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

Abstract

We performed a case-controlled, double-blind study to examine the performance of three multivariate clinical models (Wilson, Arné, and Naguib models) in the prediction 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, thyromental distance, thyrosternal distance, neck circumference, 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 Arné (54.6%) or Wilson (40.2%) models. Both the Naguib (76.8%) and Arné (74.7%) model classified more intubations correctly (P = 0.01) than the Wilson model (66.5%). The specificity of Arné, 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 developed using logistic regression and includes thyromental 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.

Radiologic indicators for prediction of difficult laryngoscopy in patients with cervical spondylosis

“…Naguib et al23 applied radiological indicators to a predictive model of difficult airway and achieved a high sensitivity and AUC, greater than the Wilson score and Arnè model. Whether radiologic indicators have a high efficacy of predicting difficult laryngoscopy in patients with cervical spondylosis would be useful to know in the clinical setting.…”

Can Difficult Intubation Be Easily and Rapidly Predicted?

“…An article by Naguib et al 16 , published in Anesthesia & Analgesia in 2006, evaluated three scoring models for assessing difficult intubation: the Wilson (weight, cervical spine movement, temporomandibular joint movement, receding mandible and buck teeth), Arné (previous difficult intubation, diseases associated with difficult intubation, clinical symptoms of airway pathology, temporomandibular joint movement, cervical spine movement and the Mallampati score) and Naguib (height, IIG, TMD and the Mallampati score). However, not even the combination of examination methods is reliable.…”

Mallampati Test as a Predictor of Laryngoscopic View

“…The preanesthetic examination of the airways should be primarily aimed at detecting as many patients with difficult airways as possible. This is necessary for minimizing the risk of unanticipated difficult/failed intubation 17 . From this point of view, the sensitivity of a test may be a more valuable parameter for predicting difficult intubation than its specificity.…”

“…The test for predicting difficult intubation should have high accuracy, sensitivity and positive predictive value to identify all patients in whom intubation will be difficult 17 . Apparently, no clinical test, the Mallampati scoring system being no exception, can meet these criteria when used alone.…”

“…Effective and reliable prediction requires a com-Mallampati test as a predictor of laryngoscopic view bination of several parameters (e.g. age, height, weight, BMI, MMT, head and neck movement, dentition status, upper lip bite test [18][19][20] , interincisor gap 17,21,22 , and thyromental distance 17,22,23 ). Usually, the more parameters are used, the higher is the accuracy of prediction.…”