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Prediction of the Difficult Laryngoscopy with Ultrasound Measurements of Hyomental Distance Cover

Abstract

Ultrasound measurement of hyomental distance is promising as a predictor for difficult laryngoscopy in cases of difficult airway management. The aim of the study was to evaluate the prognostic value of ultrasound measurement of hyomental distance (HMD) for prediction of difficult laryngoscopy. Hyomental distance was sonographically measured in neutral (HMDn) and extreme head extension (HMDe) positions for fifty-six patients scheduled for elective surgery requiring tracheal intubation. Then the hyomental distance ratio (HMDR) was calculated. According to presence of difficult laryngoscopy assessed by the Cormack–Lehane (CL) score, patients were divided into a difficult laryngoscopy group (DL, n = 15) and easy laryngoscopy group (EL, n = 41). We calculated the sensitivity and specificity of HMDn, HMDe, and HMDR for difficult laryngoscopy. DL was present in 15 (27%) patients. We found a significant intergroup difference in HMDR between the DL and EL groups (1.12 ± 0.04 vs. 1.24 ± 0.06, respectively; p < 0.001). In contrast, we were not able to find a significant difference for HMDn and HMDr. HMDR had the highest sensitivity 86.7% and specificity 85.4% (p < 0.01) to predict difficult laryngoscopy, where the area under the curve was 0.939; p < 0.01 for HDMR < 1.2 cm. Moreover, we found that difficult laryngoscopy was associated with higher body mass index (BMI), with higher values in the DL group compared to EL patients (34.3 ± 9.1 vs. 28.5 ± 5.7 kg/m2, respectively; p = 0.035). HMDR < 1.2 cm measured by ultrasound might have a good predictive value for prediction of difficult laryngoscopy.

DOI: https://doi.org/10.2478/prolas-2022-0057 | Journal eISSN: 2255-890X | Journal ISSN: 1407-009X
Language: English
Page range: 372 - 376
Submitted on: Nov 15, 2021
Accepted on: Jun 30, 2022
Published on: Jul 23, 2022
Published by: Latvian Academy of Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2022 Zane Glāzniece-Kagane, Arvīds Bērziņš, Aleksandrs Kagans, Sergejs Grigorjevs, Agnese Ozoliņa, Biruta Mamaja, published by Latvian Academy of Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.