Udaya Seneviratne1, Kathiravelu Puvanendran. 1. National Neuroscience Institute, Singapore General Hospital Campus, Outram Road, Singapore, Singapore 169608. gnrswr@sgh.com.sg
Abstract
OBJECTIVES: To assess prevalence, severity, and predictive factors of excessive daytime sleepiness (EDS) in obstructive sleep apnea (OSA) in an Asian population. METHODS: A retrospective, cross-sectional study of data from patients diagnosed with OSA over a period of three years and having had overnight polysomnography (PSG) followed by daytime multiple sleep latency test (MSLT). Respiratory disturbance index (RDI) was used for diagnosis and assessment of severity. OSA was classified as mild (RDI 5-20), moderate (RDI 20-40), and severe (RDI>40). EDS was objectively assessed using MSLT. According to MSLT, patients were categorized into two groups; EDS (mean sleep latency:MSL<10) and no EDS (MSL>10). PSG, MSLT and demographic data were subjected to univariate and multivariate analyses to ascertain predictive factors of EDS. RESULTS: There were 195 patients comprising 89.4% males and 10.6% females. The severity of OSA was mild in 35.9%, moderate in 27.2%, and severe in 36.9%. EDS was demonstrated in 87.2%. Sleep onset REM periods were detected in the MSLT of 28.2% patients. Univariate analysis demonstrated age, RDI, sleep efficiency, total arousals, arousals with apnea, arousal index, number of desaturations, and severity of snoring as significant predictors of EDS. However, stepwise logistic regression analysis identified only sleep efficiency, total arousals, and severity of snoring as significant predictive factors. CONCLUSIONS: OSA causes EDS in the majority of patients. Severe snoring, higher sleep efficiency and increased total arousals in polysomnography seem to predict EDS.
OBJECTIVES: To assess prevalence, severity, and predictive factors of excessive daytime sleepiness (EDS) in obstructive sleep apnea (OSA) in an Asian population. METHODS: A retrospective, cross-sectional study of data from patients diagnosed with OSA over a period of three years and having had overnight polysomnography (PSG) followed by daytime multiple sleep latency test (MSLT). Respiratory disturbance index (RDI) was used for diagnosis and assessment of severity. OSA was classified as mild (RDI 5-20), moderate (RDI 20-40), and severe (RDI>40). EDS was objectively assessed using MSLT. According to MSLT, patients were categorized into two groups; EDS (mean sleep latency:MSL<10) and no EDS (MSL>10). PSG, MSLT and demographic data were subjected to univariate and multivariate analyses to ascertain predictive factors of EDS. RESULTS: There were 195 patients comprising 89.4% males and 10.6% females. The severity of OSA was mild in 35.9%, moderate in 27.2%, and severe in 36.9%. EDS was demonstrated in 87.2%. Sleep onset REM periods were detected in the MSLT of 28.2% patients. Univariate analysis demonstrated age, RDI, sleep efficiency, total arousals, arousals with apnea, arousal index, number of desaturations, and severity of snoring as significant predictors of EDS. However, stepwise logistic regression analysis identified only sleep efficiency, total arousals, and severity of snoring as significant predictive factors. CONCLUSIONS: OSA causes EDS in the majority of patients. Severe snoring, higher sleep efficiency and increased total arousals in polysomnography seem to predict EDS.
Authors: Maria Tejada; Carol Viele; Kord M Kober; Bruce A Cooper; Steven M Paul; Laura B Dunn; Marilyn J Hammer; Fay Wright; Yvette P Conley; Jon D Levine; Christine Miaskowski Journal: Sleep Date: 2019-10-09 Impact factor: 5.849
Authors: Thomas Roth; Jonathan R L Schwartz; Max Hirshkowitz; Milton K Erman; Jeffrey M Dayno; Sanjay Arora Journal: J Clin Sleep Med Date: 2007-10-15 Impact factor: 4.062