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Predictive performance of a multivariable difficult intubation model for obese patients

BACKGROUND: A predictive model of scores of difficult intubation (DI) may help physicians screen for airway difficulty to reduce morbidity and mortality in obese patients. The present study aimed to set up and evaluate the predictive performance of a newly developed, practical, multivariate DI model...

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Autores principales: Siriussawakul, Arunotai, Maboonyanon, Patcharee, Kueprakone, Subongkot, Samankatiwat, Suthasinee, Komoltri, Chulaluk, Thanakiattiwibun, Chayanan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117055/
https://www.ncbi.nlm.nih.gov/pubmed/30161197
http://dx.doi.org/10.1371/journal.pone.0203142
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author Siriussawakul, Arunotai
Maboonyanon, Patcharee
Kueprakone, Subongkot
Samankatiwat, Suthasinee
Komoltri, Chulaluk
Thanakiattiwibun, Chayanan
author_facet Siriussawakul, Arunotai
Maboonyanon, Patcharee
Kueprakone, Subongkot
Samankatiwat, Suthasinee
Komoltri, Chulaluk
Thanakiattiwibun, Chayanan
author_sort Siriussawakul, Arunotai
collection PubMed
description BACKGROUND: A predictive model of scores of difficult intubation (DI) may help physicians screen for airway difficulty to reduce morbidity and mortality in obese patients. The present study aimed to set up and evaluate the predictive performance of a newly developed, practical, multivariate DI model for obese patients. METHODS: A prospective multi-center study was undertaken on adults with a body mass index (BMI) of 30 kg/m(2) or more who were undergoing conventional endotracheal intubation. The BMI and 10 preoperative airway tests (namely, malformation of the teeth in the upper jaw, the modified Mallampati test [MMT], the upper lip bite test, neck mobility testing, the neck circumference [NC], the length of the neck, the interincisor gap, the hyomental distance, the thyromental distance [TM] and the sternomental distance) were examined. A DI was defined as one with an intubation difficulty scale (IDS) score ≥ 5. RESULTS: The 1,015 patients recruited for the study had a mean BMI of 34.2 (standard deviation: 4.3 kg/m(2)). The proportions for easy intubation, slight DI and DI were 81%, 15.8% and 3.2%, respectively. Drawing on the results of a multivariate analysis, clinically meaningful variables related to obesity (namely, BMI, MMT, and the ratio of NC to TM) were used to build a predictive model for DI. Nevertheless, the best model only had a fair predictive performance. The area under the receiver operating characteristic curve (AUC) was 0.71 (95% confidence interval 0.68–0.84). CONCLUSIONS: The predictive performance of the selected model showed limited benefit for preoperative screening to predict DI among obese patients.
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spelling pubmed-61170552018-09-16 Predictive performance of a multivariable difficult intubation model for obese patients Siriussawakul, Arunotai Maboonyanon, Patcharee Kueprakone, Subongkot Samankatiwat, Suthasinee Komoltri, Chulaluk Thanakiattiwibun, Chayanan PLoS One Research Article BACKGROUND: A predictive model of scores of difficult intubation (DI) may help physicians screen for airway difficulty to reduce morbidity and mortality in obese patients. The present study aimed to set up and evaluate the predictive performance of a newly developed, practical, multivariate DI model for obese patients. METHODS: A prospective multi-center study was undertaken on adults with a body mass index (BMI) of 30 kg/m(2) or more who were undergoing conventional endotracheal intubation. The BMI and 10 preoperative airway tests (namely, malformation of the teeth in the upper jaw, the modified Mallampati test [MMT], the upper lip bite test, neck mobility testing, the neck circumference [NC], the length of the neck, the interincisor gap, the hyomental distance, the thyromental distance [TM] and the sternomental distance) were examined. A DI was defined as one with an intubation difficulty scale (IDS) score ≥ 5. RESULTS: The 1,015 patients recruited for the study had a mean BMI of 34.2 (standard deviation: 4.3 kg/m(2)). The proportions for easy intubation, slight DI and DI were 81%, 15.8% and 3.2%, respectively. Drawing on the results of a multivariate analysis, clinically meaningful variables related to obesity (namely, BMI, MMT, and the ratio of NC to TM) were used to build a predictive model for DI. Nevertheless, the best model only had a fair predictive performance. The area under the receiver operating characteristic curve (AUC) was 0.71 (95% confidence interval 0.68–0.84). CONCLUSIONS: The predictive performance of the selected model showed limited benefit for preoperative screening to predict DI among obese patients. Public Library of Science 2018-08-30 /pmc/articles/PMC6117055/ /pubmed/30161197 http://dx.doi.org/10.1371/journal.pone.0203142 Text en © 2018 Siriussawakul et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Siriussawakul, Arunotai
Maboonyanon, Patcharee
Kueprakone, Subongkot
Samankatiwat, Suthasinee
Komoltri, Chulaluk
Thanakiattiwibun, Chayanan
Predictive performance of a multivariable difficult intubation model for obese patients
title Predictive performance of a multivariable difficult intubation model for obese patients
title_full Predictive performance of a multivariable difficult intubation model for obese patients
title_fullStr Predictive performance of a multivariable difficult intubation model for obese patients
title_full_unstemmed Predictive performance of a multivariable difficult intubation model for obese patients
title_short Predictive performance of a multivariable difficult intubation model for obese patients
title_sort predictive performance of a multivariable difficult intubation model for obese patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117055/
https://www.ncbi.nlm.nih.gov/pubmed/30161197
http://dx.doi.org/10.1371/journal.pone.0203142
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