ArticleIndian journal of anaesthesia2026
Anatomical level-dependent variation in ultrasonographic skin-to-epiglottis depth and its diagnostic performance for difficult laryngoscopy: A prospective observational study.
Article in Indian journal of anaesthesia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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.
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