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A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures

BACKGROUND: Airway management is challenging in children with Robin sequence (RS) requiring mandibular distraction osteogenesis (MDO). We derived and validated a prediction rule to identify difficult intubation before MDO for children with RS based on craniofacial computed tomography (CT) images. ME...

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Autores principales: Mao, Zhe, Zhang, Na, Cui, Yingqiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868728/
https://www.ncbi.nlm.nih.gov/pubmed/31752712
http://dx.doi.org/10.1186/s12871-019-0889-1
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author Mao, Zhe
Zhang, Na
Cui, Yingqiu
author_facet Mao, Zhe
Zhang, Na
Cui, Yingqiu
author_sort Mao, Zhe
collection PubMed
description BACKGROUND: Airway management is challenging in children with Robin sequence (RS) requiring mandibular distraction osteogenesis (MDO). We derived and validated a prediction rule to identify difficult intubation before MDO for children with RS based on craniofacial computed tomography (CT) images. METHOD: This was a retrospective study of 69 children with RS requiring MDO from November 2016 to June 2018. Multiple CT imaging parameters and baseline characteristic (sex, age, gestational age, body mass index [BMI]) were compared between children with normal and difficult intubation according to Cormack−Lehane classification. A clinical prediction rule was established to identify difficult intubation using group differences in CT parameters (eleven distances, six angles, one section cross-sectional area, and three segment volumes) and clinicodemographic characteristics. Predictive accuracy was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: The overall incidence of difficult intubation was 56.52%, and there was no significant difference in sex ratio, age, weight, height, BMI, or gestational age between groups. The distance between the root of the tongue and posterior pharyngeal wall was significantly shorter, the bilateral mandibular angle shallower, and the cross-sectional area at the epiglottis tip smaller in the difficult intubation group. A clinical prediction rule based on airway cross-sectional area at the tip of the epiglottis was established. Area > 36.97 mm(2) predicted difficult intubation while area < 36.97 mm(2) predicted normal intubation with 100% sensitivity, 62.5% specificity, 78.6% positive predictive value, and 100% negative predictive value (area under the ROC curve = 0.8125). CONCLUSION: Computed tomography measures can objectively evaluate upper airway morphology in patients with RS for prediction of difficult intubation. If validated in a larger series, the measures identified could be incorporated into airway assessment tools to guide treatment decisions. This was a retrospective study and was granted permission to access and use these medical records by the ethics committee of Guangzhou Women and Children’s Medical Center. TRIALS REGISTRATION: Registration No. ChiCTR1800018252, NaZhang, Sept 7 2018.
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spelling pubmed-68687282019-12-12 A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures Mao, Zhe Zhang, Na Cui, Yingqiu BMC Anesthesiol Research Article BACKGROUND: Airway management is challenging in children with Robin sequence (RS) requiring mandibular distraction osteogenesis (MDO). We derived and validated a prediction rule to identify difficult intubation before MDO for children with RS based on craniofacial computed tomography (CT) images. METHOD: This was a retrospective study of 69 children with RS requiring MDO from November 2016 to June 2018. Multiple CT imaging parameters and baseline characteristic (sex, age, gestational age, body mass index [BMI]) were compared between children with normal and difficult intubation according to Cormack−Lehane classification. A clinical prediction rule was established to identify difficult intubation using group differences in CT parameters (eleven distances, six angles, one section cross-sectional area, and three segment volumes) and clinicodemographic characteristics. Predictive accuracy was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: The overall incidence of difficult intubation was 56.52%, and there was no significant difference in sex ratio, age, weight, height, BMI, or gestational age between groups. The distance between the root of the tongue and posterior pharyngeal wall was significantly shorter, the bilateral mandibular angle shallower, and the cross-sectional area at the epiglottis tip smaller in the difficult intubation group. A clinical prediction rule based on airway cross-sectional area at the tip of the epiglottis was established. Area > 36.97 mm(2) predicted difficult intubation while area < 36.97 mm(2) predicted normal intubation with 100% sensitivity, 62.5% specificity, 78.6% positive predictive value, and 100% negative predictive value (area under the ROC curve = 0.8125). CONCLUSION: Computed tomography measures can objectively evaluate upper airway morphology in patients with RS for prediction of difficult intubation. If validated in a larger series, the measures identified could be incorporated into airway assessment tools to guide treatment decisions. This was a retrospective study and was granted permission to access and use these medical records by the ethics committee of Guangzhou Women and Children’s Medical Center. TRIALS REGISTRATION: Registration No. ChiCTR1800018252, NaZhang, Sept 7 2018. BioMed Central 2019-11-21 /pmc/articles/PMC6868728/ /pubmed/31752712 http://dx.doi.org/10.1186/s12871-019-0889-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Mao, Zhe
Zhang, Na
Cui, Yingqiu
A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures
title A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures
title_full A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures
title_fullStr A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures
title_full_unstemmed A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures
title_short A clinical prediction rule to identify difficult intubation in children with Robin sequence requiring mandibular distraction osteogenesis based on craniofacial CT measures
title_sort clinical prediction rule to identify difficult intubation in children with robin sequence requiring mandibular distraction osteogenesis based on craniofacial ct measures
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868728/
https://www.ncbi.nlm.nih.gov/pubmed/31752712
http://dx.doi.org/10.1186/s12871-019-0889-1
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