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Manual vs. automated analysis of polysomnographic recordings in patients with chronic obstructive pulmonary disease

Sleep and Breathing volume 17, pages 533–539 (2013)Cite this article

Abstract

Purpose

The sleep quality, as assessed by polysomnography (PSG), of patients with chronic obstructive pulmonary disease (COPD) can be severely disturbed. The manual analysis of PSGs is time-consuming, and computer systems have been developed to automatically analyze PSGs. Studies on the reliability of automated analyses in healthy subjects show varying results, and the purpose of this study was to assess whether automated analysis of PSG by one certain automatic system in patients with COPD provide accurate outcomes when compared to manual analysis.

Methods

In a retrospective study, the full-night polysomnographic recordings of patients with and without COPD were analyzed automatically by Matrix Sleep Analysis software and manually. The outcomes of manual and automated analyses in both groups were compared using Bland–Altman plots and Students’ paired t tests.

Results

Fifty PSGs from patients with COPD and 57 PSGs from patients without COPD were included. In both study groups, agreement between manual and automated analysis was poor in nearly all sleep and respiratory parameters, like total sleep time, sleep efficiency, sleep latency, amount of rapid eye movement sleep and other sleep stages, number of arousals, apnea–hypopnea index, and desaturation index.

Conclusion

Automated analysis of PSGs by the studied automated system in patients with COPD has poor agreement with manual analysis when looking at sleep and respiratory parameters and should, therefore, not replace the manual analysis of PSG recordings in patients with COPD.

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Fig. 1

Abbreviations

AASM:

American Academy of Sleep Medicine

AHI:

Apnea–hypopnea index

COPD:

Chronic obstructive pulmonary disease

EEG:

Electroencephalography

EMG:

Electromyography

EOG:

Electrooculography

FEV1 :

Forced expiratory volume in 1 s

nREM:

Non-REM sleep

OSAHS:

Obstructive sleep apnea–hypopnea syndrome

PLM:

Periodic leg movements

PSG:

Polysomnography

REM:

Rapid eye movement

SE:

Sleep efficiency

SOL:

Sleep-onset latency

SpO2 :

Oxygen saturation

TST:

Total sleep time

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Acknowledgements

This study was supported with an unrestricted grant from GlaxoSmithKline. We would like to thank all coworkers at the Clinical Neurophysiology Department and Sleep Laboratory at the Rijnstate Hospital and Velp Hospital for their assistance in the study logistics and data collection, Mrs. Lian Roovers for her statistical assistance, and GlaxoSmithKline for the financial support. The funding agency did not have any involvement in the study design, data collection, data analysis, interpretation of data, manuscript preparation, and/or in the decision to submit the paper for publication.

Conflict of interest

The authors declare that they have no conflicts of interest.

Author information

Affiliations

  1. Department of Pulmonology, Rijnstate Hospital, P.O. Box 9555, 6800 TA, Arnhem, The Netherlands

    Gerben Stege, Petra J. E. Vos, Marjo J. T. van de Ven & Frank J. J. van den Elshout

  2. Department of Pulmonology, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands

    P. N. Richard Dekhuijzen & Yvonne F. Heijdra

  3. Department of Neurology, St. Antonius Hospital, P.O. Box 2500, 3430 EM, Nieuwegein, The Netherlands

    Pieter H. E. Hilkens

Authors
  1. Gerben Stege
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  2. Petra J. E. Vos
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  3. P. N. Richard Dekhuijzen
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  4. Pieter H. E. Hilkens
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  5. Marjo J. T. van de Ven
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  6. Yvonne F. Heijdra
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  7. Frank J. J. van den Elshout
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Corresponding author

Correspondence to Gerben Stege.

Additional information

This study was performed at the Rijnstate Hospital, Arnhem, The Netherlands.

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Stege, G., Vos, P.J.E., Dekhuijzen, P.N.R. et al. Manual vs. automated analysis of polysomnographic recordings in patients with chronic obstructive pulmonary disease. Sleep Breath 17, 533–539 (2013). https://doi.org/10.1007/s11325-012-0714-2

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  • DOI: https://doi.org/10.1007/s11325-012-0714-2

Keywords

  • Computerized scoring
  • Polysomnography
  • Chronic obstructive pulmonary disease
  • Sleep stage scoring