Neurology · 2018
Sleep-disordered breathing among patients admitted for inpatient video-EEG monitoring.
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Sivathamboo Shobi, Farrand Sarah, Chen Zhibin, White Elise J, Pattichis Andrew Andreas, Hollis Callum, Carino John, Roberts Caitlin J, Minogue Thomas, Jones Nigel C, Yerra Raju, French Christopher, Perucca Piero, Kwan Patrick, Velakoulis Dennis, O'Brien Terence J, Goldin Jeremy
Аннотация
OBJECTIVE: To examine the prevalence and risk factors of sleep-disordered breathing (SDB) in individuals with epilepsy and psychogenic nonepileptic seizures (PNES).
METHODS: We conducted a cross-sectional study of consecutive patients admitted for inpatient video-EEG monitoring at The Royal Melbourne Hospital, Australia, between December 1, 2011, and July 31, 2017. Participants underwent routine clinical investigations during their monitoring period including polysomnography, neurocognitive testing, and screening instruments of daytime somnolence, sleep quality, and quality of life.
RESULTS: Our study population consisted of 370 participants who received a diagnosis of epilepsy (n = 255), PNES (n = 93), or both disorders (n = 22). Moderate to severe SDB (defined by an apnea-hypopnea index ≥15) was observed in 26.5% (98/370) of individuals, and did not differ across subgroups: epilepsy 26.3% (67/255), PNES 29.0% (27/93), or both disorders 18.2% (4/22; p = 0.610). Following adjustment for confounders, pathologic daytime sleepiness predicted moderate to severe SDB in epilepsy (odds ratio [OR] 10.35, 95% confidence interval [CI] 2.09-51.39; p = 0.004). In multivariable analysis, independent predictors for moderate to severe SDB in epilepsy were older age (OR 1.07, 95% CI 1.04-1.10; p < 0.001) and higher body mass index (OR 1.06, 95% CI 1.01-1.11; p = 0.029), and in PNES older age (OR 1.10, 95% CI 1.03-1.16; p = 0.002).
CONCLUSION: Polysomnography during inpatient video-EEG monitoring identified a substantial number of patients with undiagnosed SDB. This was remarkable in the subgroup with PNES, who were often female and obese. Identification of risk factors may improve management of SDB in these populations. The association with pathologic daytime sleepiness suggests that SDB may be an important contributor to these common and disabling symptoms in patients with epilepsy.
METHODS: We conducted a cross-sectional study of consecutive patients admitted for inpatient video-EEG monitoring at The Royal Melbourne Hospital, Australia, between December 1, 2011, and July 31, 2017. Participants underwent routine clinical investigations during their monitoring period including polysomnography, neurocognitive testing, and screening instruments of daytime somnolence, sleep quality, and quality of life.
RESULTS: Our study population consisted of 370 participants who received a diagnosis of epilepsy (n = 255), PNES (n = 93), or both disorders (n = 22). Moderate to severe SDB (defined by an apnea-hypopnea index ≥15) was observed in 26.5% (98/370) of individuals, and did not differ across subgroups: epilepsy 26.3% (67/255), PNES 29.0% (27/93), or both disorders 18.2% (4/22; p = 0.610). Following adjustment for confounders, pathologic daytime sleepiness predicted moderate to severe SDB in epilepsy (odds ratio [OR] 10.35, 95% confidence interval [CI] 2.09-51.39; p = 0.004). In multivariable analysis, independent predictors for moderate to severe SDB in epilepsy were older age (OR 1.07, 95% CI 1.04-1.10; p < 0.001) and higher body mass index (OR 1.06, 95% CI 1.01-1.11; p = 0.029), and in PNES older age (OR 1.10, 95% CI 1.03-1.16; p = 0.002).
CONCLUSION: Polysomnography during inpatient video-EEG monitoring identified a substantial number of patients with undiagnosed SDB. This was remarkable in the subgroup with PNES, who were often female and obese. Identification of risk factors may improve management of SDB in these populations. The association with pathologic daytime sleepiness suggests that SDB may be an important contributor to these common and disabling symptoms in patients with epilepsy.