The challenges in scoring hypopneas in children: is pulse wave amplitude drop the answer?

BackgroundIdentifying electroencephalogram (EEG) cortical arousals are crucial in scoring hypopneas and respiratory efforts related arousals (RERAs) during a polysomnogram. As children have high arousal threshold, many of the flow limited breaths or hypopneas may not be associated with visual EEG arousals, hence this may lead to potential underestimation of the degree of sleep disordered breathing. Pulse wave amplitude (PWA) is a signal obtained from finger photoplethysmography which correlates directly to finger blood flow. The drop in PWA has been shown to be a sensitive marker for subcortical/autonomic and cortical arousals. Our aim was to use the drop in PWA as a surrogate for arousals to guide scoring of respiratory events in pediatric patients.MethodsTen polysomnograms for patients between the ages of 5–15 years who had obstructive apnea-hypopnea indices between 1 and 5 events/hour were identified. Patients with syndromes were excluded. A drop in PWA signal of at least 30% that lasted for 3 s was needed to identify subcortical/autonomic arousals. Arousals were rescored based on this criteria and subsequently respiratory events were rescored. Paired t-tests were employed to compare PSG indices scored with or without PWA incorporation.ResultsThe sample of 10 children included 2 females, and the average age was 9.8 ± 3.1 years. Overall, polysomnography revealed an average total sleep time of 464.1 ± 25 min, sleep efficiency of 92% +/−4.2, sleep latency of 19.6 ± 17.0 min, rapid eye movement (REM) latency 143 ± 66 min, N1 3.9% +/−2.0, N2 50.3% +/−12.0, N3 28.2% +/−9.1, REM 16.7% +/−4.0, and wakefulness after sleep onset (WASO) 18.1 ± 7.5 min. Including arousals from PWA changes, respiratory indices significantly increased including total AHI (2.3 ± 0.7 vs 5.7 ± 2.1, p < 0.001), obstructive AHI (1.45 ± 0.7 vs 4.8 ± 1.8, p < 0.001), and RDI (2.36 ± 0.7 vs 7.6 ± 2.0, p < 0.001). Likewise, total arousal index was significantly higher (8.7 ± 2.3 vs 29.4 ± 6.5, p < 0.001).ConclusionsThe drop in pulse wave amplitude signal is a useful marker to guide scoring arousals that are not otherwise easily identified in pediatric polysomnography and subsequently helped in scoring respiratory events that otherwise would not be scored. Further studies are needed to delineate if such methodology would affect clinical outcome.     

Sleep physiology in recovery from burnout

This study aimed to investigate the role of sleep physiology in recovery from burnout, in particular the relation between sleep and changes in fatigue and whether those changes would be related to return to work.23 white-collar workers on long-term sick leave (>3 months) due to a burnout related diagnosis and 16 healthy controls were subjected to polysomnographic recordings at baseline and after 6-12 months’ rehabilitation. Occupational status, subjective sleep quality, fatigue, anxiety and depression were assessed. Recovery from burnout was accompanied by improved sleep continuity. Significant interaction effects were seen for number of arousals, sleep fragmentation, sleep latency, sleep efficiency and time of rising. The burnout group improved significantly on all symptom variables although the post-treatment levels did not reach the levels of the controls. Recovery from fatigue was related to a reduction of the arousal from sleep and was the best predictor of return to work.     

The roles of TNF-α and the soluble TNF receptor I on sleep architecture in OSA

Objective  Patients with obstructive sleep apnea (OSA) have been described to have increased levels of inflammatory cytokines (particularly TNF-α) and have severely disturbed sleep architecture. Serum inflammatory markers, even in normal individuals, have been associated with abnormal sleep architecture. Not much is known about the role the TNF receptor plays in the inflammation of OSA nor if it is associated with changes in sleep architecture or arousals during the night. We hypothesized that the TNF receptor might play an important role in the inflammation as well as sleep architecture changes in patients with OSA. Design  Thirty-six patients with diagnosed (AHI > 15) but untreated OSA were enrolled in this study. Baseline polysomnograms as well as TNF-α and soluble TNF receptor I (sTNF-RI) serum levels were obtained on all patients. We evaluated the association between serum levels of TNF-α and sTNF-RI with various polysomongraphic characteristics, including sleep stages and EEG arousals. Results  sTNF-RI levels were significantly correlated with snore arousals (r value 0.449, p value 0.009), spontaneous movement arousals (r value 0.378, p value 0.025), and periodic limb movement arousals (r value 0.460, p value 0.008). No statistically significant correlations were observed with TNF-α to any polysomnographic variables. To control for statistical significance with multiple comparisons, a MANOVA was performed with TNF-α and sTNF-RI as dependent variables and sleep architecture measures and arousals as independent variables. The model for sTNF-RI was statistically significant (F value 2.604, p value 0.03), whereas the model for TNF-α was not, suggesting sleep quality significantly affects sTNF-RI. Hierarchal linear regression analysis demonstrated that sTNF-RI was independently associated with spontaneous movement arousal index scores after controlling for age, body mass index, and sleep apnea severity. Conclusions  These findings suggest that sTNF-RI is associated with arousals during sleep, but not with other measures in patients with OSA.     

Muscle Artifact Removal from Human Sleep EEG by Using Independent Component Analysis

Muscle artifacts are typically associated with sleep arousals and awakenings in normal and pathological sleep, contaminating EEG recordings and distorting quantitative EEG results. Most EEG correction techniques focus on ocular artifacts but little research has been done on removing muscle activity from sleep EEG recordings. The present study was aimed at assessing the performance of four independent component analysis (ICA) algorithms (AMUSE, SOBI, Infomax, and JADE) to separate myogenic activity from EEG during sleep, in order to determine the optimal method. AMUSE, Infomax, and SOBI performed significantly better than JADE at eliminating muscle artifacts over temporal regions, but AMUSE was independent of the signal-to-noise ratio over non-temporal regions and markedly faster than the remaining algorithms. AMUSE was further successful at separating muscle artifacts from spontaneous EEG arousals when applied on a real case during different sleep stages. The low computational cost of AMUSE, and its excellent performance with EEG arousals from different sleep stages supports this ICA algorithm as a valid choice to minimize the influence of muscle artifacts on human sleep EEG recordings.     

The Arousal Disorders Questionnaire: a new and effective screening tool for confusional arousals,Sleepwalking and Sleep Terrors in epilepsy and sleep disorders units

BackgroundArousal Disorders (DoA) include Confusional Arousals, Sleepwalking and Sleep Terrors. DoA diagnosis is mainly clinical but no validated questionnaires exist for DoA screening according to the criteria of the International Classification of Sleep Disorders, Third Edition. Recently our group proposed the Arousal Disorders Questionnaire (ADQ) as a new diagnostic tool for DoA diagnosis. The objective of this study was to evaluate the diagnostic accuracy of the ADQ in a sleep and epilepsy center.MethodsOne interviewer blinded to clinical and video-polysomnographic (VPSG) data administered the ADQ to 150 patients consecutively admitted to our Sleep and Epilepsy Centers for a follow-up visit. The final diagnosis, according to VPSG recordings of at least one major episode, classified patients either with DoA (DoA group) or with other sleep-related motor behaviors confounding for DoA (nDoA group).Results47 patients (31%) composed the DoA group; 56 patients with REM sleep behavior disorder, 39 with sleep-hypermotor epilepsy, six with night eating syndrome, and two with drug-induced DoA composed the nDoA group. The ADQ had a sensitivity of 72% (95% CI: 60–82) and a specificity of 96% (95% CI: 89–98) for DoA diagnosis; excluding the items regarding consciousness and episode recall, sensitivity was 83% (95% CI: 71–90) and specificity 93% (95% CI: 86–97).ConclusionsThe ADQ showed good accuracy in screening patients with DoA in a sleep and epilepsy center setting. Diagnostic criteria related to cognition and episode recall reduced ADQ sensitivity, therefore a better definition of these criteria is required, especially in adults.     

Cyclic alternating pattern (CAP) alterations in narcolepsy

BACKGROUND AND PURPOSE: Narcolepsy is a sleep disorder with clinical symptoms attributed to a reduced activation of the arousal system. Cyclic alternating pattern (CAP) is the expression of rhythmic arousability during non-rapid eye movement (NREM) sleep. CAP parameters, arousals and conventional sleep measures were studied in narcoleptic patients with cataplexy. PATIENTS AND METHODS: Data were collected from all-night polysomnographic (PSG) recordings and the multiple sleep latency test (MSLT) on the intervening day of 25 drug-naive patients (10 males and 15 females; mean age: 34+/-16 years) after adaptation and exclusion of other sleep disorders. A group of 25 age- and gender-matched normal sleepers were selected as controls. Each PSG recording was subdivided into sleep cycles. Analysis of CAP included classification of A phases into subtypes A1, A2, and A3. RESULTS: There was an increase in sleep period time mainly due to an increased wake time after sleep onset. REM latency was sharply reduced. The percentage of NREM sleep was slightly reduced and the balance between light sleep (S1+S2) and deep sleep (S3+S4) showed a curtailment of the former, while deep sleep was slightly increased. Excluding sleep cycles with sleep onset REM periods (SOREMPs), the duration of ordered sleep cycles was not different between narcoleptics and controls. The two groups showed similar values of arousal index, while CAP time, CAP rate, number of CAP cycles and of phase A subtypes (in particular subtypes A1) were significantly reduced in narcoleptic patients. CONCLUSIONS: The reduced periods of CAP in narcoleptic NREM sleep could be the electroencephalographic (EEG) expression of a generally reduced arousability or an increased strength of sleep-promoting forces in the balance between sleep and arousal systems. This can explain some of the clinical correlates of the disorder, i.e. excessive sleepiness, short sleep latency and impaired attentive performances, even without any sign of arousal-induced sleep fragmentation.     

Behavioral Control of Respiration in Sleep

Three experiments are presented involving behavioral control of sleeping respiration during all-night sleep recording. Probability and latency of the breathing response to an auditory signal revealed that control over sleeping respiration was obtained in all sleep stages and was maintained over several nights. This control was especially marked when failure to respond was punished (contingency procedure) by increasing the intensity of the signal (Experiments 2 and 3). Few awakenings occurred to the signal but signs of brief arousal (bursts of alpha activity, increases in EMG activity, EEG “speeding”) often accompanied the behavioral response. Overall sleep patterns were only minimally disrupted by the procedure. Demonstrating behavioral control over sleeping respiration may be a promising step toward the development of behavioral therapies for certain sleep apnea disorders and hypoventilation syndromes.     

Unchanged heart rate-respiratory frequency ratio in preterm infants during spontaneous arousals

Aim: To find out whether a correlation of heart rate (HR) and respiratory frequency (RF) defined as HR-RF-ratio (HRR) may be helpful to identify arousals in term and preterm infants.
Methods: Polygraphic recordings were performed in 25 term infants (gestational age 40.1 ± 1.1 weeks) and 25 preterm infants (gestational age 31.1 ± 1.3 weeks) during undisturbed daytime sleep. Arousals were scored as suggested by the 'International Paediatric Work Group on Arousals' and divided into cortical arousals and subcortical arousals. HRR was defined as HR over RF. Arousals were compared to a 30-sec period preceding an arousals.
Results: Two hundred arousals were scored (100 cortical arousals and 100 subcortical arousals). HRR increased during arousals in term infants (p < 0.001). This was true for cortical arousals (p < 0.001) and subcortical arousals (p < 0.05) of term infants. In contrast, in preterm infants HRR remained unchanged during cortical arousals and subcortical arousals.
Conclusion: An increase of HRR during arousals is a simple parameter to identify arousals in term infants, but not in preterm infants suggesting that an unchanged HRR might be an indicator of an immature arousal response.     

Sleep-Dependent Improvement in Visuomotor Learning: A Causal Role for Slow Waves

Study Objectives:

Sleep after learning often benefits memory consolidation, but the underlying mechanisms remain unclear. In previous studies, we found that learning a visuomotor task is followed by an increase in sleep slow wave activity (SWA, the electroencephalographic [EEG] power density between 0.5 and 4.5 Hz during non-rapid eye movement sleep) over the right parietal cortex. The SWA increase correlates with the postsleep improvement in visuomotor performance, suggesting that SWA may be causally responsible for the consolidation of visuomotor learning. Here, we tested this hypothesis by studying the effects of slow wave deprivation (SWD).

Design:

After learning the task, subjects went to sleep, and acoustic stimuli were timed either to suppress slow waves (SWD) or to interfere as little as possible with spontaneous slow waves (control acoustic stimulation, CAS).

Setting:

Sound-attenuated research room.

Participants:

Healthy subjects (mean age 24.6 ± 1.0 years; n = 9 for EEG analysis, n = 12 for behavior analysis; 3 women)

Measurements and Results:

Sleep time and efficiency were not affected, whereas SWA and the number of slow waves decreased in SWD relative to CAS. Relative to the night before, visuomotor performance significantly improved in the CAS condition (+5.93% ± 0.88%) but not in the SWD condition (−0.77% ± 1.16%), and the direct CAS vs SWD comparison showed a significant difference (P = 0.0007, n = 12, paired t test). Changes in visuomotor performance after SWD were correlated with SWA changes over right parietal cortex but not with the number of arousals identified using clinically established criteria, nor with any sign of “EEG lightening” identified using a novel automatic method based on event-related spectral perturbation analysis.

Conclusion:

These results support a causal role for sleep slow waves in sleep-dependent improvement of visuomotor performance.

Citation:

Landsness EC; Crupi D; Hulse BK; Peterson MJ; Huber R; Ansari H; Coen M; Cirelli C; Benca RM; Ghilardi MF; Tononi G. Sleep-dependent improvement in visuomotor learning: a causal role for slow waves. SLEEP 2009;32(10):1273-1284.     

Comparison of sleep parameters at titration and subsequent compliance between CPAP-pretreated and non-CPAP-pretreated patients with obstructive sleep apnea

BACKGROUND AND PURPOSE: Obstructive sleep apnea-hypopnea syndrome (OSAHS) patients undergo continuous positive airway pressure (CPAP) treatment for the first time on titration night, and then the effect of overnight CPAP treatment is estimated immediately. The purpose of this study is to compare the effects of CPAP-pretreated and non-pretreated on patients with OSAHS. METHODS: Prospective randomized, controlled parallel study was performed. Seventy patients with OSAHS received autoadjusted CPAP treatment for 2 months and then received the standard manual titration (CPAP-pretreated group). The other 70 did not receive any CPAP treatment before receiving the standard manual titration (non-CPAP-pretreated group). RESULTS: The CPAP-pretreated group had significantly improved sleep efficiency and arousal index in non-rapid eye movement (NREM) sleep compared with the initial CPAP group at titration, whereas there were no significant differences between the two groups in other sleep parameters. Eight patients in the non-CPAP-pretreated group discontinued CPAP treatment 9 months after the titration, whereas one patient in the CPAP-pretreated group discontinued treatment. CONCLUSIONS: A preceding CPAP treatment showed minimal effects on sleep parameters on titration night and subsequent CPAP compliance rate, although it was speculated that this preceding treatment might be of benefit for better compliance in some patients.