Identifying a Personalized Anesthetic with Fuzzy PROMETHEE

Area of Science:

• Anesthesiology
• Decision Sciences
• Medical Informatics

Background:

• Anesthetic selection requires careful patient evaluation.
• Multi-criteria decision-making (MCDA) offers a structured approach to complex choices.
• Optimizing anesthetic choice impacts patient safety and outcomes.

Purpose of the Study:

• To apply a multi-criteria decision-making technique for selecting appropriate anesthetic agents.
• To demonstrate the utility of fuzzy PROMETHEE in anesthetic selection.
• To personalize anesthetic agent choice based on patient-specific factors.

Main Methods:

• The fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment of Evaluations) method was employed.
• Key criteria included minimum alveolar concentration, partition coefficients, onset/recovery times, and dosage.
• Analysis involved defining criteria values, weights, and preference functions.

Main Results:

• Nitrous oxide and xenon were ranked as preferred inhaled agents; midazolam as preferred injected agent in general ranking.
• For a specific patient (70-year-old female with COPD, obesity, diabetes), desflurane and etomidate became preferred.
• Nitrous oxide was least preferred for the specific patient profile.

Conclusions:

• Fuzzy PROMETHEE provides a robust framework for anesthetic selection.
• Assigning criteria weights and grading alternatives are critical challenges in MCDA.
• Expert clinical judgment remains essential alongside decision-making tools.