Association between sleep EEG characteristics and early neurological improvement in patients with acute ischemic stroke.

OBJECTIVE

This study was to explore the correlation between macroscopic and microscopic sleep architectures and early neurological improvement (ENI) in acute ischemic stroke by utilizing polysomnography (PSG) for sleep monitoring.

METHODS

Acute ischemic stroke patients were recruited to the Department of Neurology Inpatients of the Second Hospital affiliated with Soochow University from November 2015 and October 2021. PSG data were collected from all enrolled patients after admission, and sleep spindles and slow oscillations (SOs) were extracted and analyzed. Stroke patients were then divided into ENI and non-ENI groups based on the percentage difference between the National Institutes of Health Stroke Scale (NIHSS) score at admission and discharge, then clinical features, macro and micro sleep structure were compared between the two groups. Logistic regression analysis was used to explore the factors affecting the early improvement of neurological function in stroke patients.

RESULTS

In multivariable analysis, specific sleep architecture features were independent predictors of ENI. Higher sleep efficiency (p = 0.002) and stronger SO-spindle coupling (p = 0.011) were independently associated with increased odds of ENI, while higher spindle frequency (p = 0.023) and higher SO frequency (p = 0.012) were independently associated with reduced odds. A higher level of non-high density lipoprotein cholesterol (p = 0.009) and thalamic (p = 0.006) and other cortical and subcortical infarctions (p = 0.035) were also independently associated with lower ENI odds.

CONCLUSION

Macroscopical and microscopical sleep structures influence early recovery from stroke, and the precise coupling of SO and sleep spindle is independently associated with favorable neurological outcomes in stroke patients.