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Anatomic features of the neck as predictive markers of difficult direct laryngoscopy in men and women: A prospective study

Identifieur interne : 001C91 ( Main/Exploration ); précédent : 001C90; suivant : 001C92

Anatomic features of the neck as predictive markers of difficult direct laryngoscopy in men and women: A prospective study

Auteurs : Liaskou Chara [Grèce] ; Vouzounerakis Eleftherios [Grèce] ; Moirasgenti Maria [Grèce] ; Trikoupi Anastasia [Grèce] ; Staikou Chryssoula [Grèce]

Source :

RBID : PMC:4050935

Abstract

Background and Aims:

Difficult airway assessment is based on various anatomic parameters of upper airway, much of it being concentrated on oral cavity and the pharyngeal structures. The diagnostic value of tests based on neck anatomy in predicting difficult laryngoscopy was assessed in this prospective, open cohort study.

Methods:

We studied 341 adult patients scheduled to receive general anaesthesia. Thyromental distance (TMD), sternomental distance (STMD), ratio of height to thyromental distance (RHTMD) and neck circumference (NC) were measured pre-operatively. The laryngoscopic view was classified according to the Cormack–Lehane Grade (1-4). Difficult laryngoscopy was defined as Cormack–Lehane Grade 3 or 4. The optimal cut-off points for each variable were identified by using receiver operating characteristic analysis. Sensitivity, specificity and positive predictive value and negative predictive value (NPV) were calculated for each test. Multivariate analysis with logistic regression, including all variables, was used to create a predictive model. Comparisons between genders were also performed.

Results:

Laryngoscopy was difficult in 12.6% of the patients. The cut-off values were: TMD ≤7 cm, STMD ≤15 cm, RHTMD >18.4 and NC >37.5 cm. The RHTMD had the highest sensitivity (88.4%) and NPV (95.2%), while TMD had the highest specificity (83.9%). The area under curve (AUC) for the TMD, STMD, RHTMD and NC was 0.63, 0.64, 0.62 and 0.54, respectively. The predictive model exhibited a higher and statistically significant diagnostic accuracy (AUC: 0.68, P < 0.001). Gender-specific cut-off points improved the predictive accuracy of NC in women (AUC: 0.65).

Conclusions:

The TMD, STMD, RHTMD and NC were found to be poor single predictors of difficult laryngoscopy, while a model including all four variables had a significant predictive accuracy. Among the studied tests, gender-specific cut-off points should be used for NC.


Url:
DOI: 10.4103/0019-5049.130822
PubMed: 24963183
PubMed Central: 4050935


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<title>Methods:</title>
<p>We studied 341 adult patients scheduled to receive general anaesthesia. Thyromental distance (TMD), sternomental distance (STMD), ratio of height to thyromental distance (RHTMD) and neck circumference (NC) were measured pre-operatively. The laryngoscopic view was classified according to the Cormack–Lehane Grade (1-4). Difficult laryngoscopy was defined as Cormack–Lehane Grade 3 or 4. The optimal cut-off points for each variable were identified by using receiver operating characteristic analysis. Sensitivity, specificity and positive predictive value and negative predictive value (NPV) were calculated for each test. Multivariate analysis with logistic regression, including all variables, was used to create a predictive model. Comparisons between genders were also performed.</p>
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<title>Results:</title>
<p>Laryngoscopy was difficult in 12.6% of the patients. The cut-off values were: TMD ≤7 cm, STMD ≤15 cm, RHTMD >18.4 and NC >37.5 cm. The RHTMD had the highest sensitivity (88.4%) and NPV (95.2%), while TMD had the highest specificity (83.9%). The area under curve (AUC) for the TMD, STMD, RHTMD and NC was 0.63, 0.64, 0.62 and 0.54, respectively. The predictive model exhibited a higher and statistically significant diagnostic accuracy (AUC: 0.68,
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<p>The TMD, STMD, RHTMD and NC were found to be poor single predictors of difficult laryngoscopy, while a model including all four variables had a significant predictive accuracy. Among the studied tests, gender-specific cut-off points should be used for NC.</p>
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<name sortKey="Safavi, M" uniqKey="Safavi M">M Safavi</name>
</author>
<author>
<name sortKey="Honarmand, A" uniqKey="Honarmand A">A Honarmand</name>
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<author>
<name sortKey="Zare, N" uniqKey="Zare N">N Zare</name>
</author>
</analytic>
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<biblStruct>
<analytic>
<author>
<name sortKey="Arne, J" uniqKey="Arne J">J Arne</name>
</author>
<author>
<name sortKey="Descoins, P" uniqKey="Descoins P">P Descoins</name>
</author>
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</author>
<author>
<name sortKey="Ferrier, B" uniqKey="Ferrier B">B Ferrier</name>
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<author>
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</author>
<author>
<name sortKey="Aries, J" uniqKey="Aries J">J Ariès</name>
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</analytic>
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<name sortKey="Langeron, O" uniqKey="Langeron O">O Langeron</name>
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<author>
<name sortKey="Masso, E" uniqKey="Masso E">E Masso</name>
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</analytic>
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<analytic>
<author>
<name sortKey="Gonzalez, H" uniqKey="Gonzalez H">H Gonzalez</name>
</author>
<author>
<name sortKey="Minville, V" uniqKey="Minville V">V Minville</name>
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<analytic>
<author>
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<author>
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<analytic>
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</author>
<author>
<name sortKey="Kessell, G" uniqKey="Kessell G">G Kessell</name>
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<biblStruct>
<analytic>
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<name sortKey="Ronayne, M" uniqKey="Ronayne M">M Ronayne</name>
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<name sortKey="Cunningham, Aj" uniqKey="Cunningham A">AJ Cunningham</name>
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</div1>
</back>
</TEI>
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<list>
<country>
<li>Grèce</li>
</country>
<region>
<li>Attique (région)</li>
</region>
<settlement>
<li>Athènes</li>
</settlement>
</list>
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<country name="Grèce">
<noRegion>
<name sortKey="Chara, Liaskou" sort="Chara, Liaskou" uniqKey="Chara L" first="Liaskou" last="Chara">Liaskou Chara</name>
</noRegion>
<name sortKey="Anastasia, Trikoupi" sort="Anastasia, Trikoupi" uniqKey="Anastasia T" first="Trikoupi" last="Anastasia">Trikoupi Anastasia</name>
<name sortKey="Chryssoula, Staikou" sort="Chryssoula, Staikou" uniqKey="Chryssoula S" first="Staikou" last="Chryssoula">Staikou Chryssoula</name>
<name sortKey="Eleftherios, Vouzounerakis" sort="Eleftherios, Vouzounerakis" uniqKey="Eleftherios V" first="Vouzounerakis" last="Eleftherios">Vouzounerakis Eleftherios</name>
<name sortKey="Maria, Moirasgenti" sort="Maria, Moirasgenti" uniqKey="Maria M" first="Moirasgenti" last="Maria">Moirasgenti Maria</name>
</country>
</tree>
</affiliations>
</record>

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