0841 Aripiprazole for Treating Post-COVID-19 Hypersomnolence in Adolescents: A Case Series

Background: Sleep habits and total sleep duration are essential factors for healthy growth and development of children. There is evidence showing that eating time and quantity as well as proportion of foods macronutrients affect the sleep quality. Objectives: The aim of this study was to investigate the sleep habits of preschool children in Qazvin and the role of calorie, macronutrients and caffeine intake in a mixed normal meal on sleep induction. Materials and Methods: A total number of 210 children of 3 - 6 years old (108 boys and 102 girls) were randomly selected from a pediatric clinic in the city of Qazvin. Participants’ heights and their weights were recorded using standard techniques. Sleep habits questionnaires were filled out and three 24-hour diet-recalls for one weekend and two weekdays were assigned by a trained health worker. Results: The total night sleep duration, bedtime and wake-up time in the morning were 10.30 ± 1.30 hours, 23.30 ± 1.30 pm and 9.0 ± 1.30 am, respectively. Among all children, 21.9% had sleep onset latency and the bedtime of 56% was 10 pm or later. The results of this study showed no significant relationship between calorie, macronutrients, and caffeine intakes of the children, and the total sleep duration, bedtime, wake-up time, and sleep latency (P > 0.05). Conclusions: Based on the results of this study, no significant relationship was observed between the dietary intake and sleep habits. This might be due to the small sample size or other factors, suggested to be investigated in the future.

The aims were (1) to investigate differences by ethnicity and socioeconomic status (SES) in objective measures of sleep in children aged 7-9 years and (2) determine whether measures of sleep predict child achievement in reading or mathematics after controlling for ethnicity and SES. Four groups of parent-child dyads were recruited: Māori, low-SES schools (n = 18); Māori, high-SES schools (n = 17); New Zealand European, low-SES schools (n = 18); New Zealand European, high-SES schools (n = 17). Child sleep was measured by actigraphy. Parents and teachers reported child daytime sleepiness and behavior, and children completed a self-report of anxiety symptoms. Teachers also reported on child achievement in reading and mathematics. Children from low-SES schools went to bed later on school nights (F[1,68] = 12.150, P = .001) and woke later (F[1,68] = 15.978, P < .001) than children from high-SES schools but had similar sleep duration. There were no differences related to ethnicity. Children from low-SES schools were almost 3 times more likely to be below national standards for mathematics. Children not meeting academic standards in mathematics had a later sleep start time, lower sleep period efficiency, and a decreased total sleep time. However, when SES and sleep period efficiency were modeled together neither were found to significantly influence achievement in mathematics. In this study, SES influenced sleep timing but not the quality and quantity of sleep in 7- to 9-year-old children, and a significant independent effect of sleep efficiency on learning could not be demonstrated.

Preterm infants are babies born before completion of 37 w of gestation. Their organs are immature especially brain. Sleep has a vital role in brain development and maturation in infants. Neonatal intensive care unit is a place where infant’s comfort is disturbed by many environmental stimuli. So the sleep is disrupted. Nesting facilitates transformation of sleep pattern from erratic disturbed spells to deep peaceful nights and contented days. This study aimed to investigate the effect of nesting on sleep pattern of infants hospitalized in NICUs. This crossover clinical trial was performed at a tertiary Neonatal Intensive Care Unit (NICU). 21 preterm infants who met the inclusion criteria were enrolled. They were randomly assigned to two groups of nest and routine procedure. Sleep status was evaluated by using neonatal sleep assessment Scale. Duration of Total Sleep Time per cycle (TST) and duration of each stage such as quiet sleep, active sleep indeterminate sleep were recorded and analysed by using paired t-test. Duration of Total Sleep Time per cycle (TST) and duration of each stage were significantly higher among preterm with nesting than usual procedure of care (p<0.001). Duration of sleep time in each stages shows, duration of active sleep is significantly reduced (34.76) with nesting as compared to routine care (39.55) although which is not significant (t=1.134, P=0.270) there is significant increase in quiet sleep (63.62 ± 17.957) with nesting than with routine care and indeterminate sleep time was increased with nesting as compared with sleep in routine care which is highly significant (t=4.570, p<0.001), (t=2.297, p=0.003) at 0.05 level of significance. The present study results supports the use of nesting aids in increase sleep and duration of quiet sleep and aids in stability of physiological parameters. Thus using nesting for preterm infant is recommended to facilitate infant’s quality of sleep in NICU.

IntroductionEmotional self-regulation (ESR) skills are vital for mental and physical health. There is growing evidence linking sleep to ESR in school-aged children, but associations in toddlers remain unclear. The current study examined associations between toddlers’ sleep duration and behaviors and ESR. Materials and methodsThis study utilized baseline data from 1358 toddlers (Mage=26±3.9mo) from the Let’s Grow trial. Total sleep duration was calculated by summing parent-reported average nighttime sleep and daytime nap duration. Sleep behaviors (bedtime routine, bedtime resistance, sleep latency, and night waking) were assessed using the Children’s Sleep Habits Questionnaire and Brief Infant Questionnaire. Toddlers’ ESR skills were assessed via a 4-item parent-report scale adopted from the Fast Track Project Child Behaviour Questionnaire, with a lower score indicating better ESR. Linear regression models assessed associations of sleep duration and behaviors with ESR.ResultsToddlers’ average daily total sleep, nighttime sleep, and nap duration were 12.1h, 10.6h, and 1.5h, respectively. Girls and boys had similar nighttime sleep, total sleep, and ESR scores. However, girls had longer naps than boys (1.6h vs 1.4h, t=-3.5, p=0.0004). Total sleep, nighttime sleep, and nap duration were inversely associated with ESR (all p<0.01), indicating that higher sleep duration was associated with better ESR. Sleep behaviors were positively associated with ESR (all p<0.01), with more problem sleep behaviors associated with poorer ESR. ConclusionInitial results suggest that improving sleep duration and behaviors are associated with better ESR in toddlers. Supporting parents to improve their toddlers’ sleep may help foster better ESR skills.

Investigate whether retirement transitions are associated with changes in sleep duration and sleep timing, and whether these associations are modified by age, sex, mental health, or circadian preference. The Retirement and Sleep Trajectories (REST) study is a longitudinal study consisting of four annual mailed surveys that collected information about employment, sleep, and health. Differences in reported sleep duration, bedtime and wake time between successive surveys were calculated to estimate change over 1, 2, and 3 y. Linear regression models were used to estimate changes in these sleep parameters associated with retirement 1, 2, and 3 y posttransition. Retiring from full-time work was associated with bedtimes that were 30, 31, and 36 min later 1, 2, and 3 y postretirement; wake times that were 63, 69, and 78 min later; and sleep durations that were 15, 16, and 22 min longer 1, 2, and 3 y postretirement. These associations did not differ by sex or mental health status. Age and circadian preference modified the associations between retirement and change in sleep parameters; the increase in sleep duration was shorter and the wake time extension was lesser with advancing retirement age; those with evening preference had longer wake time extensions than those with morning preference. Transitioning to retirement is associated with longer sleep duration, later bedtimes, and later wake times. These changes were detectable about 1 y postwork transition and were persistent up to 3 y later.

Sleep duration and timing are nonlinearly associated with depressive symptoms among older adults

For clinicians involved in investigating and treating sleep disorders, understanding the accuracy of patient recall of supine sleep would allow informed comparisons between polysomnography (PSG) and patient-reported sleep in patients with supine-predominant obstructive sleep apnea. This study aims to assess the accuracy of patient perception of supine sleep. Prospective observational cohort study, assessing patient perception of total sleep and supine sleep, including duration. Data were analyzed utilizing descriptive statistics, bias-plot (Bland-Altman) analysis, and Spearman correlation (rs) to analyze relationships among continuous data. Total number of patients who underwent PSG was 518, with data from 368 of these patients analyzed. Most of these patients underwent diagnostic PSG (49.2%). Patients were excluded because of missing or incomplete data (n = 133) or immobility (n = 17). Some patients (n = 97, 26%) did not perceive supine sleep, with 34 (35% of those with unperceived supine sleep or 9% of whole group) of these having more than 60 minutes of PSG supine sleep (range 0-305.5 minutes). All "unsure" patients (n = 8, 2.2%) had significant supine sleep recorded (31.5-257.5 minutes). For the presence of any PSG supine sleep, questioning had a sensitivity of 77.9%, specificity 72.7% with positive predictive value of 96.7% and negative predictive value of 24.5%. There was a significant correlation (rs = 0.63, P < .0001) between perceived and PSG supine sleep, but wide limits of agreement (-246.9 to 194.2 minutes). In patients undergoing in-laboratory PSG, the perception of supine sleep predicts the presence of PSG supine sleep. However, questioning patients has a poor negative predictive value and patient estimates of supine sleep duration are inaccurate.

Objective: To examine if sleep timing (combination of bedtime and wake up time) is associated with energy intake and physical activity/sedentary behaviour in obese adolescents. Methods: Participants included in this cross-sectional examination were 26 (13 females) obese volunteers (BMI ≥ 95th percentile) with a mean age of 13.6 ± 0.5 years and valid data on self-reported sleep, food intake (dietary record), physical activity and sedentary time (accelerometer), screen time (self-reported), and anthropometry (BMI). We categorized participants as “late sleepers” (midpoint of sleep >3:30 a.m., n=13) and participants as “normal sleepers” (midpoint of sleep ≤ 2:30 a.m., n=13). Results: As expected, wake-up time and bedtime were different between sleep timing groups (p<0.01); however, total sleep duration was the same (9.23 ± 1.14 vs. 9.16 ± 1.28 hours for normal and late sleepers, respectively, p=0.88). There was no significant BMI difference between late sleepers and normal sleepers. Total daily caloric intake was 27% higher in late sleepers (425 kcal) compared to normal sleepers (p=0.04). Using a linear regression model in the whole sample we observed that later sleep timing was associated with greater total caloric intake, independent of age, sex, BMI, moderate-to-vigorous physical activity (MVPA) and sleep duration (β=368.6, p=0.01). No association was found between sleep timing and MVPA or sedentary time. However, later sleep timing was related to greater screen time, independent of age, sex, BMI and sleep duration (β=105.7, p<0.01). Conclusion: The present study is the first to report that later bedtime is associated with greater caloric intake and screen time in obese adolescents independent of total sleep duration.

The lifestyles change of children and adolescents during the COVID-19 pandemic due to antipandemic measures can affect their sleep health. Existing studies have used convenient samples and focused on the initial months of the pandemic, leaving a knowledge gap on changes in young people's sleep patterns under the "new normal" under COVID-19. As part of a territory-wide epidemiological study in Hong Kong, this cross-sectional study recruited primary and secondary school students by stratified random sampling. Sleep parameters were collected using the structured diagnostic interview for sleep patterns and disorders. We investigated the pandemic's effects on sleep parameters by comparing data of participants recruited pre-COVID and those recruited during COVID using multivariate regression, adjusting for age, sex, household income, seasonality, and presence of mental disorders, and the moderators and mediators of the effects. Between September 1, 2019 and June 2, 2021, 791 primary and 442 secondary school students were recruited and analyzed. Primary school and secondary school participants assessed before COVID had a longer sleep latency on school days (95% confidence interval [CI] = 1.0-5.2 minutes, adjusted P-value = .010; and 95% CI= 3.9-13.0 minutes, adjusted P-value = .004, respectively) and nonschool days (95% CI = 1.7-7.2 minutes, adjusted P-value = .005; 95% CI = 3.4-13.7 minutes, adjusted P-value = .014, respectively). Low household income was a moderator for later bedtime (adjusted P-value = .032) and later sleep onset (adjusted P-value = .043) during nonschool days among secondary school students. Changes associated with COVID have a widespread and enduring effect on the sleep health of school-aged students in Hong Kong. Household income plays a role in adolescent sleep health resilience, and the impact of antiepidemic measures on the health gaps of the youth should be considered. Chau SWH, Hussain S, Chan SSM, etal. A comparison of sleep-wake patterns among school-age children and adolescents in Hong Kong before and during the COVID-19 pandemic. J Clin Sleep Med. 2023;19(4):749-757.

Delaying the time of start of school allows for longer sleep duration, better mood, and better school performance. In South Korea, a campaign was launched in 2014 to delay the school start time to 9 a.m. We analyzed the campaign’s effects on adolescents’ total sleep duration, sleepiness (presented as weekend catch-up sleep), emotions, and school performance. Based on data from 2013, changes of sleep patterns, emotions, and academic achievement in adolescents were evaluated using the 2012–2016 Korea Youth Risk Behavior Web-based survey from two educational districts: Gyeonggi (fully participated in the delayed school start time campaign; intervention group) and Daegu/Gyeongbuk/Ulsan (DGU, never participated; control group). The primary outcomes were sleep duration, time of sleep onset, and difference in sleep duration between weekdays and the weekend. Secondary outcomes were the proportional changes of mood, stress, and school performance. The sleep duration of students in the intervention group temporarily increased in 2015. However, because there was a simultaneous delay in time of sleep onset, sleep duration returned to pre-campaign levels in 2016. Although sleep duration did not increase, weekend catch-up sleep decreased by approximately 19 minutes for students in the intervention group. Meanwhile, in the control group sleep duration tended to decrease over the same period. The impact of the campaign on students' emotions and school performance could not be confirmed. This study demonstrated that delaying the school start time to 9 a.m. reduced duration of weekend catch-up sleep with a transient increase in sleep duration in adolescents.

Sleep problems are a common consequence of multiple sclerosis; however, there is limited evidence regarding the agreement between device-measured and self-reported sleep parameters in adults with multiple sclerosis. The present study examined the agreement between self-reported and device-measured parameters of sleep quality in a sample of adults with multiple sclerosis. Participants (n = 49) completed a 7-day sleep diary and wore a wrist-worn ActiGraph GT3×+ (ActiGraph Corp., Pensecola, FL) for seven consecutive nights to quantify self-reported and device-measured sleep parameters, respectively. There was a significant discrepancy between self-reported and device-measured parameters of total time in bed (mean difference = 19.8 [51.3] min), sleep onset latency (mean difference = 22.2 [19.5] min), and frequency of awakenings during the night (mean difference = 12.8 [6.8]). Intraclass correlation estimates indicated poor agreement between methods on most parameters, except for total time in bed (intraclass correlation = 0.80). Bland-Altman plots suggested that total time in bed and total sleep time had acceptable levels of agreement and linear regression analyses indicated that sleep onset latency (F = 113.91, B = -1.34, P < .001), number of awakenings (F = 543.34, B = 1.85, P < .001), and sleep efficiency (F = 18.39, B = -0.77, P < .001) had significant proportional bias. Our results draw attention to the discrepancies between sleep parameter measurements and highlight the importance of including both self-report and device-measured outcomes for a complete and accurate representation of sleep in adults with multiple sclerosis. Cederberg KLJ, Mathison BG, Schuetz ML, Motl RW. Discrepancies between self-reported and device-measured sleep parameters in adults with multiple sclerosis. J Clin Sleep Med. 2022;18(2):415-421.

Epstein LJ, Cai A, Klerman EB, Czeisler CA. Resolving delayed sleep-wake phase disorder with a pandemic: two case reports. J Clin Sleep Med. 2022;18(1):315-318.

The main purpose of the present study was to calculate percentile curves for total sleep duration per 24 hours, for nighttime and for daytime sleep duration from early infancy to late adolescence to illustrate the developmental course and age-specific variability of these variables among subjects. A total of 493 subjects from the Zurich Longitudinal Studies were followed using structured sleep-related questionnaires at 1, 3, 6, 9, 12, 18, and 24 months after birth and then at annual intervals until 16 years of age. Gaussian percentiles for ages 3 months to 16 years were calculated for total sleep duration (time in bed) and nighttime and daytime sleep duration. The mean sleep duration for ages 1 to 16 years was estimated by generalized additive models based on the loess smoother; a cohort effect also had to be included. The standard deviation (SD) was estimated from the loess smoothed absolute residuals from the mean curve. For ages 3, 6, and 9 months, an alternative approach with a simple model linear in age was used. For age 1 month, empirical percentiles were calculated. Total sleep duration decreased from an average of 14.2 hours (SD: 1.9 hours) at 6 months of age to an average of 8.1 hours (SD: 0.8 hours) at 16 years of age. The variance showed the same declining trend: the interquartile range at 6 months after birth was 2.5 hours, whereas at 16 years of age, it was only 1.0 hours. Total sleep duration decreased across the studied cohorts (1974-1993) because of increasingly later bedtime but unchanged wake time across decades. Consolidation of nocturnal sleep occurred during the first 12 months after birth with a decreasing trend of daytime sleep. This resulted in a small increase of nighttime sleep duration by 1 year of age (mean 11.0 +/- 1.1 hours at 1 month to 11.7 +/- 1.0 hours at 1 year of age). The most prominent decline in napping habits occurred between 1.5 years of age (96.4% of all children) and 4 years of age (35.4%). Percentile curves provide valuable information on developmental course and age-specific variability of sleep duration for the health care professional who deals with sleep problems in pediatric practice.

Response

Allergic rhinitis (AR) is the most common chronic disorder in the pediatric population. Although several studies have investigated the correlation between AR and sleep-related issues, the association between the duration and time of sleep and AR has not been analyzed in long-term national data. This study investigated the relationship between sleep time and duration and AR risk in middle- and high-school students (adolescents aged 12–18). We analyzed national data from the Korea Youth Risk Behavior Web-based Survey by the Korea Centers for Disease Control and Prevention from 2007–2012. The sample size was 274,480, with an average response rate of 96.2%. Multivariate logistic regression analyses were conducted to determine the relationship between sleep and AR risk. Furthermore, to determine the best-fitted model among independent variables such as sleep duration, sleep time, and the combination of sleep duration and sleep time, we used Akaike Information Criteria (AIC) to compare models. A total of 43,337 boys and 41,665 girls reported a diagnosis of AR at baseline. The odds ratio increased with age and with higher education and economic status of the parents. Further, students in mid-sized and large cities had stronger relationships to AR than those in small cities. In both genders, AR was associated with depression and suicidal ideation. In the analysis of sleep duration and sleep time, the odds ratio increased in both genders when sleep duration was <7 hours, and when the time of sleep was later than 24∶00 hours. Our results indicate an association between sleep time and duration and AR. This study is the first to focus on the relationship between sleep duration and time and AR in national survey data collected over 6 years.