Sleep and Breathing

, Volume 19, Issue 2, pp 623–630 | Cite as

Comorbidity modulates non invasive ventilation-induced changes in breath print of obstructive sleep apnea syndrome patients

  • Raffaele Antonelli Incalzi
  • Giorgio Pennazza
  • Simone Scarlata
  • Marco Santonico
  • Chiara Vernile
  • Livio Cortese
  • Elena Frezzotti
  • Claudio Pedone
  • Arnaldo D’Amico
Original Article



In obstructive sleep apnea syndrome (OSAS), exhaled volatile organic compounds (VOCs) change after long-term continuous positive airway pressure (CPAP). The objective of the study was to verify whether changes in VOCs pattern are detectable after the first night of CPAP and to identify correlates, if any, of these changes.


Fifty OSAS patients underwent a multidimensional assessment and breath print (BP) analysis through 28 sensors e-nose at baseline and after the first night of CPAP. Boxplots of individual BP evolution after CPAP and groups were compared by ANOVA and Fisher’s exact t. Partial least square discriminant analysis (PLS-DA), with leave-one-out as cross-validation was used to calculate to which extent basal BP could predicts changes in apnea-hypopnea index (AHI).


CPAP was effective in all the patients (delta AHI 35.8 events/h; residual AHI 6.0 events/h). BP dramatically changed after a single-night CPAP and changes conformed to two well-distinguished patterns: pattern C (n = 29), characterized by consonant boxplots, and pattern D (n = 21), with variably discordant boxplots. The average number of comorbid diseases (1.55 [standard deviation, SD 1.0] in group C, 3.14 [SD 1.8] in group D, p < 0.001) and the prevalence of selected comorbidity (diabetes mellitus, metabolic syndrome, and chronic heart failure), were the only features distinguishing groups.


We found that BP change after a single night of CPAP largely depends upon comorbidity. Comorbidity likely contributes to phenotypic variability in OSAS population. BP might qualify as a surrogate index of the response to and, later, compliance with CPAP.


Obstructive sleep apnea Continuous positive airway pressure Electronic nose Breath fingerprint Diagnosis Compliance to therapy 


Conflict of interest


Financial support


Author’s contribution and acknowledgement

Raffaele Antonelli Incalzi: study concept and design, analysis and interpretation of data, preparation of manuscript, revision of the manuscript for important intellectual content.

Giorgio Pennazza: acquisition of subjects and data, study concept and design, analysis and interpretation of data, statistical advice, preparation of manuscript

Simone Scarlata: acquisition of subjects and data, study concept and design, analysis and interpretation of data, preparation of manuscript.

Marco Santonico: acquisition of subjects and data, study concept and design, analysis and interpretation of data, preparation of manuscript.

Chiara Vernile: acquisition of subjects and data; analysis and interpretation of data;

Livio Cortese: acquisition of subjects and data.

Elena Frezzotti: acquisition of subjects and data.

Claudio Pedone: analysis and interpretation of data, statistical advice, preparation of manuscript.

Arnaldo D’Amico: analysis and interpretation of data, revision of the manuscript for important intellectual content


  1. 1.
    Drager LF, Togeiro SM, Polotsky VY, Lorenzi-Filho G (2013) Obstructive sleep apnea: a cardiometabolic risk in obesity and the metabolic syndrome. J Am Coll Cardiol 62:569–576CrossRefPubMedGoogle Scholar
  2. 2.
    Sánchez-de-la-Torre M, Campos-Rodriguez F, Barbé F (2013) Obstructive sleep apnoea and cardiovascular disease. Lancet Respir Med 1:61–72CrossRefPubMedGoogle Scholar
  3. 3.
    Quan SF, Wright R, Baldwin CM et al (2006) Obstructive sleep apnea-hypopnea and neurocognitive functioning in the Sleep Heart Health Study. Sleep Med 7:498–507CrossRefPubMedGoogle Scholar
  4. 4.
    Terán-Santos J, Jiménez-Gómez A, Cordero-Guevara J (1999) The association between sleep apnea and the risk of traffic accidents. Cooperative Group Burgos-Santander. N Engl J Med 340:847–851CrossRefPubMedGoogle Scholar
  5. 5.
    Phillips CL, Grunstein RR, Darendeliler MA et al (2013) Health outcomes of continuous positive airway pressure versus oral appliance treatment for obstructive sleep apnea: a randomized controlled trial. Am J Respir Crit Care Med 187:879–887CrossRefPubMedGoogle Scholar
  6. 6.
    Greulich T, Hattesohl A, Grabisch A et al (2013) Detection of obstructive sleep apnoea by an electronic nose. Eur Respir J 42:145–155CrossRefPubMedGoogle Scholar
  7. 7.
    Xie X, Pan L, Ren D, Du C, Guo Y (2013) Effects of continuous positive air way pressure therapy on systemic inflammation in obstructive sleep apnea: a meta-analysis. Sleep Med 14:1139–1150CrossRefPubMedGoogle Scholar
  8. 8.
    Cohen J (1988) Statistical power analysis for the behavioral sciences, 2nd edn. Lawrence Erlbaum, HillsdaleGoogle Scholar
  9. 9.
    Sharma SK, Kurian S, Malik V et al (2004) A stepped approach for prediction of obstructive sleep apnea in overtly asymptomatic obese subjects: a hospital based study. Sleep Med 5:351–357CrossRefPubMedGoogle Scholar
  10. 10.
    Dixon JB, Schachter LM, O'Brien PE (2003) Predicting sleep apnea and excessive day sleepiness in the severely obese: indicators for polysomnography. Chest 123:1134–1141CrossRefPubMedGoogle Scholar
  11. 11.
    Zonato AI, Bittencourt LR, Martinho FL, Júnior JF, Gregório LC, Tufik S (2003) Association of systematic head and neck physical examination with severity of obstructive sleep apnea-hypopnea syndrome. Laryngoscope 113:973–980CrossRefPubMedGoogle Scholar
  12. 12.
    Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R, Parthasarathy S, Quan SF, Redline S, Strohl KP, Davidson Ward SL, Tangredi MM, American Academy of Sleep Medicine (2012) Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med 8(5):597–619PubMedCentralPubMedGoogle Scholar
  13. 13.
    Redline S, Sanders MH, Lind BK et al (1998) Methods for obtaining and analyzing unattended PSG data for a multicenter study. Sleep Heart Health Res Group Sleep 21:759–767Google Scholar
  14. 14.
    Tenax® GR adsorbent resin for trapping volatiles. Scientific Instrument Services, Inc. []. Accessed 20 May 2014
  15. 15.
    Santonico M, Pennazza G, Grasso S, D’Amico A, Bizzarri M (2013) Design and test of a biosensor-based multisensorial system: a proof of concept study. Sensors (Basel) 13:16625–16640CrossRefGoogle Scholar
  16. 16.
    Rencher AC (2002) Methods of multivariate analysis. John Wiley & Sons Inc., New YorkCrossRefGoogle Scholar
  17. 17.
    Lehmann EL (1993) The Fisher, Neyman-Pearson theories of testing hypotheses: one theory or two? J Am Stat Assoc 88:1242–1249CrossRefGoogle Scholar
  18. 18.
    Corsonello A, Pedone C, Scarlata S, Zito A, Laino I, Antonelli-Incalzi R (2013) The oxygen therapy. Curr Med Chem 20:1103–1126CrossRefPubMedGoogle Scholar
  19. 19.
    Row BW (2007) In: Roach RC et al (eds) Chapter 5 in Hypoxia and the circulation. Springer, New York, p 5114Google Scholar
  20. 20.
    Koutsourelakis I, Perraki E, Economou NT, Dimitrokalli P, Vagiakis E, Roussos C, Zakynthinos S (2009) Predictors of residual sleepiness in adequately treated obstructive sleep apnoea patients. Eur Respir J 34:687–693CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Raffaele Antonelli Incalzi
    • 1
    • 2
  • Giorgio Pennazza
    • 3
  • Simone Scarlata
    • 1
  • Marco Santonico
    • 3
  • Chiara Vernile
    • 3
  • Livio Cortese
    • 1
  • Elena Frezzotti
    • 1
  • Claudio Pedone
    • 1
  • Arnaldo D’Amico
    • 3
  1. 1.Chair of Geriatrics, Unit of Respiratory PathophysiologyCampus Bio-Medico UniversityRomeItaly
  2. 2.San Raffaele- Cittadella della Carità FoundationTarantoItaly
  3. 3.Center for Integrated Research - CIR, Unit of Electronics for Sensor SystemsCampus Bio-Medico UniversityRomeItaly

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