Prospective development and validation of an objective classification for difficult facemask ventilation: the MASCAN...

Area of Science:

• Anesthesiology
• Airway Management
• Medical Informatics

Background:

• Difficult facemask ventilation lacks a standardized definition, causing inconsistent identification in clinical practice.
• Objective classification is needed to improve consistency in research and patient care.

Purpose of the Study:

• To develop and validate an objective classification and numeric score for difficult facemask ventilation.
• To establish clear criteria for identifying challenging mask ventilation scenarios.

Main Methods:

• A prospective study of 400 patients undergoing tracheal intubation for ENT or maxillofacial surgery.
• Facemask ventilation was assessed for indicators including grip, airway adjuncts, operator, ventilation method, oxygen saturation, tidal volume, and leak fraction.
• A multivariable logistic regression model (MASCAN model) and score were developed using selected indicators.

Main Results:

• Difficult facemask ventilation occurred in 10.8% of patients.
• Five indicators formed the MASCAN model and score: two-handed grip, oral airway use, jaw thrust, low tidal volume, and significant oxygen saturation drop.
• The MASCAN model achieved an AUC of 0.96, and the MASCAN score achieved 0.94, demonstrating high accuracy.

Conclusions:

• The MASCAN score provides an objective, data-driven classification for difficult facemask ventilation.
• Defined thresholds of the MASCAN score can improve airway documentation.
• This score may inform and enhance future airway management strategies.