Emergency front of neck access (eFONA) is recommended as a life-saving procedure to establish and secure the airway, thus restoring oxygenation in a can't intubate, can't oxygenate (CICO) scenario [[1], [2], [3]]. DAS guideline recommends that eFONA is carried out using a scalpel-bougie-tube technique [2]. Both technical and non-technical factors can contribute to the difficulty of this procedure and failure is common [[4], [5], [6]]. Increasing depth and impalpability of the CTM make the procedure technically challenging [7,8]. The distance from skin to CTM ranges from 8 to 19 mm [mean (SD) 13.69 (0.96) mm] in cadavers of mixed body habitus [9]. This distance increases by 2–3 mm for every increase of 5 kg M−2 in body mass index (BMI) [10]. In patients with BMI >40 kg M−2 the CTM depth is predicted to be at least 16.8 mm [11].

To adequately prepare for a difficult airway requiring eFONA, it is recommended that anaesthetists identify the CTM before the induction of anaesthesia [2,5]. Ultrasound localisation of the CTM is superior to digital palpation and recommended for use when the CTM is impalpable [[12], [13], [14], [15], [16], [17], [18], [19]]. Misidentification of the CTM is more common in female patients likely owing to the less prominent thyroid cartilage [20,21]. However, ultrasonography of the airway requires training and experience. The adoption of point-of-care ultrasonography by anaesthetists perioperatively has been hindered by both unfamiliarity and lack of ultrasound availability [22]. Therefore, a model to predict depth of CTM is useful for clinicians to adequately prepare for eFONA. This study aims to develop a multiple logistic regression model using patient characteristics and airway assessment parameters to predict depth of CTM.