Predictive performance of a multivariable difficult intubation model for obese patients

Area of Science:

• Anesthesiology
• Critical Care Medicine
• Obesity Medicine

Background:

• Difficult intubation (DI) poses risks for obese patients.
• Predictive models can aid in screening for airway difficulty.
• Obesity is a significant risk factor for intubation complications.

Purpose of the Study:

• To develop and evaluate a practical, multivariate predictive model for difficult intubation in obese patients.
• To assess the model's performance in identifying patients with a high likelihood of DI.

Main Methods:

• Prospective, multi-center study of 1,015 obese adults (BMI ≥ 30 kg/m2) undergoing endotracheal intubation.
• Evaluated body mass index (BMI) and 10 preoperative airway tests.
• Defined DI as an intubation difficulty scale (IDS) score ≥ 5.

Main Results:

• The developed model incorporated BMI, modified Mallampati test (MMT), and neck circumference to thyromental distance ratio (NC/TM).
• The best predictive model achieved an area under the receiver operating characteristic curve (AUC) of 0.71, indicating fair predictive performance.
• Only 3.2% of patients experienced DI, with 15.8% having slight DI.

Conclusions:

• The developed predictive model for DI in obese patients demonstrated limited effectiveness for preoperative screening.
• Further research is needed to improve the accuracy of DI prediction in this population.