The degree to which a surgical patient's subconscious processing of pain, or "nociception," is properly managed by their anesthesiologist will directly affect the degree of post-operative drug side effects they'll experience and the need for further pain management they'll require. But pain is a subjective feeling to measure, even when patients are awake, much less when they are unconscious. In a new study, MIT and Massachusetts General Hospital (MGH) researchers describe a set of statistical models that objectively quantified nociception during surgery.
Ultimately, they hope to help anesthesiologists optimize drug dose and minimize post-operative pain and side effects. The new models integrate data meticulously logged over 18,582 minutes of 101 abdominal surgeries in men and women at MGH. Led by former MIT graduate student Sandya Subramanian, now an assistant professor at UC Berkeley and UC San Francisco, the researchers collected and analyzed data from five physiological sensors as patients experienced a total of 49,878 distinct "nociceptive stimuli" (such as incisions or cautery).
Moreover, the team recorded what drugs were administered, and how much and when, to factor in their effects on nociception or cardiovascular measures. They then used all the data to develop a set of statistical models that performed well in retrospectively indicating the body's response to nociceptive stimuli. The team's goal is to furnish such accurate, objective, and physiologically principled .