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Clinical and functional prediction of moderate to severe obstructive sleep apnoea

Identifieur interne : 007026 ( Istex/Corpus ); précédent : 007025; suivant : 007027

Clinical and functional prediction of moderate to severe obstructive sleep apnoea

Auteurs : Caterina Bucca ; Luisa Brussino ; Milena Maria Maule ; Ileana Baldi ; Giuseppe Guida ; Beatrice Culla ; Franco Merletti ; Antonio Foresi ; Giovanni Rolla ; Roberto Mutani ; Alessandro Cicolin

Source :

RBID : ISTEX:E1D9BAF2361A029ACA6C87C0623964A9D13DECF9

English descriptors

Abstract

Introduction:  Upper airway inflammation and narrowing are characteristics of obstructive sleep apnoea (OSA). Inflammatory markers have been found to be increased in exhaled breath and induced sputum of patients with OSA.

Url:
DOI: 10.1111/j.1752-699X.2010.00223.x

Links to Exploration step

ISTEX:E1D9BAF2361A029ACA6C87C0623964A9D13DECF9

Le document en format XML

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<div type="abstract">Introduction:  Upper airway inflammation and narrowing are characteristics of obstructive sleep apnoea (OSA). Inflammatory markers have been found to be increased in exhaled breath and induced sputum of patients with OSA.</div>
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<hi rend="bold">Introduction: </hi>
Upper airway inflammation and narrowing are characteristics of obstructive sleep apnoea (OSA). Inflammatory markers have been found to be increased in exhaled breath and induced sputum of patients with OSA.</p>
<p>
<hi rend="bold">Objectives: </hi>
The aim of this study was to investigate if the measurement of exhaled nitric oxide (F
<hi rend="subscript">ENO</hi>
), as marker of airway inflammation, together with the forced mid‐expiratory/mid‐inspiratory airflow ratio (FEF
<hi rend="subscript">50</hi>
/FIF
<hi rend="subscript">50</hi>
), as marker of upper airway narrowing, may help to predict OSA.</p>
<p>
<hi rend="bold">Methods: </hi>
Two hundred one consecutive outpatients with suspected OSA were prospectively studied between January 2004 and December 2005. All patients underwent clinical examination, spirometry with measurement of FEF
<hi rend="subscript">50</hi>
/FIF
<hi rend="subscript">50</hi>
, maximum inspiratory pressure, arterial blood gas analysis, exhaled nitric oxide (F
<hi rend="subscript">ENO</hi>
) and overnight polysomnography. Linear regression models were used to evaluate the effect of measured variables on the apnoea–hypopnoea index (AHI). Models were cross‐validated by bootstrapping.</p>
<p>
<hi rend="bold">Results: </hi>
Most of the patients were obese and had severe OSA. FEF
<hi rend="subscript">50</hi>
/FIF
<hi rend="subscript">50</hi>
, F
<hi rend="subscript">ENO</hi>
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<hi rend="subscript">ENO</hi>
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<p>
<hi rend="bold">Conclusions: </hi>
The measurement of F
<hi rend="subscript">ENO</hi>
and of FEF
<hi rend="subscript">50</hi>
/FIF
<hi rend="subscript">50</hi>
improves the ability to predict OSA and may be used to identify patients who require a sleep study.</p>
<p>Please cite this paper as: Bucca C, Brussino L, Maule MM, Baldi I, Guida G, Culla B, Merletti F, Foresi A, Rolla G, Mutani R and Cicolin A. Clinical and functional prediction of moderate to severe obstructive sleep apnoea.
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<p>
<b>Introduction: </b>
Upper airway inflammation and narrowing are characteristics of obstructive sleep apnoea (OSA). Inflammatory markers have been found to be increased in exhaled breath and induced sputum of patients with OSA.</p>
<p>
<b>Objectives: </b>
The aim of this study was to investigate if the measurement of exhaled nitric oxide (F
<sub>ENO</sub>
), as marker of airway inflammation, together with the forced mid‐expiratory/mid‐inspiratory airflow ratio (FEF
<sub>50</sub>
/FIF
<sub>50</sub>
), as marker of upper airway narrowing, may help to predict OSA.</p>
<p>
<b>Methods: </b>
Two hundred one consecutive outpatients with suspected OSA were prospectively studied between January 2004 and December 2005. All patients underwent clinical examination, spirometry with measurement of FEF
<sub>50</sub>
/FIF
<sub>50</sub>
, maximum inspiratory pressure, arterial blood gas analysis, exhaled nitric oxide (F
<sub>ENO</sub>
) and overnight polysomnography. Linear regression models were used to evaluate the effect of measured variables on the apnoea–hypopnoea index (AHI). Models were cross‐validated by bootstrapping.</p>
<p>
<b>Results: </b>
Most of the patients were obese and had severe OSA. FEF
<sub>50</sub>
/FIF
<sub>50</sub>
, F
<sub>ENO</sub>
and an interaction term between smoking and F
<sub>ENO</sub>
contributed significantly to the predictive model for AHI, in addition to age, neck circumference, body mass index and carboxyhaemoglobin saturation. A nomogram to predict AHI was obtained, which converted the effect of each covariate in the model to a 0–100 scale. The nomogram showed a good predictive ability for AHI values between 25 and 64.</p>
<p>
<b>Conclusions: </b>
The measurement of F
<sub>ENO</sub>
and of FEF
<sub>50</sub>
/FIF
<sub>50</sub>
improves the ability to predict OSA and may be used to identify patients who require a sleep study.</p>
<p>Please cite this paper as: Bucca C, Brussino L, Maule MM, Baldi I, Guida G, Culla B, Merletti F, Foresi A, Rolla G, Mutani R and Cicolin A. Clinical and functional prediction of moderate to severe obstructive sleep apnoea.
<i>Clin Respir J</i>
2011; 5: 219–226.</p>
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<b>Authorship</b>
: Bucca, Brussino and Cicolin are principal investigators and wrote the report. Bucca, Cicolin, Foresi, Mutani and Rolla were responsible for data review and interpretation. Maule, Baldi and Merletti planned and performed the statistical analysis. Culla and Guida did the clinical examination. The OSA group performed patients' selection, sleep questionnaire and polysomnography. All authors have participated in planning the study and in interpretation of the results and have seen and approved the final version.</p>
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<b>Ethics</b>
: The study was approved by the local ethics committee, and patients gave their informed consent to the study.</p>
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<b>Conflicts of interest</b>
: The authors have stated explicitly that there are no conflicts of interest in connection with this article.</p>
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<affiliation>E-mail: caterina.bucca@unito.it</affiliation>
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<name type="personal">
<namePart type="given">Luisa</namePart>
<namePart type="family">Brussino</namePart>
<affiliation>Dipartimento di Scienze Biomediche e Oncologia Umana, Università di Torino, Torino, Italia</affiliation>
<role>
<roleTerm type="text">author</roleTerm>
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<name type="personal">
<namePart type="given">Milena Maria</namePart>
<namePart type="family">Maule</namePart>
<affiliation>Unità di Epidemiologia dei Tumori, CPO Piemonte, CeRMS, Università di Torino, Torino, Italia</affiliation>
<role>
<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ileana</namePart>
<namePart type="family">Baldi</namePart>
<affiliation>Unità di Epidemiologia dei Tumori, CPO Piemonte, CeRMS, Università di Torino, Torino, Italia</affiliation>
<role>
<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Giuseppe</namePart>
<namePart type="family">Guida</namePart>
<affiliation>Dipartimento di Scienze Biomediche e Oncologia Umana, Università di Torino, Torino, Italia</affiliation>
<role>
<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Beatrice</namePart>
<namePart type="family">Culla</namePart>
<affiliation>Dipartimento di Scienze Biomediche e Oncologia Umana, Università di Torino, Torino, Italia</affiliation>
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<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Franco</namePart>
<namePart type="family">Merletti</namePart>
<affiliation>Unità di Epidemiologia dei Tumori, CPO Piemonte, CeRMS, Università di Torino, Torino, Italia</affiliation>
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<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Antonio</namePart>
<namePart type="family">Foresi</namePart>
<affiliation>Unità Respiratoria, Sesto San Giovanni Hospital, Sesto San Giovanni, Italia</affiliation>
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<roleTerm type="text">author</roleTerm>
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<name type="personal">
<namePart type="given">Giovanni</namePart>
<namePart type="family">Rolla</namePart>
<affiliation>Dipartimento di Scienze Biomediche e Oncologia Umana, Università di Torino, Torino, Italia</affiliation>
<role>
<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Roberto</namePart>
<namePart type="family">Mutani</namePart>
<affiliation>Centro di Medicina del Sonno, Dipartimento di Neuroscienze, Università di Torino, Torino, Italia</affiliation>
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<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alessandro</namePart>
<namePart type="family">Cicolin</namePart>
<affiliation>Centro di Medicina del Sonno, Dipartimento di Neuroscienze, Università di Torino, Torino, Italia</affiliation>
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<dateIssued encoding="w3cdtf">2011-10</dateIssued>
<edition>Received: 25 January 2010; Revision requested: 05 July 2010; Accepted: 22 August 2010</edition>
<copyrightDate encoding="w3cdtf">2011</copyrightDate>
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<abstract>Introduction:  Upper airway inflammation and narrowing are characteristics of obstructive sleep apnoea (OSA). Inflammatory markers have been found to be increased in exhaled breath and induced sputum of patients with OSA.</abstract>
<abstract>Objectives:  The aim of this study was to investigate if the measurement of exhaled nitric oxide (FENO), as marker of airway inflammation, together with the forced mid‐expiratory/mid‐inspiratory airflow ratio (FEF50/FIF50), as marker of upper airway narrowing, may help to predict OSA.</abstract>
<abstract>Methods:  Two hundred one consecutive outpatients with suspected OSA were prospectively studied between January 2004 and December 2005. All patients underwent clinical examination, spirometry with measurement of FEF50/FIF50, maximum inspiratory pressure, arterial blood gas analysis, exhaled nitric oxide (FENO) and overnight polysomnography. Linear regression models were used to evaluate the effect of measured variables on the apnoea–hypopnoea index (AHI). Models were cross‐validated by bootstrapping.</abstract>
<abstract>Results:  Most of the patients were obese and had severe OSA. FEF50/FIF50, FENO and an interaction term between smoking and FENO contributed significantly to the predictive model for AHI, in addition to age, neck circumference, body mass index and carboxyhaemoglobin saturation. A nomogram to predict AHI was obtained, which converted the effect of each covariate in the model to a 0–100 scale. The nomogram showed a good predictive ability for AHI values between 25 and 64.</abstract>
<abstract>Conclusions:  The measurement of FENO and of FEF50/FIF50 improves the ability to predict OSA and may be used to identify patients who require a sleep study.</abstract>
<abstract>Please cite this paper as: Bucca C, Brussino L, Maule MM, Baldi I, Guida G, Culla B, Merletti F, Foresi A, Rolla G, Mutani R and Cicolin A. Clinical and functional prediction of moderate to severe obstructive sleep apnoea. Clin Respir J 2011; 5: 219–226.</abstract>
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<genre>keywords</genre>
<topic>BMI</topic>
<topic>exhaled nitric oxide</topic>
<topic>inspiratory flow–volume curve</topic>
<topic>nomogram</topic>
<topic>obstructive sleep apnoea</topic>
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<identifier type="ISSN">1752-6981</identifier>
<identifier type="eISSN">1752-699X</identifier>
<identifier type="DOI">10.1111/(ISSN)1752-699X</identifier>
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<date>2011</date>
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<caption>vol.</caption>
<number>5</number>
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<detail type="issue">
<caption>no.</caption>
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<identifier type="DOI">10.1111/j.1752-699X.2010.00223.x</identifier>
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<accessCondition type="use and reproduction" contentType="copyright">© 2010 Blackwell Publishing Ltd</accessCondition>
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