Identifying a Personalized Anesthetic with Fuzzy PROMETHEE

During an anesthetic evaluation, the individual's medical history and overall fitness for the whole medical procedure should be carefully examined. The objective of this study was to apply a multi-criteria decision-making technique to determine the proper anesthetic agent for specific patients.

The fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment of Evaluations) method was applied to determine the most appropriate agent. Minimum alveolar concentration, blood:gas and oil:gas partition coefficients, onset of action, recovery time, duration, induction and maintenance doses, and washout time were used as the criteria for the analysis. After defining the values of each criteria, the criteria weights and the preference function were set, and finally the results for two different examples, one for general ranking and one for a specific individual were obtained.

The results show that nitrous oxide and xenon are among the preferred inhaled anesthetics in the ranking of the inhaled anesthetics, whereas midazolam was identified as the preferred injected agent. When the weights are selected according to a specific patient's condition, namely a 70-year-old woman to undergo an emergent laparoscopic appendectomy with comorbidities, including severe chronic obstructive pulmonary disease as a consequence of a life-long smoking habit, morbid obesity, and type II diabetes, the results changed significantly. In this case, desflurane and etomidate come first in the ranking of inhaled and injected anesthetics, respectively, while nitrous oxide is the least preferred anesthetic agent.

Expert opinion is always needed. Assigning weights to criteria and grading alternatives are the major challenges in multi-criteria decision-making studies. Fuzzy PROMETHEE is proposed to solve a multi-criteria decision-making problem in selecting a general anesthetic.