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Observational Study
Effectiveness and Validity of Sonographic Upper Airway Evaluation to Predict Difficult Laryngoscopy.
- Pawel Andruszkiewicz, Jacek Wojtczak, Dorota Sobczyk, Orest Stach, and Ilona Kowalik.
- Second Department of Anesthesiology and Intensive Care, Warsaw Medical University, Warsaw, Poland paul.andruszkiewicz@gmail.com.
- J Ultrasound Med. 2016 Oct 1; 35 (10): 2243-52.
ObjectivesOur objective was to evaluate the effectiveness of 9 airway sonographic parameters imaged from the submandibular view as predictors of difficult laryngoscopy. Additionally, we aimed to evaluate the validity of the models of combined sonographic and clinical tests in predicting difficult laryngoscopy.MethodsThis study analyzed a sample of 199 patients who were categorized as having easy (grades 1 and 2) or difficult (grades 3 and 4) laryngoscopy during general anesthesia with endotracheal intubation based on the laryngoscopic criteria of Cormack and Lahane (Anaesthesia 1984; 39:1105-1111). Nine sonographic parameters imaged from the submandibular view, including the hyomental distance in neutral and extended positions, hyomental distance ratio, tongue cross-sectional area, tongue width, tongue volume, tongue thickness-to-oral cavity height ratio, and floor of the mouth muscle cross-sectional area and volume, were analyzed. The validity of the models encompassing combined screening tests was assessed.ResultsTwenty-two patients (11.1%) were categorized as having difficult laryngoscopy. Statistically significant differences between patients with difficult and easy laryngoscopy were noted for 5 of 9 parameters. The diagnostic validity profiles showed poor sensitivity (9.1%-42.9%) and positive predictive value (4.5%-66.7%), but good specificity (71.8%-97.7%) and negative predictive value (87.1%-94.5%). The combination of tests improved the diagnostic validity profile (area under the curve, 0.852).ConclusionsSonographic predictors may help identify patients with difficult laryngoscopy. Individual measures have unsatisfactory diagnostic profiles. The models based on combined tests have improved diagnostic value.
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