Prevalence and Related Parameters of Daytime Sleepiness in Patients with Habitual Snoring

BACKGROUND: Excessive daytime sleepiness (EDS) is a common symptom in patients with habitual snoring, including obstructive sleep apnea (OSA). However, there had been no studies for the prevalence and related factors of EDS in patients with habitual snoring in Korea. So we studied the prevalence and related factors of EDS in patients with habitual snoring. METHODS: Sixty two patients with habitual snoring were selected from our sleep center from February 2004 to January 2007. All patients were given an overnight polysomnography and then took the multiple sleep latency tests the following day. They were classified into two groups: EDS (mean sleep latency, MSL or =10 minutes). We studied the prevalence of EDS in patients with habitual snoring and compared two groups about the demographic data and polysomnographic characteristics. RESULTS: Most (72.6%) patients with habitual snoring demonstrated EDS. There were significant different parameters between the EDS group and the no EDS group, such as total sleep time, percent of slow wave sleep, snoring index, arousal index, and number of desaturation. Among these, the logistic regression analysis identified total sleep time as a significant predictive factor for daytime sleepiness. MSL correlated significantly with the percent of slow wave sleep and number of desaturation. CONCLUSIONS: Our results showed the high prevalence of EDS in patients with habitual snoring in Korea. Long total sleep time in polysomnography seems to predict EDS.

A Case of Diabetic Uremic Encephalopathy with Symmetric MR signal Changes in the Basal Ganglia

Acute changes of the bilateral basal ganglia shown in the brain MRI a diabetic uremic patient have been rarely reported. We report a 52-year-old diabetic uremic patient who had neurological disturbances. At admission, axial diffusion-weighted images and T2-weighted images showed high signal intensities in the bilateral basal ganglia, and axial T1-weighted images visualized low signal intensities in same area. The underlying mechanism may be associated with metabolic as well as vascular factors.