Case report: Diagnosis and intervention of a non-24-h sleep-wake disorder in a sighted child with a psychiatric disorder.

Circadian rhythm sleep-wake disorders (CRSWD) are sleep dysfunctions related to circadian functioning. They are characterized by symptoms of insomnia or excessive sleepiness that occur because the intrinsic circadian pacemaker is not entrained to a 24-h light/dark cycle. Affected individuals with a free-running disorder or hypernycthemeral syndrome (N24SWD) have a longer sleep-wake cycle that produces a sleep pattern that typically delays each day. The disorder is seen in 70% of blind people, and among people with healthy vision, it is a rare pathology. Among sighted cases, 80% are young men and 28% have a psychiatric disorder. The patient was a 14-year-old boy with a psychiatric pathology diagnosed with a PANDAS syndrome (pediatric autoimmune neuropsychiatric disorders associated with streptococci), a sudden acute and debilitating onset of intense anxiety and mood lability accompanied by obsessive compulsive-like issues and/or tics, in association with a streptococcal A infection that occurs immediately prior to the symptoms. As a comorbidity, he exhibited severe insomnia due to an irregular sleep pattern that strongly delayed his sleep schedule day to day. It affected his daily routines, as he was not going to school, and aggravated, furthermore, the psychiatric symptoms. He was referred for sleep consultation, where the case was explored by ambulatory circadian monitoring (ACM) using the novel system Kronowise® (Chronolab, University of Murcia) and diagnosed with a non-24-h sleep-wake disorder (N24SWD). The first treatment approach for the patient was focused on improving symptoms during the acute infection and psychiatric symptoms. Additionally, sleep pathology was treated by light therapy and melatonin. After 8 months and different trials, it was possible to establish a treatment to normalize the symptoms and fix his sleep rhythm in a normal schedule as well as to reduce anxious symptoms during the day. The association of PANDAS and N24SWD has not previously been reported in the literature.

Sleep Problems and Circadian Functioning in Children and Adolescents With Autism Spectrum Disorder.

BACKGROUND: Sleep problems are a prevalent comorbidity in autism spectrum disorder (ASD) with a multifactorial basis in which circadian misalignment has been described. METHODS: A cross-sectional study was conducted including 52 children and adolescents with ASD (9.85 ± 3.07) and 27 children and adolescent controls with normal intellectual functioning (8.81 ± 2.14). They were matched for age, sex, and body mass index, and all were drug-naïve. An ambulatory circadian monitoring device was used to record temperature and motor, body position, sleep, and light intensity. RESULTS: Individuals with ASD presented longer sleep-onset latency, lower sleep efficiency, and decreased total sleep time and tended to be more sedentary and have less exposure to light. They also showed lower amplitude, low interdaily stability, and a different pattern of wrist temperature across the day, with a midpoint of sleep that did not concur with sleep midpoint indicated by the rest of circadian parameters. CONCLUSIONS: The sleep problems observed in this sample resemble those reported previously, with the exception of nocturnal awakenings which did not show differences. The ambulatory circadian monitoring device enabled measurement of circadian parameters such as temperature which, until now, were scarcely described in children with ASD and could be used to better understand sleep and circadian system in ASD.

Application of Machine Learning Methods to Ambulatory Circadian Monitoring (ACM) for Discriminating Sleep and Circadian Disorders.

The present study proposes a classification model for the differential diagnosis of primary insomnia (PI) and delayed sleep phase disorder (DSPD), applying machine learning methods to circadian parameters obtained from ambulatory circadian monitoring (ACM). Nineteen healthy controls and 242 patients (PI = 184; DSPD = 58) were selected for a retrospective and non-interventional study from an anonymized Circadian Health Database (https://kronowizard.um.es/). ACM records wrist temperature (T), motor activity (A), body position (P), and environmental light exposure (L) rhythms during a whole week. Sleep was inferred from the integrated variable TAP (from temperature, activity, and position). Non-parametric analyses of TAP and estimated sleep yielded indexes of interdaily stability (IS), intradaily variability (IV), relative amplitude (RA), and a global circadian function index (CFI). Mid-sleep and mid-wake times were estimated from the central time of TAP-L5 (five consecutive hours of lowest values) and TAP-M10 (10 consecutive hours of maximum values), respectively. The most discriminative parameters, determined by ANOVA, Chi-squared, and information gain criteria analysis, were employed to build a decision tree, using machine learning. This model differentiated between healthy controls, DSPD and three insomnia subgroups (compatible with onset, maintenance and mild insomnia), with accuracy, sensitivity, and AUC >85%. In conclusion, circadian parameters can be reliably and objectively used to discriminate and characterize different sleep and circadian disorders, such as DSPD and OI, which are commonly confounded, and between different subtypes of PI. Our findings highlight the importance of considering circadian rhythm assessment in sleep medicine.

Blue-Enriched Light Enhances Alertness but Impairs Accurate Performance in Evening Chronotypes Driving in the Morning.

Attention maintenance is highly demanding and typically leads to vigilance decrement along time on task. Therefore, performance in tasks involving vigilance maintenance for long periods, such as driving, tends to deteriorate over time. Cognitive performance has been demonstrated to fluctuate over 24 h of the day (known as circadian oscillations), thus showing peaks and troughs depending on the time of day (leading to optimal and suboptimal times of day, respectively). Consequently, vigilance decrements are more pronounced along time on task when it is performed at suboptimal times of day. According to research, light exposure (especially blue-enriched white) enhances alertness. Thus, it has been proposed to prevent the vigilance decrement under such adverse circumstances. We aimed to explore the effects of blue-enriched white light (vs. dim light) on the performance of a simulated driving task at a suboptimal time of day. A group of evening-types was tested at 8 am, as this chronotype had previously shown their largest vigilance decrement at that time. In the dim light condition, vigilance decrements were expected on both subjective (as increments in the Karolinska Sleepiness Scale scores) and behavioral measures [as slower reaction times (RTs) in the auditory Psychomotor Vigilance Task, slower RTs to unexpected events during driving, and deteriorated driving accuracy along time on task]. Physiological activation was expected to decrease (as indexed by an increase of the distal-proximal temperature gradient, DPG). Under blue-enriched white light, all these trends should be attenuated. Results from the control dim light condition replicated the vigilance decrement in all measures. Most important, the blue-enriched white light attenuated this decrement, leading to both lower DPG and faster RTs. However, it impaired accuracy of driving performance, and did not have any effect on subjective sleepiness. We conclude that exposure to blue-enriched light provides an effective countermeasure to enhance vigilance performance at suboptimal times of day, according to measures such as RTs. However, it should be considered that alerting effects of light could impair accuracy in precision tasks as keeping a proper car position. The current findings provide ergonomic implications for safety and fatigue related management systems.

Do elite athletes sleep well? / ¿Duermen bien los deportistas de élite?

Introducción: El objetivo del estudio fue evaluar el sueño, ritmos circadianos y estado neurocognitivo de deportistas de alto rendimiento durante el periodo habitual de entrenamiento, competiciones y estudios. Materiales y métodos: Se evaluó un equipo de 12 jugadoras (mujeres, 15-17 años) de baloncesto de alto rendimiento, concentrado en una residencia de deportistas. Se estudió el sueño mediante polisomnografía, los ritmos circadianos mediante sensores de monitorización circadiana ambulatoria, y el estado neurocognitivo mediante batería de cuestionarios. Resultados: Las deportistas duermen 6:57±0,02 h, la actividad nocturna del 201,1±33,7% se sitúa por encima de la normalidad (65-135%), la regularidad de horarios, de un 72,6±9,2% también está fuera de rango normal (75-125%). La profundidad de sueño del 85,1±2,6% (valores normales entre 85-100%) es reducida, y la temperatura periférica elevada durante el día, de 33,4±0,9 ◦C (valores normales entre 31-33 ◦C) indica somnolencia. Conclusiones: Las deportistas de nuestro estudio duermen menos horas de las necesarias, la calidad del sueño es baja debido a la fatiga muscular y a unos malos hábitos, y los horarios irregulares deterioran el sistema circadiano. Todo esto influye en su rendimiento tanto físico como mental. Es básico concienciar al colectivo con todos los estamentos implicados, de la importancia de mejorar estos hábitos de sueño para mantener el rendimiento físico óptimo

Introduction: The objective of the study was to evaluate sleep, circadian rhythms and neurocognitive status of high performance athletes during the usual period of training, competitions and studies. Materials and methods: A team of 12 high-performance basketball players (women, 15-17 years old) concentrated in a sports residence was evaluated. Sleep was studied through polysomnography, circadian rhythms using ambulatory circadian monitoring sensors, and neurocognitive status using s battery of questionnaires. Results: Athletes sleep 6:57±0.02 h, nocturnal activity of 201.1±33.7% is above normal range (65-135%), regularity of schedules, 72.6±9.2% is also out of range (75-125%). The sleep depth of 85.1±2.6% (normal values between 85 and 100%) is reduced, and the peripheral temperature during the day, of 33.4±0.9 ◦C (normal values between 31 and 33 ◦C) indicates drowsiness. Conclusions: Our sample of athletes sleep less than the necessary hours, their sleep quality is low due to muscle fatigue and poor habits, and their irregular schedule deteriorates the circadian system. All of this influences both physical and mental performance. It is essential to raise awareness of the importance of improving these sleep habits in order to maintain optimum physical performance

Blue-Enriched White Light Enhances Physiological Arousal But Not Behavioral Performance during Simulated Driving at Early Night.

Vigilance usually deteriorates over prolonged driving at non-optimal times of day. Exposure to blue-enriched light has shown to enhance arousal, leading to behavioral benefits in some cognitive tasks. However, the cognitive effects of long-wavelength light have been less studied and its effects on driving performance remained to be addressed. We tested the effects of a blue-enriched white light (BWL) and a long-wavelength orange light (OL) vs. a control condition of dim light on subjective, physiological and behavioral measures at 21:45 h. Neurobehavioral tests included the Karolinska Sleepiness Scale and subjective mood scale, recording of distal-proximal temperature gradient (DPG, as index of physiological arousal), accuracy in simulated driving and reaction time in the auditory psychomotor vigilance task. The results showed that BWL decreased the DPG (reflecting enhanced arousal), while it did not improve reaction time or driving performance. Instead, blue light produced larger driving errors than OL, while performance in OL was stable along time on task. These data suggest that physiological arousal induced by light does not necessarily imply cognitive improvement. Indeed, excessive arousal might deteriorate accuracy in complex tasks requiring precision, such as driving.