Predictive Performance of Three Multivariate Difficult Tracheal Intubation Models: A Double-blind, Case-controlled Study

We performed a case-controlled, double-blind study to examine the performance of three multivariate clinical models(Wilson,Arne´,andNaguibmodels)intheprediction of unanticipated difficult intubation. The study group consisted of 97 patients in whom an unanticipated difficult intubation had occurred. For each difficult intubation patient, a matched control patient was selected in whom tracheal intubation had been easily accomplished. Postoperatively, a blinded investigator evaluated both patients. The clinical assessment included the patient’s weight, height, age, Mallampati score, interincisor gap, thyromentaldistance,thyrosternaldistance,neckcircumference, Wilson risk sum score, history of previous difficult intubation, and diseases associated with difficult laryngoscopy or intubation. The Naguib model was significantly more sensitive (81.4%; P 0.0001) than the Arne´ (54.6%) or Wilson (40.2%) models. Both the Naguib (76.8%) and Arne´ (74.7%) model classified more intubations correctly (P 0.01) than the Wilson model (66.5%). The specificity of Arne´, Wilson, and Naguib model was 94.9%, 92.8%, and 72.2%, respectively (P 0.0001). The corresponding area under the receiver operating characteristic curve was 0.87, 0.79, and 0.82, respectively. Our new model for prediction of difficult intubation was developedusinglogisticregressionandincludesthyromental distance, Mallampati score, interincisor gap, and height. This model is 82.5% sensitive and 85.6% specific with an area under the receiver operating characteristic curve of 0.90. (Anesth Analg 2006;102:818–24)