0452 Intra-individual Stability of Quantitative EEG as a Biomarker in Obstructive Sleep Apnea
Abstract Introduction Clinical sleep parameters are poor predictors of sleepiness and performance decrements in obstructive sleep apnea (OSA). There is some evidence that electroencephalography (EEG) microstructure measured during sleep and wakefulness may be a more promising objective biomarker of...
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Veröffentlicht in: | Sleep (New York, N.Y.) N.Y.), 2018-04, Vol.41 (suppl_1), p.A171-A171 |
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Zusammenfassung: | Abstract
Introduction
Clinical sleep parameters are poor predictors of sleepiness and performance decrements in obstructive sleep apnea (OSA). There is some evidence that electroencephalography (EEG) microstructure measured during sleep and wakefulness may be a more promising objective biomarker of sleepiness and neurobehavioural function. We aimed to investigate the intra-individual stability of EEG slow wave (delta power) and spindle frequency (sigma power) activity during non-rapid eye movement (NREM) sleep in OSA patients.
Methods
We recorded sleep EEG during overnight polysomnography on two separate occasions from 61 OSA patients. EEG recorded at the C3-M2 derivation was quantitatively analysed using power spectral analysis following artefact removal. Relative delta (0.5–4.5 Hz) and sigma (12-15Hz) power in NREM sleep were calculated. Intra-class Correlation Coefficients (ICC) and Bland-Altman plots were used to assess agreement between nights.
Results
ICCs demonstrated good-to-excellent agreement in the delta and sigma frequencies between nights (0.843 and 0.890 respectively). Bland-Altman analysis of delta power showed a mean difference close to zero (-0.35, 95% limits -9.4,8.6) and no systematic difference as delta power increased. The stability of sigma power appeared to reduce as sigma increased, but the mean difference was close to zero (0.05, 95% limits -1.6,1.8).
Conclusion
This work has demonstrated the stability of EEG activity in NREM sleep in slow wave and spindle frequency activity ranges within individuals with OSA. This suggests data from only one night of sleep may be useful to provide a trait-like biomarker for predicting vulnerability to daytime impairment observed in OSA.
Support (If Any)
This study was funded by the Australian National Health and Medical Research Council (Project Grant #1004528, NeuroSleep Centre of Research Excellence #1060992 Fellowships and a Sydney Medical School Summer Scholarship). |
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ISSN: | 0161-8105 1550-9109 |
DOI: | 10.1093/sleep/zsy061.451 |