A trial of positive airway pressure for the treatment of sleep apnea in pregnancy.

BACKGROUND: The pathophysiology of obstructive sleep apnea in pregnancy remains poorly understood and studies examining the effect of treatment with positive airway pressure on pregnancy have been limited. OBJECTIVE: This study aimed to perform a randomized controlled trial of positive airway pressure treatment for obstructive sleep apnea in pregnancy. STUDY DESIGN: Participants with a body mass index ≥30 kg/m2 underwent polysomnography at 14 to 20 weeks' gestation (visit 1) and those with obstructive sleep apnea (apnea-hypopnea index ≥5 but <50) were enrolled. In phase 1, participants were randomized to autotitrating positive airway pressure vs sham positive airway pressure; in phase 2, the sham arm was replaced with a sleep hygiene control. Participants returned at 28 to 31 weeks' gestation (visit 2). The mean arterial blood pressure, uterine artery Doppler pulsatility index, endoglin, soluble FMS-like tyrosine kinase 1 levels, and placental growth factor levels were measured, as well as fasting glucose and insulin to calculate insulin resistance (homeostatic model assessment for insulin resistance). The primary outcome was a composite of the uterine artery Doppler pulsatility index, soluble FMS-like tyrosine kinase 1 to placental growth factor ratio, and the homeostatic model assessment for insulin resistance. For secondary analyses, each outcome variable was analyzed independently. Adherence to treatment was examined. RESULTS: A total of 241 participants completed visit 1, and 89 (37%) had an apnea-hypopnea index between 5 and 50. Of the those, 51 participants were randomized in phase 1 and 38 in phase 2. There was no significant difference in our primary outcome by treatment group. In secondary analyses, the uterine artery Doppler pulsatility index was lower in participants on autotitrating positive airway pressure when compared with sleep hygiene controls. Otherwise, there were no differences in the mean arterial blood pressure, angiogenic markers, or metabolic markers in phase 1, phase 2, or across the entire study. The overall adherence to autotitrating positive airway pressure therapy was low, but the mean use was greater in phase 2 (0.3±0.6 hours/night vs 1.3±2.3 hours/night; P=.10). For those on active therapy, fasting glucose values decreased as adherence increased. CONCLUSION: This randomized controlled trial of autotitrating positive airway pressure in pregnancy did not find any differences in a composite primary cardiometabolic risk profile between the treatment groups. Higher autotitrating positive airway pressure adherence was associated with lower fasting glucose levels. The use of a sham positive airway pressure control arm in phase1 may have negatively impacted adherence to active treatment.

A trait of mind: stability and robustness of sleep across sleep opportunity manipulations during simulated military operational stress.

STUDY OBJECTIVES: Within-subject stability of certain sleep features across multiple nights is thought to reflect the trait-like behavior of sleep. However, to be considered a trait, a parameter must be both stable and robust. Here, we examined the stability (i.e. across the same sleep opportunity periods) and robustness (i.e. across sleep opportunity periods that varied in duration and timing) of different sleep parameters. METHODS: Sixty-eight military personnel (14 W) spent 5 nights in the sleep laboratory during a simulated military operational stress protocol. After an adaptation night, participants had an 8-hour sleep opportunity (23:00-07:00) followed by 2 consecutive nights of sleep restriction and disruption which included two 2-hour sleep opportunities (01:00-03:00; 05:00-07:00) and, lastly, another 8-hour sleep opportunity (23:00-07:00). Intra-class correlation coefficients were calculated to examine differences in stability and robustness across different sleep parameters. RESULTS: Sleep architecture parameters were less stable and robust than absolute and relative spectral activity parameters. Further, relative spectral activity parameters were less robust than absolute spectral activity. Absolute alpha and sigma activity demonstrated the highest levels of stability that were also robust across sleep opportunities of varying duration and timing. CONCLUSIONS: Stability and robustness varied across different sleep parameters, but absolute NREM alpha and sigma activity demonstrated robust trait-like behavior across variable sleep opportunities. Reduced stability of other sleep architecture and spectral parameters during shorter sleep episodes as well as across different sleep opportunities has important implications for study design and interpretation.

Identification of Veterans With PTSD Based on EEG Features Collected During Sleep.

Background: Previously, we identified sleep-electroencephalography (EEG) spectral power and synchrony features that differed significantly at a population-average level between subjects with and without posttraumatic stress disorder (PTSD). Here, we aimed to examine the extent to which a combination of such features could objectively identify individual subjects with PTSD. Methods: We analyzed EEG data recorded from 78 combat-exposed Veteran men with (n = 31) and without (n = 47) PTSD during two consecutive nights of sleep. To obviate the need for manual assessment of sleep staging and facilitate extraction of features from the EEG data, for each subject, we computed 780 stage-independent, whole-night features from the 10 most commonly used EEG channels. We performed feature selection and trained a logistic regression model using a training set consisting of the first 47 consecutive subjects (18 with PTSD) of the study. Then, we evaluated the model on a testing set consisting of the remaining 31 subjects (13 with PTSD). Results: Feature selection yielded three uncorrelated features that were consistent across the two consecutive nights and discriminative of PTSD. One feature was from the spectral power in the delta band (2-4 Hz) and the other two were from phase synchronies in the alpha (10-12 Hz) and gamma (32-40 Hz) bands. When we combined these features into a logistic regression model to predict the subjects in the testing set, the trained model yielded areas under the receiver operating characteristic curve of at least 0.80. Importantly, the model yielded a testing-set sensitivity of 0.85 and a positive predictive value (PPV) of 0.31. Conclusions: We identified robust stage-independent, whole-night features from EEG signals and combined them into a logistic regression model to discriminate subjects with and without PTSD. On the testing set, the model yielded a high sensitivity and a PPV that was twice the prevalence rate of PTSD in the U.S. Veteran population. We conclude that, using EEG signals collected during sleep, such a model can potentially serve as a means to objectively identify U.S. Veteran men with PTSD.

Increased oscillatory frequency of sleep spindles in combat-exposed veteran men with post-traumatic stress disorder.

STUDY OBJECTIVES: Sleep disturbances are core symptoms of post-traumatic stress disorder (PTSD), but reliable sleep markers of PTSD have yet to be identified. Sleep spindles are important brain waves associated with sleep protection and sleep-dependent memory consolidation. The present study tested whether sleep spindles are altered in individuals with PTSD and whether the findings are reproducible across nights and subsamples of the study. METHODS: Seventy-eight combat-exposed veteran men with (n = 31) and without (n = 47) PTSD completed two consecutive nights of high-density EEG recordings in a laboratory. We identified slow (10-13 Hz) and fast (13-16 Hz) sleep spindles during N2 and N3 sleep stages and performed topographical analyses of spindle parameters (amplitude, duration, oscillatory frequency, and density) on both nights. To assess reproducibility, we used the first 47 consecutive participants (18 with PTSD) for initial discovery and the remaining 31 participants (13 with PTSD) for replication assessment. RESULTS: In the discovery analysis, compared to non-PTSD participants, PTSD participants exhibited (1) higher slow-spindle oscillatory frequency over the antero-frontal regions on both nights and (2) higher fast-spindle oscillatory frequency over the centro-parietal regions on the second night. The first finding was preserved in the replication analysis. We found no significant group differences in the amplitude, duration, or density of slow or fast spindles. CONCLUSIONS: The elevated spindle oscillatory frequency in PTSD may indicate a deficient sensory-gating mechanism responsible for preserving sleep continuity. Our findings, if independently validated, may assist in the development of sleep-focused PTSD diagnostics and interventions.

Alterations in sleep electroencephalography synchrony in combat-exposed veterans with post-traumatic stress disorder.

STUDY OBJECTIVES: We assessed whether the synchrony between brain regions, analyzed using electroencephalography (EEG) signals recorded during sleep, is altered in subjects with post-traumatic stress disorder (PTSD) and whether the results are reproducible across consecutive nights and subpopulations of the study. METHODS: A total of 78 combat-exposed veteran men with (n = 31) and without (n = 47) PTSD completed two consecutive laboratory nights of high-density EEG recordings. We computed a measure of synchrony for each EEG channel-pair across three sleep stages (rapid eye movement [REM] and non-REM stages 2 and 3) and six frequency bands. We examined the median synchrony in 9 region-of-interest (ROI) pairs consisting of 6 bilateral brain regions (left and right frontal, central, and parietal regions) for 10 frequency-band and sleep-stage combinations. To assess reproducibility, we used the first 47 consecutive subjects (18 with PTSD) for initial discovery and the remaining 31 subjects (13 with PTSD) for replication. RESULTS: In the discovery analysis, five alpha-band synchrony pairs during non-REM sleep were consistently larger in PTSD subjects compared with controls (effect sizes ranging from 0.52 to 1.44) across consecutive nights: two between the left-frontal and left-parietal ROIs, one between the left-central and left-parietal ROIs, and two across central and parietal bilateral ROIs. These trends were preserved in the replication set. CONCLUSION: PTSD subjects showed increased alpha-band synchrony during non-REM sleep in the left frontoparietal, left centro-parietal, and inter-parietal brain regions. Importantly, these trends were reproducible across consecutive nights and subpopulations. Thus, these alterations in alpha synchrony may be discriminatory of PTSD.

An attempt to identify reproducible high-density EEG markers of PTSD during sleep.

STUDY OBJECTIVES: We examined electroencephalogram (EEG) spectral power to study abnormalities in regional brain activity in post-traumatic stress disorder (PTSD) during sleep. We aimed to identify sleep EEG markers of PTSD that were reproducible across nights and subsamples of our study population. METHODS: Seventy-eight combat-exposed veteran men with (n = 31) and without (n = 47) PTSD completed two consecutive nights of high-density EEG recordings in a laboratory. We performed spectral-topographical EEG analyses on data from both nights. To assess reproducibility, we used the first 47 consecutive participants (18 with PTSD) for initial discovery and the remaining 31 participants (13 with PTSD) for replication. RESULTS: In the discovery analysis, compared with non-PTSD participants, PTSD participants exhibited (1) reduced delta power (1-4 Hz) in the centro-parietal regions during nonrapid eye movement (NREM) sleep and (2) elevated high-frequency power, most prominent in the gamma band (30-40 Hz), in the antero-frontal regions during both NREM and rapid eye movement (REM) sleep. These findings were consistent across the two study nights, with reproducible trends in the replication analysis. We found no significant group differences in theta power (4-8 Hz) during REM sleep and sigma power (12-15 Hz) during N2 sleep. CONCLUSIONS: The reduced centro-parietal NREM delta power, indicating reduced sleep depth, and the elevated antero-frontal NREM and REM gamma powers, indicating heightened central arousal, are potential objective sleep markers of PTSD. If independently validated, these putative EEG markers may offer new targets for the development of sleep-specific PTSD diagnostics and interventions.

EEG power during waking and NREM sleep in primary insomnia.

OBJECTIVE: Pathophysiological models of insomnia invoke the concept of 24-hour hyperarousal, which could lead to symptoms and physiological findings during waking and sleep. We hypothesized that this arousal could be seen in the waking electroencephalogram (EEG) of individuals with primary insomnia (PI), and that waking EEG power would correlate with non-REM (NREM) EEG. METHODS: Subjects included 50 PI and 32 good sleeper controls (GSC). Five minutes of eyes closed waking EEG were collected at subjects' usual bedtimes, followed by polysomnography (PSG) at habitual sleep times. An automated algorithm and visual editing were used to remove artifacts from waking and sleep EEGs, followed by power spectral analysis to estimate power from 0.5-32 Hz. RESULTS: We did not find significant differences in waking or NREM EEG spectral power of PI and GSC. Significant correlations between waking and NREM sleep power were observed across all frequency bands in the PI group and in most frequency bands in the GSC group. CONCLUSIONS: The absence of significant differences between groups in waking or NREM EEG power suggests that our sample was not characterized by a high degree of cortical arousal. The consistent correlations between waking and NREM EEG power suggest that, in samples with elevated NREM EEG beta activity, waking EEG power may show a similar pattern.

Examining initial sleep onset in primary insomnia: a case-control study using 4-second epochs.

STUDY OBJECTIVES: To explore the sleep onset process in primary insomnia patients, new rules for scoring 4-second epochs were implemented to score sleep and artifacts during initial sleep onset. Conventional scorings in 20-second and 60-second epochs were also obtained. METHODS: The start of the initial 60-second epoch of stage 1 was used to define "time zero" (t0). Sleep onset periods from 11 patients and 11 individually age- and sex-matched controls spanned from 5 minutes before t0 through 29 minutes after t0. Using the new rules, the periods were scored blind to group assignment. This t0 time-referenced the data analysis to one plausible midpoint in the sleep onset process. In parallel, latencies were time-referenced from good night time. RESULTS: Reliability in scoring sleep and artifacts was adequate (kappa = 0.68 & 0.63, respectively, p <0.001). Group differences in sleep latencies were marginal in 60-second and 20-second scoring but significant with a definition of 4-second sleep latency. Patients had more 4-second epochs scored as awake (Mantel-Haenszel chi2 = 271, d.f. = 1, p <0.001) and containing artifact (M-H chi2 = 143, p <0.001). Patients took longer to achieve 30 continuous 4-second epochs of NREM sleep (Breslow chi2 = 4.03, d.f. = 1, p = 0.045) after t0. Patients accumulated sleep more slowly with all 3 scoring rules after t0. A slower rate of accumulating sleep after t0 was detected only with the 4-second scoring (p = 0.047). CONCLUSIONS: Evidence was present for momentary state-switching instabilities in the patients during the initial sleep onset process. Using rules for scoring small epochs may reveal such instabilities more readily than traditional scoring methods.

Decreased nonlinear complexity and chaos during sleep in first episode schizophrenia: a preliminary report.

Schizophrenia is characterized by disturbed sleep architecture. It has been thought that sleep abnormalities may underlie information processing deficits associated with this disorder. Nonlinear analyses of sleep data can provide valuable information on sleep characteristics that may be relevant to the functions of sleep. This study examined the predictability and nonlinear complexity of sleep EEG time series in two EEG channels (C4 and F4) using measures of nonlinearity, such as symbolic dynamics and the largest Lyapunov exponent (LLE) in schizophrenia. A series of antipsychotic naive patients with first episode of schizophrenia or schizoaffective disorder and age-matched healthy controls were studied during awake period, stage 1/2, slow wave sleep (stage 3/4) and rapid eye movement (REM) sleep. Nonlinearity scores were significantly lower during awake stage in patients compared to controls suggesting that there may be a diminished interplay between various parameters for the genesis of waking EEG. Symbolic dynamics and LLE were significantly lower in patients during REM compared to healthy controls, suggesting decreased nonlinear complexity of the EEG time series and diminished chaos in schizophrenia. Decreased nonlinear complexity was also correlated with neurocognitive deficits as assessed by the Wisconsin card sorting test. Diminished complexity of EEG time series during awake and REM sleep in patients with schizophrenia may underlie the impaired ability to process information in psychotic disorders such as schizophrenia.

Acute stress affects heart rate variability during sleep.

OBJECTIVE: Although stress can elicit profound and lasting effects on sleep, the pathways whereby stress affects sleep are not well understood. In this study, we used autoregressive spectral analysis of the electrocardiogram (EKG) interbeat interval sequence to characterize stress-related changes in heart rate variability during sleep in 59 healthy men and women. METHODS: Participants (N = 59) were randomly assigned to a control or stress condition, in which a standard speech task paradigm was used to elicit acute stress in the immediate presleep period. EKG was collected throughout the night. The high frequency component (0.15-0.4 Hz Eq) was used to index parasympathetic modulation, and the ratio of low to high frequency power (0.04-0.15 Hz Eq/0.15-0.4 Hz Eq) of heart rate variability was used to index sympathovagal balance. RESULTS: Acute psychophysiological stress was associated with decreased levels of parasympathetic modulation during nonrapid eye movement (NREM) and rapid eye movement sleep and increased levels of sympathovagal balance during NREM sleep. Parasympathetic modulation increased across successive NREM cycles in the control group; these increases were blunted in the stress group and remained essentially unchanged across successive NREM periods. Higher levels of sympathovagal balance during NREM sleep were associated with poorer sleep maintenance and lower delta activity. CONCLUSIONS: Changes in heart rate variability associated with acute stress may represent one pathway to disturbed sleep. Stress-related changes in heart rate variability during sleep may also be important in association with chronic stressors, which are associated with significant morbidity and increased risk for mortality.