Skip to main content

Advertisement

SpringerLink
Log in

Cardiopulmonary coupling analysis: changes before and after treatment with a mandibular advancement device

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

Abstract

Purpose

The aim of this study is to evaluate the changes of sleep quality in patients using a mandibular advancement device (MAD) for obstructive sleep apnea (OSA) based upon cardiopulmonary coupling (CPC).

Methods

A total of 52 patients (mean age 53.7 ± 9.6 years, range 33–74 years) were included in this study. Of them, there were 47 males (90.4 %). All subjects were diagnosed with OSA after in-laboratory full-night polysomnography and reevaluated after 3-month use of a MAD. At baseline, apnea-hypopnea index (AHI) was 33.6 ± 17.0, Epworth sleepiness scale was 10.5 ± 4.8, and Pittsburgh sleep quality index was 5.8 ± 2.8. The CPC parameters were extracted from single-lead electrocardiography of polysomnography. We compared CPC parameters at baseline with those after 3-month use of a MAD.

Results

All respiratory indices improved with the use of MAD. However, there were no differences in the sleep architectures except N3 sleep (3.7 ± 4.3 to 6.9 ± 6.4 %, p < 0.001). The CPC parameters showed a significant improvement with the use of MAD. Low-frequency coupling (59.5 ± 16.1 to 47.7 ± 14.8 %, p < 0.001) and elevated low-frequency coupling (44.6 ± 18.4 to 32.6 ± 15.7 %, p < 0.001) significantly decreased. High-frequency coupling (28.6 ± 16.0 to 36.5 ± 15.7 %, p = 0.004) and very low frequency coupling (11.7 ± 7.2 to 15.3 ± 6.6 %, p = 0.028) significantly increased. The change of AHI significantly correlated with changes of the CPC parameters: negatively correlated with high-frequency coupling change (r = −0.572, p < 0.001) and positively correlated with low-frequency and elevated low-frequency coupling changes (r = 0.604 and 0.497, respectively; p < 0.001 in both). However, the changes of Epworth sleepiness scale and Pittsburgh sleep quality index after MAD therapy showed no significant correlation with the changes in the CPC parameters.

Conclusions

To our knowledge, this is the first study to evaluate the quality of sleep in patients using a MAD for their OSA based upon CPC analysis. Low-frequency coupling decreased as AHI improved, while high-frequency coupling increased as AHI improved. The CPC parameters showed that the sleep quality was improved by MAD therapy.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Yoshida K (2000) Effects of a mandibular advancement device for the treatment of sleep apnea syndrome and snoring on respiratory function and sleep quality. Cranio 18(2):98–105

    CAS  PubMed  Google Scholar 

  2. Loredo JS, Ancoli-Israel S, Dimsdale JE (2001) Sleep quality and blood pressure dipping in obstructive sleep apnea. Am J Hypertens 14(9 Pt 1):887–892

    Article  CAS  PubMed  Google Scholar 

  3. Loredo JS, Ancoli-Israel S, Kim EJ, Lim WJ, Dimsdale JE (2006) Effect of continuous positive airway pressure versus supplemental oxygen on sleep quality in obstructive sleep apnea: a placebo-CPAP-controlled study. Sleep 29(4):564–571

    PubMed  Google Scholar 

  4. Penzel T, McNames J, Murray A, de Chazal P, Moody G, Raymond B (2002) Systematic comparison of different algorithms for apnoea detection based on electrocardiogram recordings. Med Biol Eng Comput 40(4):402–407

    Article  CAS  PubMed  Google Scholar 

  5. Roche F, Pichot V, Sforza E, Court-Fortune I, Duverney D, Costes F, Garet M, Barthelemy JC (2003) Predicting sleep apnoea syndrome from heart period: a time-frequency wavelet analysis. Eur Respir J 22(6):937–942

    Article  CAS  PubMed  Google Scholar 

  6. Penzel T, Kantelhardt JW, Grote L, Peter JH, Bunde A (2003) Comparison of detrended fluctuation analysis and spectral analysis for heart rate variability in sleep and sleep apnea. IEEE Trans Biomed Eng 50(10):1143–1151

    Article  PubMed  Google Scholar 

  7. Rajendra Acharya U, Paul Joseph K, Kannathal N, Lim CM, Suri JS (2006) Heart rate variability: a review. Med Biol Eng Comput 44(12):1031–1051

    Article  CAS  PubMed  Google Scholar 

  8. Thomas RJ, Mietus JE, Peng CK, Goldberger AL (2005) An electrocardiogram-based technique to assess cardiopulmonary coupling during sleep. Sleep 28(9):1151–1161

    PubMed  Google Scholar 

  9. Langley P, Bowers EJ, Murray A (2010) Principal component analysis as a tool for analyzing beat-to-beat changes in ECG features: application to ECG-derived respiration. IEEE Trans Biomed Eng 57(4):821–829

    Article  PubMed  Google Scholar 

  10. Kushida CA, Morgenthaler TI, Littner MR, Alessi CA, Bailey D, Coleman J Jr, Friedman L, Hirshkowitz M, Kapen S, Kramer M, Lee-Chiong T, Owens J, Pancer JP (2006) Practice parameters for the treatment of snoring and obstructive sleep apnea with oral appliances: an update for 2005. Sleep 29(2):240–243

    PubMed  Google Scholar 

  11. Thomas RJ, Mietus JE, Peng CK, Gilmartin G, Daly RW, Goldberger AL, Gottlieb DJ (2007) Differentiating obstructive from central and complex sleep apnea using an automated electrocardiogram-based method. Sleep 30(12):1756–1769

    PubMed Central  PubMed  Google Scholar 

  12. Lee SH, Choi JH, Park IH, Kim TH, Lee HM, Park HK, Thomas RJ, Shin C, Yun CH (2012) Measuring sleep quality after adenotonsillectomy in pediatric sleep apnea. Laryngoscope 122(9):2115–2121

    Article  PubMed  Google Scholar 

  13. The Report of an American Academy of Sleep Medicine Task Force (1999) Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. Sleep 22(5):667–89

    Google Scholar 

  14. Parrino L, Ferri R, Bruni O, Terzano MG (2012) Cyclic alternating pattern (CAP): the marker of sleep instability. Sleep Med Rev 16(1):27–45

    Article  PubMed  Google Scholar 

  15. Ramar K, Desrues B, Ramar P, Morgenthaler TI (2013) Analysis of cardiopulmonary coupling to assess adaptive servo-ventilation success in complex sleep apnea management. Sleep Breath 17(2):861–866

    Article  PubMed  Google Scholar 

  16. Guo D, Peng CK, Wu HL, Mietus JE, Liu Y, Sun RS, Thomas RJ (2011) ECG-derived cardiopulmonary analysis of pediatric sleep-disordered breathing. Sleep Med 12(4):384–389

    Article  PubMed  Google Scholar 

  17. Ibrahim LH, Jacono FJ, Patel SR, Thomas RJ, Larkin EK, Mietus JE, Peng CK, Goldberger AL, Redline S (2010) Heritability of abnormalities in cardiopulmonary coupling in sleep apnea: use of an electrocardiogram-based technique. Sleep 33(5):643–646

    PubMed Central  PubMed  Google Scholar 

  18. Koo BB, Wiggins R, Molina C (2012) REM rebound and CPAP compliance. Sleep Med 13(7):864–868

    Article  PubMed  Google Scholar 

  19. Brillante R, Cossa G, Liu PY, Laks L (2012) Rapid eye movement and slow-wave sleep rebound after one night of continuous positive airway pressure for obstructive sleep apnoea. Respirology 17(3):547–553

    Article  PubMed  Google Scholar 

  20. Harrington J, Schramm PJ, Davies CR, Lee-Chiong TL Jr (2013) An electrocardiogram-based analysis evaluating sleep quality in patients with obstructive sleep apnea. Sleep Breath. doi:10.1007/s11325-013-0804-9

    Google Scholar 

Download references

Acknowledgments

This research was partly supported by SNUBH Grant No. 02-2012-053.

Conflict of interest

None of the authors declare a conflict of interest in relation to this work.

Author information

Authors and Affiliations

  1. Department of Otorhinolaryngology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-dong, Bundang-gu, Seongnam, Gyeonggi-do, 464-707, South Korea

    Woo Hyun Lee, Jae-Cheul Ahn, Jaewoon We, Chae-Seo Rhee, Chul Hee Lee & Jeong-Whun Kim

  2. Department of Oral Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea

    Pil-Young Yun

  3. Department of Psychiatry, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea

    In-Young Yoon

Authors
  1. Woo Hyun Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jae-Cheul Ahn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaewoon We
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chae-Seo Rhee
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chul Hee Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pil-Young Yun
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. In-Young Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jeong-Whun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeong-Whun Kim.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lee, W.H., Ahn, JC., We, J. et al. Cardiopulmonary coupling analysis: changes before and after treatment with a mandibular advancement device. Sleep Breath 18, 891–896 (2014). https://doi.org/10.1007/s11325-014-0961-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11325-014-0961-5

Keywords

Search

Navigation