Skip to main content
Log in

Nasal pressure recordings to detect obstructive sleep apnea

  • Original Article
  • Published:
Sleep and Breathing Aims and scope Submit manuscript

Abstract

Obstructive sleep apnea (OSA) is a common disease. Given the costs of in-laboratory polysomnography (PSG), alternative ambulatory methods for accurate diagnosis are desirable. The objective of this study was to evaluate the performance of a simple device (SleepCheck) to identify patients with sleep apnea. A total of 30 consecutive patients with suspected OSA syndrome referred to the sleep clinic were prospectively evaluated with standard PSG and SleepCheck simultaneously during an in-laboratory, supervised full-night diagnostic study. The PSG apnea and hypopnea index (AHI) was evaluated according to standard criteria, and SleepCheck assessed the respiratory disturbance index (RDI) based on nasal cannula pressure fluctuations. Compared to the full-night PSG, SleepCheck systematically overscored respiratory events (the mean difference between SleepCheck RDI and PSG AHI was 27.4±13.3 events per hour). This overscoring was in part related to normal physiologic decreases in flow during rapid eye movement sleep or after an arousal. However, there was reasonable correlation between AHI and RDI (r=0.805). Receiver operating characteristic curves with threshold values of AHI of 10 and 20/h demonstrated areas under the curves (AUCs) of 0.915 and 0.910, respectively. Optimum combinations of sensitivity and specificity for these thresholds were calculated as 86.4/75.0 and 88.9/81.0, respectively. Overall, the SleepCheck substantially overscored apneas and hypopneas in patients with suspected OSA. However, after correction of the bias, the SleepCheck had reasonable accuracy with an AUC, sensitivity, and specificity similar to other ambulatory type 4 devices currently available.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Flemons WW (2000) Measuring health related quality of life in sleep apnea. Sleep 23(Suppl 4):S109–S114

    PubMed  Google Scholar 

  2. Young T, Peppard PE, Gottlieb DJ (2002) Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med 165:1217–1239

    Article  PubMed  Google Scholar 

  3. Colt HG, Haas H, Rich GB (1991) Hypoxemia vs sleep fragmentation as cause of excessive daytime sleepiness in obstructive sleep apnea. Chest 100:1542–1548

    Article  PubMed  CAS  Google Scholar 

  4. American Academy of Sleep Medicine Task Force (1999) Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. The report of an American Academy of Sleep Medicine Task Force. Sleep 22:667–689

    Google Scholar 

  5. Zamarron C, Gude F, Barcala J, Rodriguez JR, Romero PV (2003) Utility of oxygen saturation and heart rate spectral analysis obtained from pulse oximetric recordings in the diagnosis of sleep apnea syndrome. Chest 123:1567–1576

    Article  PubMed  Google Scholar 

  6. Magalang UJ, Dmochowski J, Veeramachaneni S, Draw A, Mador MJ, El-Solh A et al (2003) Prediction of the apnea–hypopnea index from overnight pulse oximetry. Chest 124:1694–1701

    Article  PubMed  Google Scholar 

  7. Netzer N, Eliasson AH, Netzer C, Kristo DA (2001) Overnight pulse oximetry for sleep-disordered breathing in adults: a review. Chest 120:625–633

    Article  PubMed  CAS  Google Scholar 

  8. Bagnato MC, Nery LE, Moura SM, Bittencourt LR, Tufik S (2000) Comparison of AutoSet and polysomnography for the detection of apnea–hypopnea events. Braz J Med Biol Res 33:515–519

    Article  PubMed  CAS  Google Scholar 

  9. Gugger M, Mathis J, Bassetti C (1995) Accuracy of an intelligent CPAP machine with in-built diagnostic abilities in detecting apnoeas: a comparison with polysomnography. Thorax 50:1199–1201

    Article  PubMed  CAS  Google Scholar 

  10. Rees K, Wraith PK, Berthon-Jones M, Douglas NJ (1998) Detection of apnoeas, hypopnoeas and arousals by the AutoSet in the sleep apnoea/hypopnoea syndrome. Eur Respir J 12:764–769

    Article  PubMed  CAS  Google Scholar 

  11. Mayer P, Meurice JC, Philip-Joet F, Cornette A, Rakotonanahary D, Meslier N et al (1998) Simultaneous laboratory-based comparison of ResMed Autoset with polysomnography in the diagnosis of sleep apnoea/hypopnoea syndrome. Eur Respir J 12:770–775

    Article  PubMed  CAS  Google Scholar 

  12. Ayas NT, Pittman S, MacDonald M, White DP (2003) Assessment of a wrist-worn device in the detection of obstructive sleep apnea. Sleep Med 4:435–442

    Article  PubMed  Google Scholar 

  13. Bar A, Pillar G, Dvir I, Sheffy J, Schnall RP, Lavie P (2003) Evaluation of a portable device based on peripheral arterial tone for unattended home sleep studies. Chest 123:695–703

    Article  PubMed  Google Scholar 

  14. Golpe R, Jimenez A, Carpizo R (2002) Home sleep studies in the assessment of sleep apnea/hypopnea syndrome. Chest 122:1156–1161

    Article  PubMed  Google Scholar 

  15. Shochat T, Hadas N, Kerkhofs M, Herchuelz A, Penzel T, Peter JH et al (2002) The SleepStrip: an apnoea screener for the early detection of sleep apnoea syndrome. Eur Respir J 19:121–126

    Article  PubMed  CAS  Google Scholar 

  16. Liesching TN, Carlisle C, Marte A, Bonitati A, Millman RP (2004) Evaluation of the accuracy of SNAP technology sleep sonography in detecting obstructive sleep apnea in adults compared to standard polysomnography. Chest 125:886–891

    Article  PubMed  Google Scholar 

  17. Nakano H, Hayashi M, Ohshima E, Nishikata N, Shinohara T (2004) Validation of a new system of tracheal sound analysis for the diagnosis of sleep apnea–hypopnea syndrome. Sleep 27:951–957

    PubMed  Google Scholar 

  18. Gorny SW, Allen RP, Krausman DT (2000) Evaluation of an unattended monitoring system for automated detection of sleep apnea. Sleep 23:A369

    Google Scholar 

  19. Gorny SW, Spiro JR, Phillips B, Allen RP, Krausman DT (2001) Initial findings from multi-site evaluation of an unattended monitoring system for automated detection of sleep disordered breathing events. Sleep 24:A387

    Google Scholar 

  20. Spiro JR, Gorny SW, Allen RP, Krausman DT (2002) Pilot evaluation of an ambulatory airflow pressure monitor for immediate identification of sleep disordered breathing events. Sleep 25:A275

    Google Scholar 

  21. Rechtschaffen A, Kales A (1977) A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. Brain Information Service, Los Angeles

    Google Scholar 

  22. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    PubMed  CAS  Google Scholar 

  23. Parra O, Garcia-Esclasans N, Montserrat JM, Garcia Eroles L, Ruiz J, Lopez JA et al (1997) Should patients with sleep apnoea/hypopnoea syndrome be diagnosed and managed on the basis of home sleep studies? Eur Respir J 10:1720–1724

    Article  PubMed  CAS  Google Scholar 

  24. Flemons WW, Littner MR, Rowley JA, Gay P, Anderson WM, Hudgel DW et al (2003) Home diagnosis of sleep apnea: a systematic review of the literature. An evidence review cosponsored by the American Academy of Sleep Medicine, the American College of Chest Physicians, and the American Thoracic Society. Chest 124:1543–1579

    Article  PubMed  Google Scholar 

  25. Bittencourt LR, Suchecki D, Tufik S, Peres C, Togeiro SM, Bagnato MC et al (2001) The variability of the apnoea–hypopnoea index. J Sleep Res 10:245–251

    Article  PubMed  CAS  Google Scholar 

  26. Portier F, Portmann A, Czernichow P, Vascaut L, Devin E, Benhamou D et al (2000) Evaluation of home versus laboratory polysomnography in the diagnosis of sleep apnea syndrome. Am J Respir Crit Care Med 162:814–818

    PubMed  CAS  Google Scholar 

  27. Kato J, Isono S, Tanaka A, Watanabe T, Araki D, Tanzawa H et al (2000) Dose-dependent effects of mandibular advancement on pharyngeal mechanics and nocturnal oxygenation in patients with sleep-disordered breathing. Chest 117:1065–1072

    Article  PubMed  CAS  Google Scholar 

  28. Petelle B, Vincent G, Gagnadoux F, Rakotonanahary D, Meyer B, Fleury B (2002) One-night mandibular advancement titration for obstructive sleep apnea syndrome: a pilot study. Am J Respir Crit Care Med 165:1150–1153

    PubMed  Google Scholar 

  29. Walker-Engstrom ML, Ringqvist I, Vestling O, Wilhelmsson B, Tegelberg A (2003) A prospective randomized study comparing two different degrees of mandibular advancement with a dental appliance in treatment of severe obstructive sleep apnea. Sleep Breath 7:119–130

    Article  PubMed  Google Scholar 

  30. de Almeida FR, Bittencourt LR, de Almeida CI, Tsuiki S, Lowe AA, Tufik S (2002) Effects of mandibular posture on obstructive sleep apnea severity and the temporomandibular joint in patients fitted with an oral appliance. Sleep 25:507–513

    PubMed  Google Scholar 

  31. Tsai WH, Vazquez JC, Oshima T, Dort L, Roycroft B, Lowe AA et al (2004) Remotely controlled mandibular positioner predicts efficacy of oral appliances in sleep apnea. Am J Respir Crit Care Med 170:366–370

    Article  PubMed  Google Scholar 

  32. Fleury B, Rakotonanahary D, Petelle B, Vincent G, Pelletier Fleury N, Meyer B et al (2004) Mandibular advancement titration for obstructive sleep apnea: optimization of the procedure by combining clinical and oximetric parameters. Chest 125:1761–1767

    Article  PubMed  Google Scholar 

  33. Raphaelson MA, Alpher EJ, Bakker KW, Perlstrom JR (1998) Oral appliance therapy for obstructive sleep apnea syndrome: progressive mandibular advancement during polysomnography. Cranio 16:44–50

    PubMed  CAS  Google Scholar 

  34. Lowe AA (2002) Oral appliances sleep apnea: pathogenesis, diagnosis and treatment. Marcel Dekker, New York

    Google Scholar 

Download references

Acknowledgements

The authors wish to thank Mrs. Ingrid Ellis for her editorial assistance in the final preparation of the manuscript. We are grateful for the statistical analysis provided by Ms. Mary Wong. The present study was supported by CNPq (Brazilian Government), who provided a scholarship to the first author (F.R.A.). One of the authors (N.T.A.) is supported by a Michael Smith Foundation for Health Research Scholar Award, a CIMR/BCLA new investigator award, and a departmental scholar award at UBC. In addition, SleepCheck was provided by IM Systems Inc., Baltimore.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fernanda Ribeiro de Almeida.

Additional information

This study was conducted at the Sleep Laboratory and Division of Orthodontics, The University of British Columbia, Canada

Rights and permissions

Reprints and permissions

About this article

Cite this article

de Almeida, F.R., Ayas, N.T., Otsuka, R. et al. Nasal pressure recordings to detect obstructive sleep apnea. Sleep Breath 10, 62–69 (2006). https://doi.org/10.1007/s11325-005-0042-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11325-005-0042-x

Keywords

Navigation