Sleep laboratory study on single and repeated dose effects of paroxetine, alprazolam and their combination in healthy young volunteers

Automated Scoring of Sleep and Associated Events

Conventionally, sleep and associated events are scored visually by trained technologists according to the rules summarized in the American Academy of Sleep Medicine Manual. Since its first publication in 2007, the manual was continuously updated; the most recent version as of this writing was published in 2020. Human expert scoring is considered as gold standard, even though there is increasing evidence of limited interrater reliability between human scorers. Significant advances in machine learning have resulted in powerful methods for addressing complex classification problems such as automated scoring of sleep and associated events. Evidence is increasing that these autoscoring systems deliver performance comparable to manual scoring and offer several advantages to visual scoring: (1) avoidance of the rather expensive, time-consuming, and difficult visual scoring task that can be performed only by well-trained and experienced human scorers, (2) attainment of consistent scoring results, and (3) proposition of added value such as scoring in real time, sleep stage probabilities per epoch (hypnodensity), estimates of signal quality and sleep/wake-related features, identifications of periods with clinically relevant ambiguities (confidence trends), configurable sensitivity and rule settings, as well as cardiorespiratory sleep staging for home sleep apnea testing. This chapter describes the development of autoscoring systems since the first attempts in the 1970s up to the most recent solutions based on deep neural network approaches which achieve an accuracy that allows to use the autoscoring results directly for review and interpretation by a physician.

A randomized phase 1 single-dose polysomnography study of ASP8062, a GABAB receptor positive allosteric modulator

RATIONALE

Previous research suggests that sleep polysomnography and EEG endpoints can be used to assess GABAergic activity; however, the impact of GABA_B receptor positive allosteric modulators on sleep endpoints remains unclear.

OBJECTIVES

This phase 1 study compared a single dose of ASP8062 (35 mg or 70 mg), a GABA_B receptor positive allosteric modulator, with placebo and paroxetine (40 mg).

METHODS

Healthy adult volunteers were randomized to four treatments (35 mg ASP8062, 70 mg ASP8062, paroxetine 40 mg, or matching placebo), each separated by a 14-day washout. Primary endpoints obtained by polysomnography were time in stage N3 or SWS and time in rapid eye movement (REM) sleep. Secondary endpoints included impact on sleep stages and electroencephalography parameters, pharmacokinetics, nighttime growth hormone (GH), and safety/tolerability.

RESULTS

In 20 randomized volunteers, ASP8062 led to a significant and seemingly dose-dependent increase in SWS over the entire night; this increase was mainly observed during the first third of the night. ASP8062 did not impact time in REM sleep. Paroxetine had no effect on SWS but produced a significant reduction in time spent in REM sleep. A dose-dependent trend in increased GH release was also observed with ASP8062. Headache and nausea were the most commonly reported treatment-emergent adverse events (TEAEs) for ASP8062; most TEAEs were mild in severity.

CONCLUSIONS

Single-dose ASP8062 (35 and 70 mg) appeared to result in CNS penetration and enhanced GABAergic activity as measured by increases in slow-wave sleep and growth hormone release.

Epidemiologic assessment of benzodiazepine exposure among suicide deaths in Colorado, 2015-2017

BACKGROUND

Suicide rates have been climbing in the U.S., particularly in Rocky Mountain states such as Colorado. Benzodiazepines have been linked with suicidal ideation, but there have been few population level assessments of this link. We conducted a public health assessment to determine the epidemiology and prevalence of recent benzodiazepine exposure, among suicide deaths in Colorado from 2015 to 17.

METHODS

This epidemiologic assessment linked Colorado's Prescription Drug Monitoring Program, death certificate data, and Violent Death Reporting System to determine patterns of benzodiazepine exposure among suicide deaths in Colorado between 2015 and 2017. Recent benzodiazepine exposure was defined as receiving a prescription within 30 days of death or having a positive toxicology screen post-mortem.

RESULTS

Among the 3465 suicide deaths in Colorado between 2015 and 2017, 20% had recent benzodiazepine exposure, and nearly 50% of those also had recent opioid exposure. Recent benzodiazepine exposure was more common among females than males (34% versus 16%). Among suicide deaths, those who died via drug overdose were more likely to have had recent benzodiazepine exposure (48%), compared to suicides by firearm (17%), hanging/asphyxiation (13%) and all other methods (approximately 20%).

CONCLUSIONS

Benzodiazepines have been linked to suicidal ideation, but population level assessments of benzodiazepine exposure among suicide deaths are rare. Our epidemiologic assessment indicates a relatively high prevalence of recent benzodiazepine exposure that warrants further investigation from both clinical and public health perspectives.

Sleep and the Pharmacotherapy of Alcohol Use Disorder: Unfortunate Bedfellows. A Systematic Review With Meta-Analysis

Background: Sleep disorders are commonly associated with acute and chronic use of alcohol and with abstinence. To date, there are four approved drugs to treat alcohol use disorder (AUD): disulfiram, acamprosate, naltrexone, and nalmefene. These AUD therapies reduce the craving and risk of relapse into heavy drinking, but little is known about their effect on sleep. As recent evidences indicate a crucial role of sleep disorders in AUD, claiming that sleep problems may trigger alcohol abuse and relapses, it is fundamental to clarify the impact of those drugs on the sleep quality of AUD patients. This systematic review aims to answer the question: how does the pharmacotherapy for AUD affect sleep? Methods: We searched PubMed, Embase, CINAHL Plus, Cochrane, and Scopus using sleep- and AUD pharmacotherapy-related keywords. The articles included were appraised using the CASP checklists, and the risk of bias was assessed following the Cochrane risk-of-bias assessment tool. Finally, we pooled sleep outcomes in a meta-analysis to measure the overall effect. Results and Conclusion: We included 26 studies: only three studies focused on sleep as a main outcome, two with polysomnography (objective measurement), and one with subjective self-reported sleep, while all the other studies reported sleep problems among the adverse effects (subjective report). The only study available on disulfiram showed reduced REM sleep. Acamprosate showed no/little effect on self-reported sleep but improved sleep continuity and architecture measured by polysomnography. The two opioidergic drugs naltrexone and nalmefene had mainly detrimental effect on sleep, giving increased insomnia and/or somnolence compared with placebo, although not always significant. The meta-analysis confirmed significantly increased somnolence and insomnia in the naltrexone group, compared with the placebo. Overall, the currently available evidences show more sleep problems with the opioidergic drugs (especially naltrexone), while acamprosate seems to be well tolerated or even beneficial. Acamprosate might be a more suitable choice when patients with AUD report sleep problems. Due to the paucity of information available, and with the majority of results being subjective, more research on this topic is needed to further inform the clinical practice, ideally with more objective measurements such as polysomnography.

Advanced Analysis of Pharmaco-Sleep Data in Humans

Pharmaco-sleep studies in humans aim at the description of the effects of drugs, most frequently substances that act on the central nervous system, by means of quantitative analysis of biosignals recorded in subjects during sleep. Up to 2007, the only standard for the classification of sleep macrostructure that found worldwide acceptance were the rules published in 1968 by Rechtschaffen and Kales. In May 2007, the AASM Manual for the Scoring of Sleep and Associated Events was published by the American Academy of Sleep Medicine, and concerning the classification of sleep stages, these new rules are supposed to replace those developed by Rechtschaffen and Kales. As compared to the rather low interrater reliability of manual sleep scoring, semiautomated approaches may achieve a reliability close to 1 (Cohen's kappa 0.99 for 2 semiautomated scorings as compared to 0.76 for 2 manual scorings) without any decline in validity. Depending on the aim of the pharmaco-sleep study, additional analyses concerning sleep fragmentation, sleep microstructure, sleep depth, sleep processes and local aspects of sleep should be considered. For some of these additional features, rules for visual scoring have been established, while for others automatic analysis is obligatory. Generally, for reasons of cost-effectiveness but also reliability, automatic analysis is preferable to visual analysis. However, the validity of the automatic method applied has to be proven.

Computer-Assisted Automated Scoring of Polysomnograms Using the Somnolyzer System

STUDY OBJECTIVES

Manual scoring of polysomnograms is a time-consuming and tedious process. To expedite the scoring of polysomnograms, several computerized algorithms for automated scoring have been developed. The overarching goal of this study was to determine the validity of the Somnolyzer system, an automated system for scoring polysomnograms.

DESIGN

The analysis sample comprised of 97 sleep studies. Each polysomnogram was manually scored by certified technologists from four sleep laboratories and concurrently subjected to automated scoring by the Somnolyzer system. Agreement between manual and automated scoring was examined. Sleep staging and scoring of disordered breathing events was conducted using the 2007 American Academy of Sleep Medicine criteria.

SETTING

Clinical sleep laboratories.

MEASUREMENTS AND RESULTS

A high degree of agreement was noted between manual and automated scoring of the apnea-hypopnea index (AHI). The average correlation between the manually scored AHI across the four clinical sites was 0.92 (95% confidence interval: 0.90-0.93). Similarly, the average correlation between the manual and Somnolyzer-scored AHI values was 0.93 (95% confidence interval: 0.91-0.96). Thus, interscorer correlation between the manually scored results was no different than that derived from manual and automated scoring. Substantial concordance in the arousal index, total sleep time, and sleep efficiency between manual and automated scoring was also observed. In contrast, differences were noted between manually and automated scored percentages of sleep stages N1, N2, and N3.

CONCLUSION

Automated analysis of polysomnograms using the Somnolyzer system provides results that are comparable to manual scoring for commonly used metrics in sleep medicine. Although differences exist between manual versus automated scoring for specific sleep stages, the level of agreement between manual and automated scoring is not significantly different than that between any two human scorers. In light of the burden associated with manual scoring, automated scoring platforms provide a viable complement of tools in the diagnostic armamentarium of sleep medicine.

Guidelines for the recording and evaluation of pharmaco-sleep studies in man: the International Pharmaco-EEG Society (IPEG)

The International Pharmaco-EEG Society (IPEG) presents guidelines summarising the requirements for the recording and computerised evaluation of pharmaco-sleep data in man. Over the past years, technical and data-processing methods have advanced steadily, thus enhancing data quality and expanding the palette of sleep assessment tools that can be used to investigate the activity of drugs on the central nervous system (CNS), determine the time course of effects and pharmacodynamic properties of novel therapeutics, hence enabling the study of the pharmacokinetic/pharmacodynamic relationship, and evaluate the CNS penetration or toxicity of compounds. However, despite the presence of robust guidelines on the scoring of polysomnography -recordings, a review of the literature reveals inconsistent -aspects in the operating procedures from one study to another. While this fact does not invalidate results, the lack of standardisation constitutes a regrettable shortcoming, especially in the context of drug development programmes. The present guidelines are intended to assist investigators, who are using pharmaco-sleep measures in clinical research, in an effort to provide clear and concise recommendations and thereby to standardise methodology and facilitate comparability of data across laboratories.

Effects of pregabalin on sleep in generalized anxiety disorder

Sleep disturbance is a cardinal symptom in both DSM-IV and ICD-10 criteria for generalized anxiety disorder (GAD). This review summarizes the results of clinical trials and pooled analyses that provide data on pregabalin's effect on sleep disturbance in patients diagnosed with GAD. The hypothesized mechanism of action of pregabalin is distinctly different from other anxiolytics. Pregabalin binds to a membrane α2δ subunit protein to inhibit release in excited central nervous system neurons of neurotransmitters implicated in pathological anxiety. Treatment with pregabalin has been found to be associated with significant improvement in GAD-related sleep disturbance across seven placebo-controlled clinical trials. Treatment with pregabalin is associated with improvement in all forms of insomnia and improvement in sleep has been found to be correlated with reduction in functional impairment and improvement in quality of life on subjective global measures. Results of a mediational analysis suggest that 53% of the effect of pregabalin on sleep disturbance was due to a direct effect and 47% was due to an indirect effect, mediated through prior reduction in anxiety symptom severity. In patients with GAD, improvement in sleep has been found to be associated with a reduction in daytime sleepiness. However, dose-related sedation is reported, typically in the first 2 wk of treatment, in approximately 10-30% of patients, depending on the dose used and the speed of titration. Insomnia is a common component of the clinical presentation of GAD and pregabalin appears to be an efficacious treatment for this often chronic and disabling symptom.

Performance of an automated polysomnography scoring system versus computer-assisted manual scoring

STUDY OBJECTIVES

Manual scoring of polysomnograms (PSG) is labor intensive and has considerable variance between scorers. Automation of scoring could reduce cost and improve reproducibility. The purpose of this study was to compare a new automated scoring system (YST-Limited, Winnipeg, Canada) with computer-assisted manual scoring.

DESIGN

Technical assessment.

SETTING

Five academic medical centers.

PARTICIPANTS

N/A.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

Seventy PSG files were selected at University of Pennsylvania (Penn) and distributed to five US academic sleep centers. Two blinded technologists from each center scored each file. Automatic scoring was performed at Penn by a YST Limited technician using a laptop containing the software. Variables examined were sleep stages, arousals, and apnea-hypopnea index (AHI) using three methods of identifying hypopneas. Automatic scores were not edited and were compared to the average scores of the 10 technologists. Intraclass correlation coefficient (ICC) was obtained for the 70 pairs and compared to across-sites ICCs for manually scored results. ICCs for automatic versus manual scoring were > 0.8 for total sleep time, stage N2, and nonrapid eye movement arousals and > 0.9 for AHI scored by primary and secondary American Academy of Sleep Medicine criteria. ICCs for other variables were not as high but were comparable to the across-site ICCs for manually scored results.

CONCLUSION

The automatic system yielded results that were similar to those obtained by experienced technologists. Very good ICCs were obtained for many primary PSG outcome measures. This automated scoring software, particularly if supplemented with manual editing, may increase laboratory efficiency and standardize PSG scoring results within and across sleep centers.

Circadian and sleep disorder in Huntington's disease

Huntington's disease is a progressive neurological disorder that starts insidiously with motor, cognitive or psychiatric disturbance, and progresses through a distressing range of symptoms to end with a devastating loss of function, both motor and executive. There is a growing awareness that, in addition to cognitive and psychiatric symptoms, there are other important non-motor symptoms in HD, including sleep and circadian abnormalities. It is not clear if sleep-wake changes are caused directly by HD gene-related pathology, or if they are simply a consequence of having a neurodegenerative disease. From a patient point of view, the answer is irrelevant, since sleep and circadian disturbances are deleterious to good daily living, even in neurologically normal people. The assumption should be that, at the very least, sleep and/or circadian disturbance in HD patients will contribute to their symptoms. At worst, they may contribute to the progressive decline in HD. Here I review the state of our understanding of sleep and circadian abnormalities in HD. I also outline a set of simple rules that can be followed to improve the chances of a good night's sleep, since preventing any 'preventable' symptoms is the a logical first step in treating disease. The long-term impact of sleep disruption in HD is unknown. There have been no large-scale systematic studies of in sleep in HD. Furthermore, there has never been a study of the efficacy of pharmaceuticals that are typically used to treat sleep deficits in HD patients. Thus treatment of sleep disturbance in HD is necessarily empirical. A better understanding of the relationship between sleep/circadian abnormalities and HD pathology is needed, if treatment of this aspect of HD is to be optimized.

Cerebrospinal hypocretin, daytime sleepiness and sleep architecture in Parkinson's disease dementia

Excessive daytime sleepiness is common in Parkinson's disease and has been associated with Parkinson's disease-related dementia. Narcoleptic features have been observed in Parkinson's disease patients with excessive daytime sleepiness and hypocretin cell loss has been found in the hypothalamus of Parkinson's disease patients, in association with advanced disease. However, studies on cerebrospinal fluid levels of hypocretin-1 (orexin A) in Parkinson's disease have been inconclusive. Reports of sleep studies in Parkinson's disease patients with and without excessive daytime sleepiness have also been disparate, pointing towards a variety of causes underlying excessive daytime sleepiness. In this study, we aimed to measure cerebrospinal fluid hypocretin-1 levels in Parkinson's disease patients with and without dementia and to study their relationship to dementia and clinical excessive daytime sleepiness, as well as to describe potentially related sleep architecture changes. Twenty-one Parkinson's disease patients without dementia and 20 Parkinson's disease patients with dementia, along with 22 control subjects without sleep complaints, were included. Both Epworth sleepiness scale, obtained with the help of the caregivers, and mini-mental state examination were recorded. Lumbar cerebrospinal fluid hypocretin-1 levels were measured in all individuals using a radio-immunoassay technique. Additionally, eight Parkinson's disease patients without dementia and seven Parkinson's disease patients with dementia underwent video-polysomnogram and multiple sleep latencies test. Epworth sleepiness scale scores were higher in Parkinson's disease patients without dementia and Parkinson's disease patients with dementia than controls (P < 0.01) and scores >10 were more frequent in Parkinson's disease patients with dementia than in Parkinson's disease patients without dementia (P = 0.04). Cerebrospinal fluid hypocretin-1 levels were similar among groups (controls = 321.15 +/- 47.15 pg/ml; without dementia = 300.99 +/- 58.68 pg/ml; with dementia = 309.94 +/- 65.95 pg/ml; P = 0.67), and unrelated to either epworth sleepiness scale or mini-mental state examination. Dominant occipital frequency awake was slower in Parkinson's disease patients with dementia than Parkinson's disease patients without dementia (P = 0.05). Presence of slow dominant occipital frequency and/or loss of normal non-rapid eye movement sleep architecture was more frequent among Parkinson's disease patients with dementia (P = 0.029). Thus, excessive daytime sleepiness is more frequent in Parkinson's disease patients with dementia than Parkinson's disease patients without dementia, but lumbar cerebrospinal fluid hypocretin-1 levels are normal and unrelated to severity of sleepiness or the cognitive status. Lumbar cerebrospinal fluid does not accurately reflect the hypocretin cell loss known to occur in the hypothalamus of advanced Parkinson's disease. Alternatively, mechanisms other than hypocretin cells dysfunction may be responsible for excessive daytime sleepiness and the sleep architecture alterations seen in these patients.

Insomnia in patients with depression: some pathophysiological and treatment considerations

The almost ubiquitous sleep disturbances in patients with depression commonly, but not always, subside with the remission of depression. Evidence linking insomnia with the risk of relapses in recurrent depression, as well as suicide, makes optimization of the treatment of insomnia associated with depression a priority. However, most antidepressant agents do not adequately address the sleep complaints in depression: their effects on sleep range from sizeable improvement to equally significant worsening. One approach to the management of insomnia associated with depression is to choose a sedating antidepressant agent such as trazodone, mirtazapine or agomelatine. A second approach is to start with a non-sedating antidepressant (e.g. the selective serotonin reuptake inhibitors, bupropion, venlafaxine or duloxetine); those with a persistent or treatment-emergent insomnia can be switched to a more sedating antidepressant, or offered a hypnotic or cognitive-behavioural therapy as adjunctive treatment. The review discusses the advantages and disadvantages of all treatment options, pharmacological and otherwise.

Evaluation of automated and semi-automated scoring of polysomnographic recordings from a clinical trial using zolpidem in the treatment of insomnia

OBJECTIVE

To evaluate the performance of 2 automated systems, Morpheus and Somnolyzer24X7, with various levels of human review/editing, in scoring polysomnographic (PSG) recordings from a clinical trial using zolpidem in a model of transient insomnia.

METHODS

164 all-night PSG recordings from 82 subjects collected during 2 nights of sleep, one under placebo and one under zolpidem (10 mg) treatment were used. For each recording, 6 different methods were used to provide sleep stage scores based on Rechtschaffen & Kales criteria: 1) full manual scoring, 2) automated scoring by Morpheus 3) automated scoring by Somnolyzer24X7, 4) automated scoring by Morpheus with full manual review, 5) automated scoring by Morpheus with partial manual review, 6) automated scoring by Somnolyzer24X7 with partial manual review. Ten traditional clinical efficacy measures of sleep initiation, maintenance, and architecture were calculated.

RESULTS

Pair-wise epoch-by-epoch agreements between fully automated and manual scores were in the range of intersite manual scoring agreements reported in the literature (70%-72%). Pair-wise epoch-by-epoch agreements between automated scores manually reviewed were higher (73%-76%). The direction and statistical significance of treatment effect sizes using traditional efficacy endpoints were essentially the same whichever method was used. As the degree of manual review increased, the magnitude of the effect size approached those estimated with fully manual scoring.

CONCLUSION

Automated or semi-automated sleep PSG scoring offers valuable alternatives to costly, time consuming, and intrasite and intersite variable manual scoring, especially in large multicenter clinical trials. Reduction in scoring variability may also reduce the sample size of a clinical trial.

Daytime Ayahuasca administration modulates REM and slow-wave sleep in healthy volunteers

OBJECTIVES

Ayahuasca is a traditional South American psychoactive beverage and the central sacrament of Brazilian-based religious groups, with followers in Europe and the United States. The tea contains the psychedelic indole N,N-dimethyltryptamine (DMT) and beta-carboline alkaloids with monoamine oxidase-inhibiting properties that render DMT orally active. DMT interacts with serotonergic neurotransmission acting as a partial agonist at 5-HT(1A) and 5-HT(2A/2C) receptor sites. Given the role played by serotonin in the regulation of the sleep/wake cycle, we investigated the effects of daytime ayahuasca consumption in sleep parameters.

MEASUREMENTS AND RESULTS

Subjective sleep quality, polysomnography (PSG), and spectral analysis were assessed in a group of 22 healthy male volunteers after the administration of a placebo, an ayahuasca dose equivalent to 1 mg DMT kg(-1) body weight, and 20 mg d-amphetamine, a proaminergic drug, as a positive control. Results show that ayahuasca did not induce any subjectively perceived deterioration of sleep quality or PSG-measured disruptions of sleep initiation or maintenance, in contrast with d-amphetamine, which delayed sleep initiation, disrupted sleep maintenance, induced a predominance of 'light' vs 'deep' sleep and significantly impaired subjective sleep quality. PSG analysis also showed that similarly to d-amphetamine, ayahuasca inhibits rapid eye movement (REM) sleep, decreasing its duration, both in absolute values and as a percentage of total sleep time, and shows a trend increase in its onset latency. Spectral analysis showed that d-amphetamine and ayahuasca increased power in the high frequency range, mainly during stage 2. Remarkably, whereas slow-wave sleep (SWS) power in the first night cycle, an indicator of sleep pressure, was decreased by d-amphetamine, ayahuasca enhanced power in this frequency band.

CONCLUSIONS

Results show that daytime serotonergic psychedelic drug administration leads to measurable changes in PSG and sleep power spectrum and suggest an interaction between these drugs and brain circuits modulating REM and SWS.

Quantifying drug-drug interactions in pharmaco-EEG

A drug interaction refers to an event in which the usual pharmacological effect of a drug is modified by other factors, most frequently additional drugs. When two drugs are administered simultaneously, or within a short time of each other, an interaction can occur that may increase or decrease the intended magnitude or duration of the effect of one or both drugs. Drugs may interact on a pharmaceutical, pharmacokinetic or pharmacodynamic basis. Pharmacodynamic interactions arise when the alteration of the effects occurs at the site of action. This is a wide field where not only interactions between different drugs are considered but also drug and metabolites (midazolam/alpha-hydroxy-midazolam), enantiomers (ketamine), as well as phenomena such as tolerance (nordiazepam) and sensitization (diazepam). Pharmacodynamic interactions can result in antagonism or synergism and can originate at a receptor level (antagonism, partial agonism, down-regulation, up-regulation), at an intraneuronal level (transduction, uptake), or at an interneuronal level (physiological pathways). Alternatively, psychotropic drug interactions assessed through quantitative pharmaco-EEG can be viewed according to the broad underlying objective of the study: safety-oriented (ketoprofen/theophylline, lorazepam/diphenhydramine, granisetron/haloperidol), strictly pharmacologically-oriented (benzodiazepine receptors), or broadly neuro-physiologically-oriented (diazepam/buspirone). Methodological issues are stressed, particularly drug plasma concentrations, dose-response relationships and time-course of effects (fluoxetine/buspirone), and unsolved questions are addressed (yohimbine/caffeine, hydroxizyne/alcohol).

An E-health solution for automatic sleep classification according to Rechtschaffen and Kales: validation study of the Somnolyzer 24 x 7 utilizing the Siesta database

To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 x 7) consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20-95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen's kappa: 0.72) between the Somnolyzer 24 x 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 x 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 x 7 and demonstrated its applicability in clinical routine and sleep studies.