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28.01.2020 | Original Research

Ultrasonography for predicting a difficult laryngoscopy. Getting closer

Journal of Clinical Monitoring and Computing
Alejandro Martínez-García, José L. Guerrero-Orriach, María A. Pino-Gálvez
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Our objective was to evaluate the usefulness of five ultrasound measurements to predict a difficult laryngoscopy (DL). Prospective observational study. 50 patients underwent scheduled surgery under general anesthesia with orotracheal intubation with classical laryngoscopy at the University Hospital of Jaén (Spain). Sociodemographic variables, classic preintubation screening tests and ultrasound measurements of the neck soft tissue from skin to hyoid (DSH), epiglottis (DSE) and glottis (DSG) were obtained, as well as two measurements derived from the above: DSH + DSE and DSE − DSG. The relationship between a DL and ultrasound measurements was evaluated using t student test. The ROC Curve was used to establish the diagnostic accuracy of ultrasound measurements to discriminate a DL and logistic regression was used to establish a cut-off point. Multivariate analysis was performed to assess the impact of these measures in clinical practice. Patients with DL showed greater thickness of DSE (2.9 ± 0.46 cm vs 2.32 ± 0.54 cm; p = 0.001), DSH + DSE (4.25 ± 0.45 cm vs 3.62 ± 0.77 cm; p = 0.001) and DSE − DSG (1.83 ± 0.54 cm vs 1.24 ± 0.46 cm; p = 0.001) than those with an easy laryngoscopy. DSE and DSE − DSG had the highest diagnostic accuracy for DL with an area under the ROC curve of 0.79 [95%IC 0.66–0.92] and 0.82 [95%IC 0.68–0.96], respectively. It was established that DSE ≥ 3 cm, could predict a DL with a positive predictive value (PPV) of 69.23% [95%CI 40.3–98.2], and DSE − DSG ≥ 1.9 cm would do so with a PPV of 78.57% [95%CI 53.31–100%]. The multivariate analysis endorsed that DSE and DSE − DSG combined with classic tests (the Modified Mallampati score, the thyromental distance and the upper lip bite test) improved the preoperative detection of a DL. The inclusion of DSE and DSE − DSG in a multivariate model with classic parameters may offer the anesthesiologist better information for detecting a DL preoperatively.

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