Development of a multiple logistic regression model to predict depth of the cricothyroid membrane in the adult surgical population

Background

To adequately prepare for a difficult airway requiring emergency front of neck access, it is recommended that anaesthetists identify the cricothyroid membrane (CTM) before the induction of anaesthesia. In addition, the technique and success of eFONA depends on the depth of CTM. This study aims to develop a multiple logistic regression model using patient characteristics and airway assessment parameters to predict depth of the CTM.

Methods

The study was performed at University Hospitals Coventry and Warwickshire NHS Trust from October 2018 to February 2022. Following written informed consent and detailed airway assessment, ultrasonography of the neck was performed and depth of CTM was measured in supine neck extended position. We inspected the relationship of age, sex, weight, BMI, Mallampati score, thyromental distance, sternomental distance, inter-incisor distance, jaw protrusion, CTM palpability, neck extension and neck circumference with CTM depth. Each of these covariates were included in simple univariate logistic regression model as predictor with binary CTM as the response. Covariates that showed significance at p-value of 0.10 were included in a multiple logistic regression model.

Results

We analysed the data from 2578 patients. The mean (SD) depth of the CTM in male patients was 9.4 (2.7) mm and in female patients was 9.7 (3.1) mm. In simple univariate logistic regression, we found sex, weight, BMI, Mallampati score, sternomental distance, CTM palpability and neck circumference all to have a statistically significant relationship with CTM depth. There was a strong positive correlation between neck circumference and CTM depth.

Conclusion

We have developed a multiple logistic regression model for predicting CTM depth ≤13 mm based on sex, BMI, CTM palpability, sternomental distance and neck circumference with good sensitivity (0.80) and specificity (0.85).