• Chara Liaskou, Eleftherios Vouzounerakis, Anastasia Trikoupi, and Chryssoula Staikou.
• General Hospital of Rethymnon, Department of Anesthesiology, Rethymnon, Greece. Electronic address: charaliaskou@gmail.com.
• Braz J Anesthesiol. 2020 Mar 1; 70 (2): 125-133.

Background And ObjectivesThe prediction of difficult laryngoscopy is based on tests that assess anatomic characteristics of face and neck. We aimed to identify the most accurate tests and propose a multivariate predictive model.MethodsThis prospective observational study included 1134 patients. Thyromental Distance (TMD), Sternomental Distance (STMD), Ratio of Height-to-Thyromental Distance (R-H/TMD), Neck Circumference (NC), Ratio of Neck Circumference-to-Thyromental Distance (R-NC/TMD), Hyomental Distance with head in Neutral Position (HMD-NP) and at Maximal Extension (HMD-HE), Ratio of Hyomental Distance at Maximal head extension-to-hyomental distance in neutral position (R-HMD), Mallampati Class (MLC), Upper Lip Bite Test (ULBT), Mouth Opening (MO) and Head Extension (HE) were assessed preoperatively. A Cormack-Lehane Grade ≥ 3 was defined as Difficult Laryngoscopy. Sensitivity, specificity, positive and negative predictive values were assessed for all tests. Multivariate analysis with logistic regression was used to create the predictive models.ResultsA model incorporating MLC, ULBT, HE, HMD-HE and R-NC/TMD showed high prognostic accuracy; x2(5)=109.12, p <0.001, AUC=0.86, p <0.001). Its sensitivity, specificity and negative predictive value were 82.3%, 74.8% and 97.4%, respectively. A second model including two measurements not requiring patient's cooperation (R-NC/TMD and HMD-HE) exhibited good prognostic performance; x2(2)=63.5, p <0.001, AUC=0.77, p <0.001. Among single tests, HE had the highest sensitivity (78.5%) and negative predictive value (96%).ConclusionsA five-variable model incorporating MLC, ULBT, HE, HMD-HE and R-NC/TMD showed satisfyingly high predictive value for difficult laryngoscopy. A model including R-NC/TMD and HMD-HE could be useful in incapable patients. The most accurate single predictor was HE.Copyright © 2020 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights reserved.

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