Ultrasonographic evaluation of palatoglossal space may predict difficult mask ventilation: Study

Recent study explores the use of Modified Mallampati grading (MMG), ultrasonography at the submandibular region, and tongue thickness (TT) to predict difficult mask ventilation (DMV) and difficult laryngoscopy (DL). Unanticipated difficult mask ventilation has a high incidence rate despite various predictors for anticipating it, highlighting the need for accurate assessments. MMG and ultrasonography are discussed as potential tools to visualize airway structures and predict airway closure. The study involved adult patients undergoing elective surgery under general anesthesia, where the submandibular region was assessed using ultrasonography to measure palatoglossal space (PGS) and tongue thickness. PGS was significantly associated with DMV, with an area under the curve (AUC) of 0.989, indicating its high predictive value. A PGS cut-off value of 6.8 mm had a sensitivity of 94.4% in predicting DMV, making it a valuable tool for airway assessment.

Assessment of Tongue Thickness and Palatoglossal Space in Predicting Difficult Mask Ventilation

Tongue thickness was also assessed, with a cut-off value of 41 mm showing specificity but limited sensitivity in predicting DMV. The study emphasizes the simplicity and effectiveness of assessing PGS compared to obtaining dimensions, highlighting its utility as a rapid point-of-care ultrasound tool for predicting DMV. Additionally, the study compared PGS and TT in predicting both DMV and DL, providing insights into their respective sensitivities and specificities. The findings showed that an obliterated PGS had high sensitivity in predicting DL, indicating its potential as a robust predictor for airway difficulties.

Utility of Palatoglossal Space and Tongue Thickness in Predicting Airway Difficulties

The research also discusses previous studies that attempted to create scoring systems for identifying DMV but notes the challenges of using multiple parameters in assessments. Instead, the study suggests that PGS could serve as a valuable single parameter for predicting DMV due to its high sensitivity. The study concludes that PGS, alongside TT, can offer valuable insights into predicting airway difficulties during procedures requiring mask ventilation and laryngoscopy. Overall, the use of PGS and TT through ultrasonography presents promising avenues for enhancing the prediction of difficult airway management in clinical practice.

Key Points

- Modified Mallampati grading (MMG), ultrasonography at the submandibular region, and tongue thickness (TT) were studied to predict difficult mask ventilation (DMV) and difficult laryngoscopy (DL) in adult patients undergoing elective surgery.

- Ultrasonography was used to measure palatoglossal space (PGS) in the submandibular region, with PGS showing a significant association with DMV, indicated by an AUC of 0.989 and a sensitivity of 94.4% at a cut-off value of 6.8 mm.

- Tongue thickness was also assessed, but with limited sensitivity in predicting DMV, contrasting with the effectiveness of PGS assessment.

- An obliterated PGS was found to have high sensitivity in predicting DL, suggesting its potential as a robust predictor for airway difficulties.

- Previous studies used multiple parameters for DMV prediction, but this study suggests that PGS alone could be a valuable single parameter due to its high sensitivity.

- The study concludes that PGS, in combination with TT, offers valuable insights into predicting airway difficulties during procedures involving mask ventilation and laryngoscopy, showing promising avenues for improving difficult airway management predictions in clinical settings.

Reference –

Sekhar S, Kundra P, Mohan VK, Senthilnathan M, Ramesh A. Ultrasonographic evaluation of palatoglossal space to predict difficult mask ventilation – A prospective observational study. Indian J Anaesth 2025;69:315-8.