages of anesthesia were identified, but a formalized staging nomenclature, based on the relative contribution of dominant slow-wave oscillations in the EEG, had never been defined. Non-REM (slow-wave) and REM (rapid eye movement sleep) were staged in this way by sleep neurobiologists, but not anesthesiologists. In our study, we built upon the sleep stage classification system, to define maintenance patterns of general anesthesia. The formalized nomenclature helps us examine the stages of unconsciousness under anesthesia and communicate with other anesthesiologists.
What did you find?
We recorded the frontal EEGs (from the forehead) of 100 patients undergoing routine orthopedic surgeries. We discovered four primary electrical patterns that patients exhibit when they’re unconscious, and also as they’re waking up from anesthesia. The unconscious patterns show variety – not all patients’ brains look the same under anesthesia, despite similar drug exposure, meaning there are ‘neural phenotypes,’ or patterns of neuronal activity. The emergence patterns from anesthesia (pathways people’s brains take to reestablish conscious awareness after the anesthetic is turned off) bear some similarity to those pathways traversed when people are awakening from sleep.
When wakening from anesthesia, some people spend a relatively long time in non slow-wave anesthesia, which is similar to REM, the stage of sleep where dreams occur that usually precedes awakening. Others go straight from deep anesthesia, what we call slow-wave anesthesia (because of its dominant EEG patterns) to awakening. Interestingly, these patients were more likely to experience post-surgical pain, a situation akin to awakening from a deep sleep and experiencing confusion or discomfort; some childhood parasomnias like sleep terrors are characterized by moving abruptly from slow wave sleep to waking.
We began to see some tantalizing suggestions certain patterns of wake-ups from anesthesia might be more preferable. Could paying attention to these emergence trajectories prevent some problematic complications, like post-operative cognitive dysfunction? Could we ‘engineer’ or optimize anesthetic delivery to favor certain types of maintenance and emergence patterns? Can we monitor these patterns in a way that makes delivering anesthesia safer? Recognizing the variety of maintenance and emergence patterns under anesthesia also opens an entirely new possibility in the field of personalized medicine – imagine tailoring anesthetics to a person’s genome? I am trying to develop an initiative that addresses this in collaboration with Stanford’s new GenePool Biobank program.