Characteristics of quantitative arousal intensity and its association with cognitive function and sleepiness in sleep apnea patients, 2025, Gao et al.

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Characteristics of quantitative arousal intensity and its association with cognitive function and sleepiness in sleep apnea patients
Xiang Gao, Yunhan Shi, Rongcui Sui, Shenglong Xu, Mengyu Xu, Jianhong Liao, Yanru Li, Demin Ha

Study objectives:
Obstructive sleep apnea (OSA) disrupts sleep, leading to cognitive impairment and sleepiness, but risk stratification remains unclear. We developed an EEG-based arousal marker to quantify sleep fragmentation and assessed its associations with neurocognitive function and daytime sleepiness.

Methods: Arousal intensity was derived from EEG signals in 1070 APPLES (Apnea Positive Pressure Long-term Efficacy Study) study participants. We analyzed its associations with PSG parameters, cognitive function (Wechsler Abbreviated Scale of Intelligence, WASI), and sleepiness (Multiple Sleep Latency Test, MSLT; Epworth Sleepiness Scale, ESS). Stepwise regression identified predictors of cognitive function. Sensitivity analysis examined arousal intensity's link to 6-month CPAP outcomes (N = 419).

Results: Among OSA individuals, the AHI ranged from 10 to 130.7/h, the average arousal index was 26.75/h and a total of 235,835 arousal events were extracted. The arousal intensity was significantly greater for hypoxia-associated and desaturation-related events compared to hypopnea-associated or spontaneous arousals (p<0.001). It correlated negatively with age, PSG measures, and cognitive function. Adjusted models showed Delta-band arousal intensity negatively predicted WASI-Full scores (β = -3.24, p = 0.019). Higher Gamma-band intensity was associated with both greater subjective sleepiness (ESS: β = 0.03, p = 0.028) and increased CPAP-induced MSLT improvement (β = 0.12, p = 0.020).

Conclusions: Arousal intensity is a novel EEG marker for cognitive impairment and sleepiness in OSA, with potential clinical utility in predicting CPAP response. This EEG-based marker could be integrated into standard sleep analysis platforms to identify OSA patients at risk of cognitive impairment, enabling early intervention.
 
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