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Updated: Sep 11, 2026
Point-of-Care Ultrasound: A Review of Ultrasound Parameters for Predicting Difficult Airways
Published on: April 7, 2023
Anatomical level-dependent variation in ultrasonographic skin-to-epiglottis depth and its diagnostic performance for
Çağdaş Savran1, Özge Köner1, Sibel Temür1
1Department of Anesthesiology, Yeditepe University, Istanbul, Türkiye.
Background And Aims:
Ultrasonographic skin-to-epiglottis depth (SED) has been proposed as a predictor of difficult laryngoscopy (DL). Most studies have evaluated transverse measurements at a single anatomical level, and the influence of parasagittal imaging and measurement level on diagnostic performance remains unclear. This study aimed to assess anatomical level-dependent variation in parasagittal SED and to compare its diagnostic accuracy for predicting DL.
Methods:
In this prospective observational study, 150 adult patients undergoing elective surgery under general anaesthesia were evaluated preoperatively. Parasagittal SED was measured at three anatomical landmarks: the upper hyoid border (HUB), lower hyoid border (HLB), and thyrohyoid membrane (THM). Difficult laryngoscopy was defined as Cormack-Lehane grade III-IV. Diagnostic performance was analysed using receiver operating characteristic analysis.
Results:
DL occurred in 32 patients (21.3%). Parasagittal SED differed significantly across anatomical levels. HUB measurements demonstrated superior predictive performance [area under the curve (AUC) 0.86; 95% confidence interval 0.79-0.92] compared with HLB (AUC 0.75) and THM (AUC 0.65). The HUB/THM ratio showed similarly high discrimination (AUC 0.86). Conventional airway tests showed modest predictive values (AUC 0.62-0.72). Multivariable analysis identified HUB SED >24 mm, inter-incisor distance ≤4 cm, and upper lip bite test class II-III as independent predictors of DL.
Conclusion:
Parasagittal SED demonstrates anatomical level-dependent variability that affects diagnostic performance. Assessment at the upper hyoid border provides the highest discrimination and may improve ultrasound-based airway risk stratification.
