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The value of multiparameter combinations for predicting difficult airways by ultrasound

BACKGROUND: Based on the upper airway anatomy and joint function parameters examined by ultrasound, a multiparameter ultrasound model for difficult airway assessment (ultrasound model) was established, and we evaluated its ability to predict difficult airways. METHODS: A prospective case-cohort stud...

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Autores principales: Xu, Jianling, Wang, Bin, Wang, Mingfang, Yao, Weidong, Chen, Yongquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533522/
https://www.ncbi.nlm.nih.gov/pubmed/36199026
http://dx.doi.org/10.1186/s12871-022-01840-0
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author Xu, Jianling
Wang, Bin
Wang, Mingfang
Yao, Weidong
Chen, Yongquan
author_facet Xu, Jianling
Wang, Bin
Wang, Mingfang
Yao, Weidong
Chen, Yongquan
author_sort Xu, Jianling
collection PubMed
description BACKGROUND: Based on the upper airway anatomy and joint function parameters examined by ultrasound, a multiparameter ultrasound model for difficult airway assessment (ultrasound model) was established, and we evaluated its ability to predict difficult airways. METHODS: A prospective case-cohort study of difficult airway prediction in adult patients undergoing elective surgery with endotracheal intubation under general anesthesia, and ultrasound phantom examination for difficult airway assessment before anesthesia, including hyomental distance, tongue thickness, mandibular condylar mobility, mouth opening, thyromental distance, and modified Mallampati tests, was performed. Receiver operating characteristic (ROC) curve analysis was used to evaluate the effectiveness of the ultrasound model and conventional airway assessment methods in predicting difficult airways. RESULTS: We successfully enrolled 1000 patients, including 51 with difficult laryngoscopy (DL) and 26 with difficult tracheal intubation (DTI). The area under the ROC curve (AUC) for the ultrasound model to predict DL was 0.84 (95% confidence interval [CI]: 0.82–0.87), and the sensitivity and specificity were 0.75 (95% CI: 0.60–0.86) and 0.82 (95% CI: 0.79–0.84), respectively. The AUC for predicting DTI was 0.89 (95% CI: 0.87–0.91), and the sensitivity and specificity were 0.85 (95% CI: 0.65–0.96) and 0.81 (95% CI: 0.78–0.83), respectively. Compared with mouth opening, thyromental distance, and modified Mallampati tests, the ultrasound model predicted a greater AUC for DL (P < 0.05). Compared with mouth opening and modified Mallampati tests, the ultrasound model predicted a greater AUC for DTI (P < 0.05). CONCLUSIONS: The ultrasound model has good predictive performance for difficult airways. TRIAL REGISTRATION: This study is registered on chictr.org.cn (ChiCTR-ROC-17013258); principal investigator: Jianling Xu; registration date: 06/11/2017). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12871-022-01840-0.
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spelling pubmed-95335222022-10-06 The value of multiparameter combinations for predicting difficult airways by ultrasound Xu, Jianling Wang, Bin Wang, Mingfang Yao, Weidong Chen, Yongquan BMC Anesthesiol Research BACKGROUND: Based on the upper airway anatomy and joint function parameters examined by ultrasound, a multiparameter ultrasound model for difficult airway assessment (ultrasound model) was established, and we evaluated its ability to predict difficult airways. METHODS: A prospective case-cohort study of difficult airway prediction in adult patients undergoing elective surgery with endotracheal intubation under general anesthesia, and ultrasound phantom examination for difficult airway assessment before anesthesia, including hyomental distance, tongue thickness, mandibular condylar mobility, mouth opening, thyromental distance, and modified Mallampati tests, was performed. Receiver operating characteristic (ROC) curve analysis was used to evaluate the effectiveness of the ultrasound model and conventional airway assessment methods in predicting difficult airways. RESULTS: We successfully enrolled 1000 patients, including 51 with difficult laryngoscopy (DL) and 26 with difficult tracheal intubation (DTI). The area under the ROC curve (AUC) for the ultrasound model to predict DL was 0.84 (95% confidence interval [CI]: 0.82–0.87), and the sensitivity and specificity were 0.75 (95% CI: 0.60–0.86) and 0.82 (95% CI: 0.79–0.84), respectively. The AUC for predicting DTI was 0.89 (95% CI: 0.87–0.91), and the sensitivity and specificity were 0.85 (95% CI: 0.65–0.96) and 0.81 (95% CI: 0.78–0.83), respectively. Compared with mouth opening, thyromental distance, and modified Mallampati tests, the ultrasound model predicted a greater AUC for DL (P < 0.05). Compared with mouth opening and modified Mallampati tests, the ultrasound model predicted a greater AUC for DTI (P < 0.05). CONCLUSIONS: The ultrasound model has good predictive performance for difficult airways. TRIAL REGISTRATION: This study is registered on chictr.org.cn (ChiCTR-ROC-17013258); principal investigator: Jianling Xu; registration date: 06/11/2017). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12871-022-01840-0. BioMed Central 2022-10-05 /pmc/articles/PMC9533522/ /pubmed/36199026 http://dx.doi.org/10.1186/s12871-022-01840-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Xu, Jianling
Wang, Bin
Wang, Mingfang
Yao, Weidong
Chen, Yongquan
The value of multiparameter combinations for predicting difficult airways by ultrasound
title The value of multiparameter combinations for predicting difficult airways by ultrasound
title_full The value of multiparameter combinations for predicting difficult airways by ultrasound
title_fullStr The value of multiparameter combinations for predicting difficult airways by ultrasound
title_full_unstemmed The value of multiparameter combinations for predicting difficult airways by ultrasound
title_short The value of multiparameter combinations for predicting difficult airways by ultrasound
title_sort value of multiparameter combinations for predicting difficult airways by ultrasound
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533522/
https://www.ncbi.nlm.nih.gov/pubmed/36199026
http://dx.doi.org/10.1186/s12871-022-01840-0
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