Subjective sleep assessment compared to polysomnography in mechanically ventilated critically ill ICU patients.

Sleep deprivation is expected in the intensive care unit (ICU) and is associated with delirium and increased mortality. Polysomnography (PSG) is the gold standard for sleep assessment, but practical issues limit the method. Hence, many ICUs worldwide use subjective sleep assessment (SSA) for sleep monitoring, but the agreement between SSA and PSG is unknown. The hypothesis was that the level of agreement between SSA and PSG was low and that total sleep time (TST) assessed with SSA would be overestimated compared to PSG in this existing cohort database. In this sub-analysis, 30 consecutive study participants underwent 15-h PSG recordings during two consecutive nights. The attending nurse performed an hourly subjective observer rating of sleep quantity during both nights, and the agreement between SSA and PSG was determined along with mean TST. Primary outcome: The level of agreement between SSA and PSG determined by Bland-Altman analysis. Secondary outcome: (1) The overall mean TST estimated by SSA compared to PSG in all study participants enrolled in the main study during both study nights, (2) TST for all study participants evaluated hourly during both study nights, (3) TST assessed with SSA compared to PSG in study participants sedated with dexmedetomidine during the second night and for study participants treated with placebo or non-sedation the first and second nights. The level of agreement between SSA and PSG was low. Mean TST estimated by SSA during the time interval 4.00 p.m. to 7.00 a.m. was 481 min (428;534, 95% CI) vs. PSG at 437 min (386;488, 95% CI) (p = .05). When sedated with dexmedetomidine, TST estimated using SSA was 650 min (571;729, 95% CI) versus PSG which was 588 min (531;645, 95% CI) (p = 0.56). For participants treated with placebo or non-sedation TST estimated with SSA was 397 min (343;450, 95% CI) versus PSG at 362 min (302;422, 95% CI) versus (p = 0.17). In mechanically ventilated critically ill ICU patients, the level of agreement between SSA and PSG was low, and there was a significant overestimation of mean TST. SSA should only be used under awareness that it is imprecise and overestimates TST.

Narcolepsy and pregnancy: a retrospective European evaluation of 249 pregnancies.

In a retrospective cohort study undertaken in 12 European countries, 249 female narcoleptic patients with cataplexy (n = 216) and without cataplexy (n = 33) completed a self-administrated questionnaire regarding pregnancy and childbirth. The cohort was divided further into patients whose symptoms of narcolepsy started before or during pregnancy (308 pregnancies) and those in whom the first symptoms of narcolepsy appeared after delivery (106 pregnancies). Patients with narcolepsy during pregnancy were older during their first pregnancy (P < 0.001) and had a higher body mass index (BMI) prior to pregnancy (P < 0.01). Weight gain during pregnancy was higher in narcoleptic patients with cataplexy (P < 0.01). More patients with narcolepsy-cataplexy during pregnancy had impaired glucose metabolism and anaemia. Three patients experienced cataplexy during delivery. The rate of caesarean sections was higher in the narcolepsy-cataplexy group compared to the narcolepsy group (P < 0.05). The mean birth weight and gestational age of neonates were within the normal range and did not differ across groups. Neonatal care was affected adversely by symptoms of narcolepsy in 60.1% of those with narcolepsy during pregnancy. This study reports more obstetric complications in patients with narcolepsy-cataplexy during pregnancy; however, these were not severe. This group also had a higher BMI and higher incidence of impaired glucose metabolism during pregnancy. Caesarian section was conducted more frequently in narcolepsy-cataplexy patients, despite cataplexy being a rare event during delivery. Furthermore, symptoms of narcolepsy may render care of the infant more difficult.

Two nights of home polysomnography in healthy 7-14-year-old children - Feasibility and intraindividual variability.

OBJECTIVE: Attended polysomnography (PSG) is the gold standard for childhood sleep evaluation. There is, however, only limited information regarding repeated ambulatory PSG in children. We aimed to test whether in hospital attached level 2 home PSG is feasible and reproducible in healthy children. METHODS: We recruited healthy children aged 7-14 years to undergo two nights of full level 2 PSG. The PSG equipment was attached at the hospital on the day of the sleep test and all recordings were performed at home. Subjective sleep quality, nocturnal urine production, sleep time and number of awakenings were documented for a week in connection to the first PSG night. RESULTS: Thirty-three children were recruited of whom 32 children (aged 11 ± 2.1 years) underwent two nights of PSG. All 64 PSGs were technically adequate for sleep evaluation. We found mean sleep efficiency of 94% and mean total sleep time of 8.4 h. Sleep stages distribution with 5.9% N1, 46.8% N2, 24.3% N3 and 22.8% REM sleep. We found poorer subjective sleep quality, more self-reported awakenings, and shorter total sleep time on nights with PSG compared to nights without PSG with no differences between PSG study nights. No differences in nocturnal urine production were found between nights with and without PSG. The comparison of PSG variables between the two PSG nights revealed no first night effect. CONCLUSIONS: Type 2 PSG recording is feasible for sleep evaluation in children 7-14 years of age producing good data quality. We found no first night effect on PSG variables. www. CLINICALTRIALS: gov Registration number: NCT03477812.

Validation of the newly developed Sleep Screening Questionnaire Children and Adolescents (SSQ-CA) with objective sleep measures.

OBJECTIVES: Objectively validated pediatric sleep questionnaires covering a broader age range and different sleep disturbances are lacking, therefore we developed the Sleep Screening Questionnaire Children and Adolescents (SSQ-CA) and compared it with objective sleep parameters. METHODS: This child-reported questionnaire was developed by a multidisciplinary panel and face validated. In a cross-sectional prospective design, participants aged 6-17, answered the questionnaire twice with 21-28 days in between, wore actigraphy (AG) and kept a sleep diary for seven nights and home-polysomnography (PSG) for one of these nights. Exploratory factor analyses (EFA), reliability and validity assessments were performed. RESULTS: Of the 139 participants, 128 (F:47.7%, AG: n = 128, PSG: n = 59), were included in the analyses. Mean age: 11.3 years (SD: 2.9). EFA revealed 11 factors and 40 items loading above r = 0.4. Subscale internal consistency: 0.54-0.92. Subscale test-retest reliability: r = 0.71-0.87. Total sleep time (TST) from SSQ-CA on weekdays correlated with PSG (r = 0.48, p = 0.001) and with AG (r = 0.75, p < 0.001). The subscale total score for "Sleep duration and latency" correlated with TST from AG (r = -0.19, p = 0.03) and sleep latency (r = 0.31, p < 0.001), but not for PSG variables. The subscale "Awakenings" showed no correlation with objective measures whereas "Circadian rhythm" correlated to AG-derived mid-sleep time (r = 0.34, p < 0.001). CONCLUSIONS: The SSQ-CA shows adequate reliability for the 6-17-year-olds and acceptable criterion validity for two subscales. It appears to be a useful tool for screening for sleep disturbances in combination with objective tools as the subjective and objective parameters seem to uncover different aspects of sleep.

Novel method for evaluation of eye movements in patients with narcolepsy.

BACKGROUND: Narcolepsy causes abnormalities in the control of wake-sleep, non-rapid-eye-movement (non-REM) sleep and REM sleep, which includes specific eye movements (EMs). In this study, we aim to evaluate EM characteristics in narcolepsy as compared to controls using an automated detector. METHODS: We developed a data-driven method to detect EMs during sleep based on two EOG signals recorded as part of a polysomnography (PSG). The method was optimized using the manually scored hypnograms from 36 control subjects. The detector was applied on a clinical sample with subjects suspected for central hypersomnias. Based on PSG, multiple sleep latency test and cerebrospinal fluid hypocretin-1 measures, they were divided into clinical controls (N = 20), narcolepsy type 2 (NT2, N = 19), and narcolepsy type 1 (NT1, N = 28). We investigated the distribution of EMs across sleep stages and cycles. RESULTS: NT1 patients had significantly less EMs during wake, N1, and N2 sleep and more EMs during REM sleep compared to clinical controls, and significantly less EMs during wake and N1 sleep compared to NT2 patients. Furthermore, NT1 patients showed less EMs during NREM sleep in the first sleep cycle and more EMs during NREM sleep in the second sleep cycle compared to clinical controls and NT2 patients. CONCLUSIONS: NT1 patients show an altered distribution of EMs across sleep stages and cycles compared to NT2 patients and clinical controls, suggesting that EMs are directly or indirectly controlled by the hypocretinergic system. A data-driven EM detector may contribute to the evaluation of narcolepsy and other disorders involving the control of EMs.

Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson's disease.

OBJECTIVE: To determine whether sleep spindles (SS) are potentially a biomarker for Parkinson's disease (PD). METHODS: Fifteen PD patients with REM sleep behavior disorder (PD+RBD), 15 PD patients without RBD (PD-RBD), 15 idiopathic RBD (iRBD) patients and 15 age-matched controls underwent polysomnography (PSG). SS were scored in an extract of data from control subjects. An automatic SS detector using a Matching Pursuit (MP) algorithm and a Support Vector Machine (SVM) was developed and applied to the PSG recordings. The SS densities in N1, N2, N3, all NREM combined and REM sleep were obtained and evaluated across the groups. RESULTS: The SS detector achieved a sensitivity of 84.7% and a specificity of 84.5%. At a significance level of α=1%, the iRBD and PD+RBD patients had a significantly lower SS density than the control group in N2, N3 and all NREM stages combined. At a significance level of α=5%, PD-RBD had a significantly lower SS density in N2 and all NREM stages combined. CONCLUSIONS: The lower SS density suggests involvement in pre-thalamic fibers involved in SS generation. SS density is a potential early PD biomarker. SIGNIFICANCE: It is likely that an automatic SS detector could be a supportive diagnostic tool in the evaluation of iRBD and PD patients.

Validation of a novel automatic sleep spindle detector with high performance during sleep in middle aged subjects.

Many of the automatic sleep spindle detectors currently used to analyze sleep EEG are either validated on young subjects or not validated thoroughly. The purpose of this study is to develop and validate a fast and reliable sleep spindle detector with high performance in middle aged subjects. An automatic sleep spindle detector using a bandpass filtering approach and a time varying threshold was developed. The validation was done on sleep epochs from EEG recordings with manually scored sleep spindles from 13 healthy subjects with a mean age of 57.9 ± 9.7 years. The sleep spindle detector reached a mean sensitivity of 84.6 % and a mean specificity of 95.3 %. The sleep spindle detector can be used to obtain measures of spindle count and density together with quantitative measures such as the mean spindle frequency, mean spindle amplitude, and mean spindle duration.

Automatic sleep scoring in normals and in individuals with neurodegenerative disorders according to new international sleep scoring criteria.

The aim of this study was to develop a fully automatic sleep scoring algorithm on the basis of a reproduction of new international sleep scoring criteria from the American Academy of Sleep Medicine. A biomedical signal processing algorithm was developed, allowing for automatic sleep depth quantification of routine polysomnographic recordings through feature extraction, supervised probabilistic Bayesian classification, and heuristic rule-based smoothing. The performance of the algorithm was tested using 28 manually classified day-night polysomnograms from 18 normal subjects and 10 patients with Parkinson disease or multiple system atrophy. This led to quantification of automatic versus manual epoch-by-epoch agreement rates for both normals and abnormals. Resulting average agreement rates were 87.7% (Cohen's Kappa: 0.79) and 68.2% (Cohen's Kappa: 0.26) in the normal and abnormal group, respectively. Based on an observed reliability of the manual scorer of 92.5% (Cohen's Kappa: 0.87) in the normal group and 85.3% (Cohen's Kappa: 0.73) in the abnormal group, this study concluded that although the developed algorithm was capable of scoring normal sleep with an accuracy around the manual interscorer reliability, it failed in accurately scoring abnormal sleep as encountered for the Parkinson disease/multiple system atrophy patients.