Cyclic alternating pattern (CAP) alterations in narcolepsy

Narcolepsy and rapid eye movement sleep

Since the first description of narcolepsy at the end of the 19th Century, great progress has been made. The disease is nowadays distinguished as narcolepsy type 1 and type 2. In the 1960s, the discovery of rapid eye movement sleep at sleep onset led to improved understanding of core sleep-related disease symptoms of the disease (excessive daytime sleepiness with early occurrence of rapid eye movement sleep, sleep-related hallucinations, sleep paralysis, rapid eye movement parasomnia), as possible dysregulation of rapid eye movement sleep, and cataplexy resembling an intrusion of rapid eye movement atonia during wake. The relevance of non-sleep-related symptoms, such as obesity, precocious puberty, psychiatric and cardiovascular morbidities, has subsequently been recognized. The diagnostic tools have been improved, but sleep-onset rapid eye movement periods on polysomnography and Multiple Sleep Latency Test remain key criteria. The pathogenic mechanisms of narcolepsy type 1 have been partly elucidated after the discovery of strong HLA class II association and orexin/hypocretin deficiency, a neurotransmitter that is involved in altered rapid eye movement sleep regulation. Conversely, the causes of narcolepsy type 2, where cataplexy and orexin deficiency are absent, remain unknown. Symptomatic medications to treat patients with narcolepsy have been developed, and management has been codified with guidelines, until the recent promising orexin-receptor agonists. The present review retraces the steps of the research on narcolepsy that linked the features of the disease with rapid eye movement sleep abnormality, and those that do not appear associated with rapid eye movement sleep.

Spotlight on Sleep Stage Classification Based on EEG

The recommendations for identifying sleep stages based on the interpretation of electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG], and electromyography [EMG]), derived from the Rechtschaffen and Kales manual, were published in 2007 at the initiative of the American Academy of Sleep Medicine, and regularly updated over years. They offer an important tool to assess objective markers in different types of sleep/wake subjective complaints. With the aims and advantages of simplicity, reproducibility and standardization of practices in research and, most of all, in sleep medicine, they have overall changed little in the way they describe sleep. However, our knowledge on sleep/wake physiology and sleep disorders has evolved since then. High-density electroencephalography and intracranial electroencephalography studies have highlighted local regulation of sleep mechanisms, with spatio-temporal heterogeneity in vigilance states. Progress in the understanding of sleep disorders has allowed the identification of electrophysiological biomarkers better correlated with clinical symptoms and outcomes than standard sleep parameters. Finally, the huge development of sleep medicine, with a demand for explorations far exceeding the supply, has led to the development of alternative studies, which can be carried out at home, based on a smaller number of electrophysiological signals and on their automatic analysis. In this perspective article, we aim to examine how our description of sleep has been constructed, has evolved, and may still be reshaped in the light of advances in knowledge of sleep physiology and the development of technical recording and analysis tools. After presenting the strengths and limitations of the classification of sleep stages, we propose to challenge the "EEG-EOG-EMG" paradigm by discussing the physiological signals required for sleep stages identification, provide an overview of new tools and automatic analysis methods and propose avenues for the development of new approaches to describe and understand sleep/wake states.

Sleep macro- and micro-structure in autoimmune encephalitis: single case report from the subacute phase of the disease to the follow-up

Sleep disorders are frequently described in autoimmune encephalitis (AE); however, data on sleep texture are fragmentary. We analyzed the polysomnography of a woman affected by AE, and we performed cyclic alternating pattern (CAP) scoring during the subacute phase of the disease and at follow-up. The first polysomnography showed deviations both at macro and microstructure levels, with a marked reduction of CAP rate compare to healthy sleepers (20.8% vs 33%). After 6-months sleep macrostructure improved, whilst CAP parameters remained abnormal. This is the first polysomnographic analysis, comprehensive of microstructural data, performed in AE. We briefly discuss the results.

Automated Characterization of Cyclic Alternating Pattern Using Wavelet-Based Features and Ensemble Learning Techniques with EEG Signals

Sleep is highly essential for maintaining metabolism of the body and mental balance for increased productivity and concentration. Often, sleep is analyzed using macrostructure sleep stages which alone cannot provide information about the functional structure and stability of sleep. The cyclic alternating pattern (CAP) is a physiological recurring electroencephalogram (EEG) activity occurring in the brain during sleep and captures microstructure of the sleep and can be used to identify sleep instability. The CAP can also be associated with various sleep-related pathologies, and can be useful in identifying various sleep disorders. Conventionally, sleep is analyzed using polysomnogram (PSG) in various sleep laboratories by trained physicians and medical practitioners. However, PSG-based manual sleep analysis by trained medical practitioners is onerous, tedious and unfavourable for patients. Hence, a computerized, simple and patient convenient system is highly desirable for monitoring and analysis of sleep. In this study, we have proposed a system for automated identification of CAP phase-A and phase-B. To accomplish the task, we have utilized the openly accessible CAP sleep database. The study is performed using two single-channel EEG modalities and their combination. The model is developed using EEG signals of healthy subjects as well as patients suffering from six different sleep disorders namely nocturnal frontal lobe epilepsy (NFLE), sleep-disordered breathing (SDB), narcolepsy, periodic leg movement disorder (PLM), insomnia and rapid eye movement behavior disorder (RBD) subjects. An optimal orthogonal wavelet filter bank is used to perform the wavelet decomposition and subsequently, entropy and Hjorth parameters are extracted from the decomposed coefficients. The extracted features have been applied to different machine learning algorithms. The best performance is obtained using ensemble of bagged tress (EBagT) classifier. The proposed method has obtained the average classification accuracy of 84%, 83%, 81%, 78%, 77%, 76% and 72% for NFLE, healthy, SDB, narcolepsy, PLM, insomnia and RBD subjects, respectively in discriminating phases A and B using a balanced database. Our developed model yielded an average accuracy of 78% when all 77 subjects including healthy and sleep disordered patients are considered. Our proposed system can assist the sleep specialists in an automated and efficient analysis of sleep using sleep microstructure.

Cortical arousal frequency is increased in narcolepsy type 1

STUDY OBJECTIVES

Hypocretin deficient narcolepsy (type 1, NT1) presents with multiple sleep abnormalities including sleep-onset rapid eye movement (REM) periods (SOREMPs) and sleep fragmentation. We hypothesized that cortical arousals, as scored by an automatic detector, are elevated in NT1 and narcolepsy type 2 (NT2) patients as compared to control subjects.

METHODS

We analyzed nocturnal polysomnography (PSG) recordings from 25 NT1 patients, 20 NT2 patients, 18 clinical control subjects (CC, suspected central hypersomnia but with normal cerebrospinal (CSF) fluid hypocretin-1 (hcrt-1) levels and normal results on the multiple sleep latency test), and 37 healthy control (HC) subjects. Arousals were automatically scored using Multimodal Arousal Detector (MAD), a previously validated automatic wakefulness and arousal detector. Multiple linear regressions were used to compare arousal index (ArI) distributions across groups. Comparisons were corrected for age, sex, body-mass index, medication, apnea-hypopnea index, periodic leg movement index, and comorbid rapid eye movement sleep behavior disorder.

RESULTS

NT1 was associated with an average increase in ArI of 4.02 events/h (p = 0.0246) compared to HC and CC, while no difference was found between NT2 and control groups. Additionally, a low CSF hcrt-1 level was predictive of increased ArI in all the CC, NT2, and NT1 groups.

CONCLUSIONS

The results further support the hypothesis that a loss of hypocretin neurons causes fragmented sleep, which can be measured as an increased ArI as scored by the MAD.

Defining disrupted nighttime sleep and assessing its diagnostic utility for pediatric narcolepsy type 1

STUDY OBJECTIVES

Disrupted nighttime sleep (DNS) is a core narcolepsy symptom of unconsolidated sleep resulting from hypocretin neuron loss. In this study, we define a DNS objective measure and evaluate its diagnostic utility for pediatric narcolepsy type 1 (NT1).

METHODS

This was a retrospective, multisite, cross-sectional study of polysomnograms (PSGs) in 316 patients, ages 6-18 years (n = 150 NT1, n = 22 narcolepsy type 2, n = 27 idiopathic hypersomnia, and n = 117 subjectively sleepy subjects). We assessed sleep continuity PSG measures for (1) their associations with subjective and objective daytime sleepiness, daytime sleep onset REM periods (SOREMPs), self-reported disrupted nocturnal sleep and CSF hypocretin levels and (2) their predictive value for NT1 diagnosis. We then combined the best performing DNS measure with nocturnal SOREMP (nSOREMP) to assess the added value to the logistic regression model and the predictive accuracy for NT1 compared with nSOREMP alone.

RESULTS

The Wake/N1 Index (the number of transitions from any sleep stage to wake or NREM stage 1 normalized by total sleep time) was associated with objective daytime sleepiness, daytime SOREMPs, self-reported disrupted sleep, and CSF hypocretin levels (p's < 0.003) and held highest area under the receiver operator characteristic curves (AUC) for NT1 diagnosis. When combined with nSOREMP, the DNS index had greater accuracy for diagnosing NT1 (AUC = 0.91 [0.02]) than nSOREMP alone (AUC = 0.84 [0.02], likelihood ratio [LR] test p < 0.0001).

CONCLUSIONS

The Wake/N1 Index is an objective DNS measure that can quantify DNS severity in pediatric NT1. The Wake/N1 Index in combination with or without nSOREMP is a useful sleep biomarker that improves recognition of pediatric NT1 using only the nocturnal PSG.

Polysomnographic nighttime features of narcolepsy: A systematic review and meta-analysis

Polysomnographic studies have been conducted to explore nighttime sleep features in narcolepsy, but their relationship to narcolepsy is still imperfectly understood. We conducted a systematic review of the literature exploring polysomnographic differences between narcolepsy patients and healthy controls (HCs) in EMBASE, MEDLINE, All EBM databases, CINAHL, and PsycINFO. 108 studies were identified for this review, 105 of which were used for meta-analysis. Meta-analyses revealed significant reductions in sleep latency, sleep efficiency, slow wave sleep percentage, rapid eye movement sleep (REM) latency, cyclic alternating pattern rate, and increases in total sleep time, wake time after sleep onset (WASO), awakening numbers (AWN) per hour, stage shift (SS) per hour, N1 percentage, apnea hypopnea index, and periodic limb movement index in narcolepsy patients compared with HCs. Furthermore, narcolepsy type 1 patients showed more disturbed nighttime sleep compared with narcolepsy type 2 patients. Children and adolescent narcolepsy patients show increased WASO, AWN, and SS compared with adult patients. Macro- and micro-structurally, our study suggests that narcolepsy patients have poor nighttime sleep. Sex, age, body mass index, disease duration, disease type, medication status, and adaptation night are demographic, clinical and methodological factors that contribute to heterogeneity between studies.

On the use of patterns obtained from LSTM and feature-based methods for time series analysis: application in automatic classification of the CAP A phase subtypes

The cyclic alternating pattern is a marker of sleep instability identified in the electroencephalogram signals whose sequence of transient variations compose the A phases. These phases are divided into three subtypes (A1, A2, and A3) according to the presented patterns. The traditional approach of manually scoring the cyclic alternating pattern events for the full night is unpractical, with a high probability of miss classification, due to the large quantity of information that is produced during a full night recording. To address this concern, automatic methodologies were proposed using a long short-term memory to perform the classification of one electroencephalogram monopolar derivation signal. The proposed model is composed of three classifiers, one for each subtype, performing binary classification in a one versus all procedure. Two methodologies were tested: feed the pre-processed electroencephalogram signal to the classifiers; create features from the pre-processed electroencephalogram signal which were fed to the classifiers (feature-based methods). It was verified that the A1 subtype classification performance was similar for both methods and the A2 subtype classification was higher for the feature-based methods. However, the A3 subtype classification was found to be the most challenging to be performed, and for this classification, the feature-based methods were superior. A characterization analysis was also performed using a recurrence quantification analysis to further examine the subtypes characteristics. The average accuracy and area under the receiver operating characteristic curve for the A1, A2, and A3 subtypes of the feature-based methods were respectively: 82% and 0.92; 80% and 0.88; 85% and 0.86.

Sleep Macrostructure and NREM Sleep Instability Analysis in Pediatric Developmental Coordination Disorder

Developmental Coordination Disorder (DCD) is considered to be abnormal motor skills learning, identified by clumsiness, slowness, and/or motor inaccuracy impairing the daily-life activities in all ages of life, in the absence of sensory, cognitive, or neurological deficits impairment. The present research focuses on studying DCD sleep structure and Cyclic Alternating Pattern (CAP) parameters with a full overnight polysomnography and to study the putative correlations between sleep architecture and CAP parameters with motor coordination skills. The study was a cross-sectional design involving 42 children (26M/16F; mean age 10.12 ± 1.98) selected as a DCD group compared with 79 children (49M/30F; mean age 9.94 ± 2.84) identified as typical (no-DCD) for motor ability and sleep macrostructural parameters according to the MABC-2 and polysomnographic (PSG) evaluations. The two groups (DCD and non-DCD) were similar for age (p = 0.715) and gender (p = 0.854). More significant differences in sleep architecture and CAP parameters were found between two groups and significant correlations were identified between sleep parameters and motor coordination skills in the study population. In conclusion, our data show relevant abnormalities in sleep structure of DCD children and suggest a role for rapid components of A phases on motor coordination development

Isolated rapid eye movement sleep behavior disorder and cyclic alternating pattern: is sleep microstructure a predictive parameter of neurodegeneration?

Objective

To evaluate the role of sleep cyclic alternating pattern (CAP) in patients with isolated REM sleep behavior disorder (IRBD) and ascertain whether CAP metrics might represent a marker of phenoconversion to a defined neurodegenerative condition.

Methods

Sixty-seven IRBD patients were included and classified into patients who phenoconverted to a neurodegenerative disease (RBD converters: converter REM sleep behavior disorder [cRBD]; n = 34) and remained disease-free (RBD non-converters: non-converter REM sleep behavior disorder [ncRBD]; n = 33) having a similar follow-up duration. Fourteen age- and gender-balanced healthy controls were included for comparisons.

Results

Compared to controls, CAP rate and CAP index were significantly decreased in IRBD mainly due to a decrease of A1 phase subtypes (A1 index) despite an increase in duration of both CAP A and B phases. The cRBD group had significantly lower values of CAP rate and CAP index when compared with the ncRBD group and controls. A1 index was significantly reduced in both ncRBD and cRBD groups compared to controls. When compared to the ncRBD group, A3 index was significantly decreased in the cRBD group. The Kaplan-Meier curve applied to cRBD estimated that a value of CAP rate below 32.9% was related to an average risk of conversion of 9.2 years after baseline polysomnography.

Conclusion

IRBD is not exclusively a rapid eye movement (REM) sleep parasomnia, as non-rapid eye movement (non-REM) sleep microstructure can also be affected by CAP changes. Further studies are necessary to confirm that a reduction of specific CAP metrics is a marker of neurodegeneration in IRBD.

Spindle Oscillations in Sleep Disorders: A Systematic Review

Measurement of sleep microarchitecture and neural oscillations is an increasingly popular technique for quantifying EEG sleep activity. Many studies have examined sleep spindle oscillations in sleep-disordered adults; however reviews of this literature are scarce. As such, our overarching aim was to critically review experimental studies examining sleep spindle activity between adults with and without different sleep disorders. Articles were obtained using a systematic methodology with a priori criteria. Thirty-seven studies meeting final inclusion criteria were reviewed, with studies grouped across three categories: insomnia, hypersomnias, and sleep-related movement disorders (including parasomnias). Studies of patients with insomnia and sleep-disordered breathing were more abundant relative to other diagnoses. All studies were cross-sectional. Studies were largely inconsistent regarding spindle activity differences between clinical and nonclinical groups, with some reporting greater or less activity, while many others reported no group differences. Stark inconsistencies in sample characteristics (e.g., age range and diagnostic criteria) and methods of analysis (e.g., spindle bandwidth selection, visual detection versus digital filtering, absolute versus relative spectral power, and NREM2 versus NREM3) suggest a need for greater use of event-based detection methods and increased research standardization. Hypotheses regarding the clinical and empirical implications of these findings, and suggestions for potential future studies, are also discussed.

Association between heart rate variability, blood pressure and autonomic activity in cyclic alternating pattern during sleep

STUDY OBJECTIVES

Cyclic alternating pattern (CAP) is frequently followed by changes in heart rate (HR) and blood pressure (BP), but the sequential associations between CAP and autonomic nerve activity have not been studied. The study aimed to reveal the precise changes in heart rate variability (HRV) during phase A of the CAP cycle.

DESIGN

Polysomnography was recorded according to the CAP Atlas (Terzano, 2002), and BP and electrocardiogram were simultaneously recorded. The complex demodulation method was used for analysis of HRV and evaluation of autonomic nerve activity.

SETTING

Academic sleep laboratory.

PARTICIPANTS

Ten healthy males.

MEASUREMENTS AND RESULTS

The increase in HR (median [first quartile - third quartile]) for each subtype was as follows: A1, 0.64 (-0.30 to 1.69), A2, 1.44 (0.02 to 3.79), and A3, 6.24 (2.53 to 10.76) bpm (A1 vs. A2 P < 0.001, A1 vs. A3 P < 0.001, A2 vs. A3 P < 0.001). The increase in BP for each subtype was as follows: A1, 1.23 (-2.04 to 5.75), A2, 1.76 (-1.46 to 9.32), and A3, 12.51 (4.75 to 19.94) mm Hg (A1 vs. A2 P = 0.249, A1 vs. A3 P < 0.001, A2 vs. A3 P < 0.001). In all of phase A, the peak values for HR and BP appeared at 4.2 (3.5 to 5.4) and 8.4 (7.0 to 10.3) seconds, respectively, after the onset of phase A. The area under the curve for low-frequency and high-frequency amplitude significantly increased after the onset of CAP phase A (P < 0.001) and was higher in the order of subtype A3, A2, and A1 (P < 0.001).

CONCLUSIONS

All phase A subtypes were accompanied with increased heart rate variability, and the largest heart rate variability was seen in subtype A3, while a tendency for less heart rate variability was seen in subtype A1.

Reduced orexin-A levels in frontotemporal dementia: possible association with sleep disturbance

Sleep disturbances including excessive daytime sleepiness (EDS) are encountered in frontotemporal dementia (FTD). To investigate the relationship between the plasma orexin-A levels and sleep disturbance patterns, we measured the plasma orexin-A levels and performed sleep studies in patients with FTD. The orexin-A levels were measured in 10 consecutive patients with FTD and controls by enzyme-linked immunosorbent assay. Nocturnal polysomnography (PSG) and Multiple Sleep Latency Test (MSLT) were performed in 2 patients with FTD. The orexin-A levels were significantly lower in patients with FTD compared to controls. The PSG revealed increased rapid eye movement (REM) latency in patients, whether or not they reported EDS. Mean sleep latency in MSLT was less than 10 minutes in both the patients, being shorter in patient without EDS, but none of them had REM sleep onset. Some patients with FTD may develop narcolepsy-like involuntary sleep attacks, even without complaining of EDS. Involvement of hypothalamus and a subsequent alteration in the orexin levels might be one of the determining factors in this sleep disturbance.

Disturbed dreaming and the instability of sleep: altered nonrapid eye movement sleep microstructure in individuals with frequent nightmares as revealed by the cyclic alternating pattern

STUDY OBJECTIVES

Nightmares are disturbing mental experiences during sleep that usually result in abrupt awakenings. Frequent nightmares are associated with poor subjective sleep quality, and recent polysomnographic data suggest that nightmare sufferers exhibit impaired sleep continuity during nonrapid eye movement (NREM) sleep. Because disrupted sleep might be related to abnormal arousal processes, the goal of this study was to examine polysomnographic arousal-related activities in a group of nightmare sufferers and a healthy control group.

DESIGN

Sleep microstructure analysis was carried out by scoring the cyclic alternating pattern (CAP) in NREM sleep and the arousal index in rapid eye movement (REM) sleep on the second night of the polysomnographic examination.

SETTING

Hospital-based sleep research laboratory.

PARTICIPANTS

There were 17 in the nightmare (NMs) group and 23 in the healthy control (CTLs) group.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

The NMs group exhibited reduced amounts of CAP A1 subtype and increased CAP A2 and A3 subtypes, as well as longer duration of CAP A phases in comparison with CTLs. Moreover, these differences remained significant after controlling for the confounding factors of anxious and depressive symptoms. The absolute number and frequency of REM arousals did not differ significantly between the two groups.

CONCLUSIONS

The results of our study indicate that NREM sleep microstructure is altered during nonsymptomatic nights of nightmares. Disrupted sleep in the NMs group seems to be related to abnormal arousal processes, specifically an imbalance in sleep-promoting and arousing mechanisms during sleep.

CITATION

Simor P; Bódizs R; Horváth K; Ferri R. Disturbed dreaming and the instability of sleep: altered nonrapid eye movement sleep microstructure in individuals with frequent nightmares as revealed by the cyclic alternating pattern. SLEEP 2013;36(3):413-419.

Cyclic alternating pattern (CAP): the marker of sleep instability

Cyclic alternating pattern CAP is the EEG marker of unstable sleep, a concept which is poorly appreciated among the metrics of sleep physiology. Besides, duration, depth and continuity, sleep restorative properties depend on the capacity of the brain to create periods of sustained stable sleep. This issue is not confined only to the EEG activities but reverberates upon the ongoing autonomic activity and behavioral functions, which are mutually entrained in a synchronized oscillation. CAP can be identified both in adult and children sleep and therefore represents a sensitive tool for the investigation of sleep disorders across the lifespan. The present review illustrates the story of CAP in the last 25 years, the standardized scoring criteria, the basic physiological properties and how the dimension of sleep instability has provided new insight into pathophysiolology and management of sleep disorders.

Cyclic alternating pattern in narcolepsy patients and healthy controls after partial and total sleep deprivation

OBJECTIVE

To investigate the regulation NREM sleep at baseline and in morning recovery sleep after partial and total sleep deprivation (SD) in narcolepsy-cataplexy (NC) using cyclic alternating pattern (CAP).

METHODS

Daytime sleep under either increased (no sleep in the previous night) or decreased sleep pressure (allowing 4h of sleep, 23:00-3:00 h) was recorded in ten drug-free, HLA-positive, hypocretin deficient NC patients and ten age, gender and body mass index matched healthy controls. Baseline sleep was also recorded and used for comparison purposes. CAP parameters were scored and analyzed for each subject.

RESULTS

Narcolepsy patients had significantly lower CAP rate, CAP index, CAP time, number of CAP cycles, A1 index and number of A1 cycles in comparison to healthy controls at baseline as well as after partial and total SD. In both narcolepsy patients and healthy control subjects there was a significant decrease in these parameters after partial and total SD but the changes followed a similar pattern.

CONCLUSION

The persistence of baseline differences in CAP parameters between narcolepsy patients and healthy controls and their similar behavior after partial and total SD suggests similar homeostatic NREM sleep regulation but on a different level.

SIGNIFICANCE

CAP analysis demonstrates that NREM sleep homeostasis although altered, is functional in narcolepsy patients.

Characterization of A phases during the cyclic alternating pattern of sleep

OBJECTIVE

This study aims to identify, starting from a single EEG trace, quantitative distinctive features characterizing the A phases of the Cyclic Alternating Pattern (CAP).

METHODS

The C3-A2 or C4-A1 EEG leads of the night recording of eight healthy adult subjects were used for this analysis. CAP was scored by an expert and the portions relative to NREM were selected. Nine descriptors were computed: band descriptors (low delta, high delta, theta, alpha, sigma and beta); Hjorth activity in the low delta and high delta bands; differential variance of the EEG signal. The information content of each descriptor in recognizing the A phases was evaluated through the computation of the ROC curves and the statistics sensitivity, specificity and accuracy.

RESULTS

The ROC curves show that all the descriptors have a certain significance in characterizing A phases. The average accuracy obtained by thresholding the descriptors ranges from 59.89 (sigma descriptor) to 72.44 (differential EEG variance).

CONCLUSIONS

The results show that it is possible to attribute a significant quantitative value to the information content of the descriptors.

SIGNIFICANCE

This study gives a mathematical confirm to the features of CAP generally described qualitatively, and puts the bases for the creation of automatic detection methods.

Expert opinion on pharmacotherapy of narcolepsy

IMPORTANCE TO THE FIELD

Narcolepsy is a neurodegenerative disorder resulting in the instability of the sleep-wake cycle and marked by low levels of hypocretin in cerebrospinal fluid. Sleep instability is marked by brisk, sleep-onset REM periods and sleep fragmentation, while the waking state is interrupted by the intrusion of REM sleep and sometimes accompanied by cataplectic attacks.

AREAS COVERED IN THIS REVIEW

Current pharmacologic interventions that aim to address three primary features of this disorder; excessive daytime sleepiness (EDS), cataplexy and automatic behaviors, and sleep fragmentation. We review and compare the use of traditional and new stimulants in the treatment of EDS. For the treatment of cataplexy and automatic behaviors, serotonergic and noradrenergic agents are considered. The role of gamma-hydroxybutyrate (GHB) is also explored in its ability to reduce daytime sleepiness and catapletic attacks and to consolidate sleep. Findings are based on a PubMed literature search of clinical and basic science research papers spanning 1977-2009.

WHAT THE READER WILL GAIN

A comprehensive understanding of the various existing and promising future treatments for narcolepsy. For each of these treatments, we evaluate risks versus benefits of treatment, and proposed pharmacologic mechanisms of action. We conclude with a review of new treatment approaches, including thyrotropin-releasing hormone (TRH), histamine agonists, immunotherapy and hypocretin replacement therapies.

TAKE HOME MESSAGE

Narcolepsy is an autoimmune, neurodegenerative disorder that results in significant sleep-wake instability with or without cataplectic attacks. Current treatments aim symptomatically to reconsolidate the sleep and waking states and to reduce daytime attacks of cataplexy. Future treatments aim primarily towards correcting the causal deficiency of hypocretin or preventing the autoimmune response that results in the loss of hypocretin cells.

Cyclic alternating pattern: A window into pediatric sleep

Cyclic alternating pattern (CAP) has now been studied in different age groups of normal infants and children, and it is clear that it shows dramatic changes with age. In this review we first focus on the important age-related changes of CAP from birth to peripubertal age and, subsequently, we describe the numerous studies on CAP in developmental clinical conditions such as pediatric sleep disordered breathing, disorders of arousal (sleep walking and sleep terror), pediatric narcolepsy, learning disabilities with mental retardation (fragile-X syndrome, Down syndrome, autistic spectrum disorder, Prader-Willi syndrome) or without (dyslexia, Asperger syndrome, attention-deficit/hyperactivity disorder). CAP rate is almost always decreased in these conditions with the exception of the disorders of arousal and some cases of sleep apnea. Another constant result is the reduction of A1 subtypes, probably in relationship with the degree of cognitive impairment. The analysis of CAP in pediatric sleep allows a better understanding of the underlying neurophysiological mechanisms of sleep disturbance. CAP can be considered as a window into pediatric sleep, allowing a new vision on how the sleeping brain is influenced by a specific pathology or how sleep protecting mechanisms try to counteract internal or external disturbing events.

Nocturnal aspects of narcolepsy with cataplexy

Even though the most impressive manifestation of narcolepsy is excessive sleepiness, paradoxically a significant number of patients have trouble sleeping at night. A wide array of alterations can affect the night-time sleep of a narcoleptic patient, and the aim of this review is to increase awareness on this issue, thereby enhancing the care of narcoleptic patients by more specific approaches to their disturbed night sleep. This review covers a broad variety of nocturnal sleep features in narcolepsy. Starting from animal models and the clinical features of patients, the paper then discusses the many comorbid conditions found in narcolepsy at night, the most advanced methods of analysis and the few recent advances in the specific treatment of night sleep in narcoleptic patients.

Periodic leg movements during sleep and wakefulness in narcolepsy

The objectives of the study were to measure the prevalence of periodic leg movements during NREM and REM sleep (PLMS) and while awake (PLMW) and to assess the impact of PLMS on nocturnal sleep and daytime functioning in patients with narcolepsy. One hundred and sixty-nine patients with narcolepsy and 116 normal controls matched for age and gender were included. Narcoleptics with high and low PLMS indices were compared to assess the impact of PLMS on sleep and Multiple Sleep Latency Test (MSLT) variables. More narcoleptics than controls had a PLMS index greater than 5 per hour of sleep (67% versus 37%) and an index greater than 10 (53% versus 21%). PLMS indices were higher both in NREM and REM sleep in narcoleptic patients, but the between-group difference was greater for REM sleep. A significant increase of PLMS index was also found with aging in both narcoleptic patients and controls. PLMW indices were also significantly higher in narcoleptic patients. Patients with an elevated index of PLMS had a higher percentage of stage 1 sleep, a lower percentage of REM sleep, a lower REM efficiency and a shorter MSLT latency. The present study demonstrates a high frequency of PLMS and PLMW in narcolepsy, an association between the presence of PLMS and measures of REM sleep and daytime functioning disruption. These results suggest that PLMS represent an intrinsic feature of narcolepsy.