Is It Time to Head Home for the Night? Home Sleep Testing in Young Children.
Ontology highlight
ABSTRACT:
SUBMITTER: Ross KR
PROVIDER: S-EPMC7640629 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
Publications
Is It Time to Head Home for the Night? Home Sleep Testing in Young Children.
Ross Kristie R KR Redline Susan S
Annals of the American Thoracic Society 20201001 10
Similar Datasets
Project description:ObjectivesExperimental studies under laboratory conditions have shown a close link between acute sleep restriction and metabolic disorders. The aim of this study was to assess the effect of a single night of moderate sleep restriction implemented under ambulatory settings on sleep organization, food intake, blood pressure, and heart rate in overweight young adults.MethodsIn a non-randomized experimental study, we evaluated 15 young, overweight adults (mean age [± SEM] 20.8 ± 0.6 y) with a mean body mass index (BMI) 27.5 ± 6.2 kg/m2 (BMI range 18.9-36.6 kg/m2). Each participant was recorded at home during two successive nights under: 1) Regular sleep routine (from 2330 to 0730 h, 'night1') and 2) Restricted sleep (6 h in bed, from 0300 to 0900 h, "night2"). Sleep was assessed by a non-invasive mobile system (Watch-PAT200) placed on the non-dominant wrist, measuring peripheral arterial tonometry. We measured sleep duration, rapid eye movement sleep (REM), light sleep (LS), deep sleep (DS), and waking. Starting 2 d before night1, four consecutive food records assessed daily food intake. Preceding and succeeding each night, hunger/satiety feelings (measured by self-reported visual analog scales), blood pressure, and heart rate were also evaluated.ResultsTotal sleep time was reduced in night2 (P = 0.007), with higher DS percentage (P = 0.03). Sleep onset and REM sleep latencies, LS time, and the number of wake episodes did not differ between nights. Energy intake was increased the day after night2 (P = 0.007), with increased fat and protein intakes (both P < 0.01) and feelings of hunger (P = 0.002). Systolic blood pressure was higher and heart rate faster in the morning after night2 (both P < 0.05).ConclusionsAn acute moderate at-home sleep restriction exacerbated food intake and feelings of hunger, and impaired blood pressure and heart rate regulation in young, overweight adults.
| S-EPMC9991999 | biostudies-literature
Project description:In human sleep studies, the probability of discomfort from the electrodes and the change in environment usually results in first-night recordings being discarded. Sleep recordings from the first night in human subjects often differ in amount of REM (rapid eye movement) sleep and the overall sleep architecture. This study investigated whether recordings of sleep states in dairy cows also show a first-night effect. Non-invasive electrophysiological recordings were carried out on nine cows of the Swedish Red breed during three consecutive 24-hour periods (recording days 1-3). Overall, cows spent 12.9 ± 1.4 hours awake, 8.2 ± 1 hours ruminating, 57.2 ± 20.3 min drowsing, 44.1 ± 20.2 min in REM sleep and 64.3 ± 38.1 min in NREM (non-rapid eye movement) sleep (mean ± SD) and there were no significant differences between recording days in total duration for any of the sleep and awake states. However, the bouts of REM sleep and rumination were longer, and the awake bouts were shorter, at night time compared to daytime, regardless of recording day. The awake bouts also showed an interaction effect with longer bouts at daytime during day 1 compared to daytime on day 3. Data on sleep and awake states recorded in adult dairy cows during three consecutive 24-h periods showed great variation in sleep time between cows, but total time for each state was not significantly affected by recording day. Further and more detailed studies of how sleep architecture is affected by recording day is necessary to fully comprehend the first-night effect in dairy cows.
| S-EPMC5898734 | biostudies-literature
Project description:Study objectivesTo explore the relationship among night-time smartphone use, sleep duration, sleep quality, and menstrual disturbances in young adult women.MethodsWomen aged 18-40 years were included in the SmartSleep Study in which they objectively tracked their smartphone use via the SmartSleep app between self-reported sleep onset and offset times (n = 764) and responded to a survey (n = 1068), which included background characteristics, sleep duration, sleep quality (Karolinska Sleep Questionnaire), and menstrual characteristics (International Federation of Gynecology and Obstetrics' definitions).ResultsThe median tracking time was four nights (interquartile range: 2-8). Higher frequency (p = .05) and longer duration (p = .02) of night-time smartphone use were associated with long sleep duration (≥9 h), but not with poor sleep quality or short sleep duration (<7 h). Short sleep duration was associated with menstrual disturbances (OR = 1.84, 95% confidence interval [CI] = 1.09 to 3.04) and irregular menstruation (OR = 2.17, 95% CI = 1.08 to 4.10), and poor sleep quality was associated with menstrual disturbances (OR = 1.43, 95% CI = 1.19 to 1.71), irregular menstruation (OR = 1.34, 95% CI = 1.04 to 1.72), prolonged bleedings (OR = 2.50, 95% CI = 1.44 to 4.43) and short-cycle duration (OR = 1.40, 95% CI = 1.06 to 1.84). Neither duration nor frequency of night-time smartphone use was associated with menstrual disturbances.ConclusionsNight-time smartphone use was associated with longer sleep duration, but not with menstrual disturbances in adult women. Short sleep duration and sleep quality were associated with menstrual disturbances. Further investigation of the effects of night-time smartphone use on sleep and female reproductive function in large prospective studies is needed.
| S-EPMC10108640 | biostudies-literature
Project description:RationaleHome sleep apnea testing (HSAT) typically does not include electroencephalogram (EEG) monitoring for sleep assessment. In patients with insomnia and low sleep efficiency, overestimation of the sleep period can result from absence of EEG, which will reduce sleep disordered breathing (SDB) indices and may lead to a false-negative result.ObjectiveTo validate a single channel frontal EEG for scoring sleep versus wake against full EEG during polysomnography, and then to examine the utility of adding this single channel EEG to standard HSAT to prevent false-negative results.MethodsEpoch-by-epoch validation for sleep scoring of single channel EEG versus full PSG was first performed in 21 subjects. This was followed by a separate retrospective analysis of 207 consecutive HSATs in adults performed in a university-affiliated sleep center using the Somte (Compumedics) HSAT with one frontal EEG as well as chin EMG, nasal airflow, oxyhemoglobin saturation, respiratory effort, pulse rate, and body position. Each study was scored twice, with (HSATEEG) and without the EEG signal visible (HSATPolygraphy), to calculate AHI4 and RDI and the effect on OSA diagnosis and severity. Analyses were repeated in 69 patients with poor sleep suggesting insomnia plus Epworth Sleepiness Scale < 7 as well as in 38 patients ultimately shown to have sleep efficiency < 70% on HSAT with EEG.Measurements and main resultsSingle channel and full EEG during polysomnography agreed on sleep versus wake in 92-95% of all epochs. HSAT without EEG overestimated the sleep period by 20% (VST = 440 ± 76 min vs TST = 356 ± 82 min), had a false-negative rate of 8% by AHI4 criteria, and underestimated disease severity in 11% of all patients. Sub-group analysis of patients with subjective poor sleep suggesting insomnia did not change the results. Patients later shown to have low sleep efficiency had lower SDB indices and a 20.8% false negative rate of sleep apnea diagnosis.ConclusionsAlthough overall false negative rates using HSATPolygraphy were moderate, suggesting utility for ruling out OSA, there was a specific subgroup in whom there were significant missed diagnoses. However, we were unable to identify this subgroup a priori.
| S-EPMC7477926 | biostudies-literature
Project description:ObjectivesApproximately 75% of women weigh more at 1-year postpartum than pre-pregnancy. More than 47% retain >10 lbs at 1-year postpartum, which is associated with adverse health outcomes for mother and child. Disturbed sleep may contribute to risk of postpartum weight retention (PWR) as short sleep duration is associated with increased risk of obesity. Thus, we investigated whether night-time sleep duration is associated with risk for excessive PWR. We also explored night-time sleep duration and change in postpartum waist circumference.MethodsThis is an ancillary analysis from a prospective cohort study. Participants were healthy primiparous adults with a singleton birth. Excessive PWR at 1-year postpartum was defined as ≥7% of pre-pregnancy weight. Log-binomial and linear regression assessed associations between night-time sleep duration at 6 months postpartum and PWR at 1-year postpartum. Linear regression assessed the association between night-time sleep duration and change in postpartum waist circumference.ResultsMean age of participants (N = 467) was 29.51 (SD ± 4.78) years. Night-time sleep duration by actigraphy or self-report was not associated with risk for excessive PWR (risk ratio 0.96, [95%CI 0.87-1.06]; risk ratio 0.95 [95%CI 0.83-1.07], respectively) or change in waist circumference.ConclusionNight-time sleep duration at 6 months postpartum was not associated with PWR at 1-year postpartum. Mixed findings among our results and previous research could be due to our focus on night-time sleep, and differences in sleep measurement methods and timeframes across studies. More comprehensively assessing sleep, including multiple sleep dimensions, may help advance our understanding of potential links between sleep and PWR.Trial registrationThe parent study, Motherhood and Pelvic Health (MAP Study), is registered at https://clinicaltrials.gov/ct2/show/NCT02512016, NCT02512016.
| S-EPMC10838128 | biostudies-literature
Project description:People with Insomnia Disorder tend to underestimate their sleep compared with polysomnography or actigraphy, a phenomenon known as paradoxical insomnia or sleep-state misperception. Previous studies suggested that night-to-night variability could be an important feature differentiating subtypes of misperception. This study aimed for a data-driven definition of misperception subtypes revealed by multiple sleep features including night-to-night variability. We assessed features describing the mean and dispersion of misperception and objective and subjective sleep duration from 7-night diary and actigraphy recordings of 181 people with Insomnia Disorder and 55 people without sleep complaints. A minimally collinear subset of features was submitted to latent class analysis for data-driven subtyping. Analysis revealed three subtypes, best discriminated by three of five selected features: an individual's shortest reported subjective sleep duration; and the mean and standard deviation of misperception. These features were on average 5.4, -0.0 and 0.5 hr in one subtype accommodating the majority of good sleepers; 4.1, -1.4 and 1.0 hr in a second subtype representing the majority of people with Insomnia Disorder; and 1.7, -2.2 and 1.5 hr in a third subtype representing a quarter of people with Insomnia Disorder and hardly any good sleepers. Subtypes did not differ on an individual's objective sleep duration mean (6.9, 7.2 and 6.9 hr) and standard deviation (0.8, 0.8 and 0.9 hr). Data-driven analysis of naturalistic sleep revealed three subtypes that markedly differed in misperception features. Future studies may include misperception subtype to investigate whether it contributes to the unexplained considerable individual variability in treatment response.
| S-EPMC7003481 | biostudies-literature
Project description:Sleep irregularity has been linked to multiple deleterious consequences in clinical populations or community adults and adolescents, but little is known about young adults. In this study, we explored the relationships between two measures of sleep regularity and a wide range of factors (lifestyle behaviors, subjective sleep, clinical outcomes, and academic performance) in a sample of female, university students in the United Arab Emirates. A total of 176 participants were recruited. Objective estimates of sleep-wake patterns were obtained using seven-day wrist actigraphy and data were used to calculate daily sleep regularity with the Sleep Regularity Index (SRI) and weekly sleep regularity with the social jetlag (SJL). Subjective sleep measures were also acquired using the Pittsburgh Sleep Quality Index (PSQI), Dysfunctional Beliefs and Attitudes about Sleep (DBAS), and daytime napping frequency. Self-reported night-time technology use frequency was ascertained using the Technology Use Questionnaire (TUQ). Psychological health was assessed using the Hospital Anxiety and Depression Scale. Objective physical health measurements for body mass index, fasting blood glucose and blood pressure were obtained. No significant associations emerged between sleep regularity and psychological physical health, or academic performance. However, significant relationships were detected between SRI and daytime napping frequency (p-value = 0.0017), PSQI (p-value = 0.0337), and DBAS (p-value = 0.0176), suggesting that daily irregular sleep patterns are associated with more frequent daytime napping, greater dysfunctional sleep beliefs, and poorer subjective sleep quality. Conversely, SJL was significantly associated with the DBAS (p-value = 0.0253), and the TUQ (p-value = 0.0208), indicating that weekly irregular sleep patterns are linked to greater dysfunctional sleep beliefs and increased nighttime technology use. In conclusion, efforts to educate and cultivate sustainable and consistent sleep-wake patterns amongst university students are needed, which can be achieved by raising awareness, promoting good sleep health habits, and minimizing excessive bedtime technology.
| S-EPMC11845451 | biostudies-literature
Project description:Study objectivesTo evaluate home sleep apnea testing (HSAT) using a type 3 portable monitor to help diagnose sleep-disordered breathing (SDB) and identify respiratory events including obstructive sleep apnea, central sleep apnea, and Cheyne-Stokes respiration in adults with stable chronic heart failure.MethodsEighty-four adults with chronic heart failure (86.9% males, age [mean ± standard deviation] 58.7 ± 16.3 years, body mass index 29.4 ± 13.0 kg/m², left ventricular ejection fraction 40.3% ± 11.5%) performed unattended HSAT followed by an in-laboratory polysomnography (PSG) with simultaneous portable monitor recording.ResultsThe apnea-hypopnea index was 22.0 ± 17.0 events/h according to HSAT, 26.8 ± 20.5 events/h on an in-laboratory portable monitor, and 23.8 ± 21.3 events/h using PSG (P = .373). A Bland-Altman analysis of the apnea-hypopnea index using HSAT vs PSG showed a mean difference (95% confidence interval) of -2.4 (-4.9 to 0.1) events/h and limits of agreement (±2 standard deviations) of -24.1 to 19.2 events/h. HSAT underestimated the apnea-hypopnea index to a greater extent at a higher apnea-hypopnea index (rho = -.358; P < .001). Similar levels of agreement from HSAT vs PSG were observed when comparing the obstructive apnea index, central apnea index, and percentage of time in a Cheyne-Stokes respiration pattern. When we used an apnea-hypopnea index ≥ 5 events/h to diagnose SDB, HSAT had 86.7% sensitivity, 76.5% specificity, 92.9% positive predictive value, and 61.9% negative predictive value compared to PSG. Detection of Cheyne-Stokes respiration using HSAT showed 94.6% sensitivity, 91.1% specificity, 88.6% positive predictive value, and 97.6% negative predictive value compared to PSG.ConclusionsHSAT with a type 3 portable monitor can help diagnose SDB and identify obstructive sleep apnea, central sleep apnea, and Cheyne-Stokes respiration events in adults with chronic heart failure.
| S-EPMC8314621 | biostudies-literature
Project description:PurposeTo determine the agreement between the manual scoring of home sleep apnea tests (HSATs) by international sleep technologists and automated scoring systems.MethodsFifteen HSATs, previously recorded using a type 3 monitor, were saved in European Data Format. The studies were scored by nine experienced technologists from the sleep centers of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC) using the locally available software. Each study was scored separately by human scorers using the nasal pressure (NP), flow derived from the NP signal (transformed NP), or respiratory inductive plethysmography (RIP) flow. The same procedure was followed using two automated scoring systems: Remlogic (RLG) and Noxturnal (NOX).ResultsThe intra-class correlation coefficients (ICCs) of the apnea-hypopnea index (AHI) scoring using the NP, transformed NP, and RIP flow were 0.96 [95% CI 0.93-0.99], 0.98 [0.96-0.99], and 0.97 [0.95-0.99], respectively. Using the NP signal, the mean differences in AHI between the average of the manual scoring and the automated systems were - 0.9 ± 3.1/h (AHIRLG vs AHIMANUAL) and - 1.3 ± 2.6/h (AHINOX vs AHIMANUAL). Using the transformed NP, the mean differences in AHI were - 1.9 ± 3.3/h (AHIRLG vs AHIMANUAL) and 1.6 ± 3.0/h (AHINOX vs AHIMANUAL). Using the RIP flow, the mean differences in AHI were - 2.7 ± 4.5/h (AHIRLG vs AHIMANUAL) and 2.3 ± 3.4/h (AHINOX vs AHIMANUAL).ConclusionsThere is very strong agreement in the scoring of the AHI for HSATs between the automated systems and experienced international technologists. Automated scoring of HSATs using commercially available software may be useful to standardize scoring in future endeavors involving international sleep centers.
| S-EPMC6615031 | biostudies-literature
Project description:Study objectivesCompare auto-adjusting positive airway pressure (APAP) treatment with positive airway pressure (PAP) titration by polysomnography (PSG) followed by CPAP treatment in patients diagnosed with obstructive sleep apnea (OSA) by home sleep apnea testing (HSAT).DesignProspective randomized treatment study.SettingTertiary Veterans Administration Medical Center.Participants156 patients diagnosed with OSA by HSAT (apneahypopnea index [AHI] ≥ 10/h) suitable for APAP treatment.InterventionsAPAP arm: Treatment with an APAP device, CPAP arm: PSG PAP titration followed by CPAP treatment.MeasurementsMean PAP adherence, Epworth sleepiness scale (ESS), Functional Outcomes of Sleep Questionnaire (FOSQ).ResultsThe mean (± SD) age, BMI, and diagnostic AHI (APAP: 28.6 ± 18.5, CPAP: 28.3 ± 16.0/h, p = NS) did not differ between the study arms. After 6 weeks of treatment, 84.6% of 78 patients started on APAP and 84.3% of 70 patients started on CPAP (8 declined treatment after the titration) were using PAP, p = NS. The 90% APAP and level of CPAP were similar (10.8 ± 3.1, 11.7 ± 2.5 cm H2O, p = 0.07). The average nightly PAP use did not differ (APAP: 4.45 ± 2.3, CPAP: 4.0 ± 2.3 h, p = NS). The improvements in the ESS (APAP: -4.2 ± 4.7, CPAP: -3.7 ± 4.8, p = NS) and in the FOSQ (APAP: 2.6 ± 3.5, CPAP: 2.2 ± 3.7, p = NS) were not different.ConclusionsFollowing diagnosis of OSA by HSAT, treatment with APAP results in equivalent PAP adherence and improvement in sleepiness compared to a PSG titration and CPAP treatment.CommentaryA commentary on this article appears in this issue on page 1277.
| S-EPMC4237517 | biostudies-literature