Predicting Difficult Intubation in Emergency Department by Intubation Assessment Score

Background The difficult intubation is associated with failure of emergency tracheal intubation. This study aimed to develop and validate a model for predicting difficult intubation in emergency department (ED). Methods A cross-sectional study was conducted in the ED. We collected data from all consecutive adult patients who underwent emergency tracheal intubation. Patients were excluded if they were intubated by low experience intubator. The difficult intubation was defined by grade III or IV of Cormack and Lehane classification. We used multivariable regression model to identify significant predictors of difficult intubation and weighted points proportional to the beta coefficient values. The ability to discriminate was quantified by using the area under receiver operating characteristics curve (AuROC). The bootstrapping method was used to validate the performance. Results A total of 1,212 intubations were analyzed. One hundred and fifty-seven intubations were enrolled in difficult intubation group. Five independence predictors were identified, and each was assigned a number of points proportional to its beta coefficient: male gender (one), large tongue (two), limit mouth opening (two), poor neck mobility (two), and presence of obstructed airway (three). Intubation assessment score model was created and applied to all subjects. The AuROC was 0.81 (95% confidence interval (CI): 0.77 - 0.85) for the development dataset, and 0.80 (95% CI: 0.76 - 0.85) for the validation dataset. We defined three risk groups: low risk (zero to one points), intermediate risk (two to three points), and high risk (above three points), and the difficult intubation rate was 4.7%, 22.5%, and 53.6%, respectively. Conclusions Intubation assessment score model was constructed from patients' simple characteristics and performed well in predicting difficult intubation and can discriminate between with and without difficult intubation.