A randomized, double-blind, placebo-controlled, multicenter, 28-day, polysomnographic study of gabapentin in transient insomnia induced by sleep phase advance.
ABSTRACT: To evaluate multiple doses of gabapentin 250 mg on polysomnography (PSG) and participant-reported sleep assessments in a 5-h phase advance insomnia model.Adults reporting occasional disturbed sleep received gabapentin 250 mg (n = 128) or placebo (n = 128). On Days 1 and 28, participants received medication 30 min before bedtime and were in bed from 17:00 to 01:00, ?5 h before their habitual bedtime. Sleep was assessed by PSG, a post sleep questionnaire, and the Karolinska Sleep Diary. Next-day residual effects and tolerability were evaluated. On Days 2-27, participants took medication at home 30 min before their habitual bedtime.Treatment-group demographics were comparable. Gabapentin resulted in significantly less PSG wake after sleep onset (WASO) compared with placebo on Day 1 (primary endpoint, mean: 107.0 versus 149.1 min, p ? 0.001) and Day 28 (113.6 versus 152.3 min, p = 0.002), and significantly greater total sleep time (TST; Day 1: 347.6 versus 283.9 min; Day 28: 335.3 versus 289.1 min) (p ? 0.001). Participant-reported WASO and TST also showed significant treatment effects on both days. Gabapentin was associated with less %stage1 on Day 1, and greater %REM on Day 28, versus placebo. During home use, gabapentin resulted in significantly less participant-reported WASO and higher ratings of sleep quality. Gabapentin was well tolerated (most common adverse events: headache, somnolence) with no evidence of next-day impairment.Gabapentin 250 mg resulted in greater PSG and participant-reported sleep duration following a 5-h phase advance on Day 1 and Day 28 of use without evidence of next-day impairment, and greater sleep duration during at-home use.
Project description:To evaluate the effects of single doses of gabapentin 250 and 500 mg on polysomnographic (PSG) and participant-reported sleep measures in a 5-h phase advance insomnia model.Adults reporting occasional disturbed sleep received gabapentin 500 mg (n = 125), 250 mg (n = 125), or placebo (n = 127) 30 min prior to bedtime and were in bed from 17:00 to 01:00, ?5 h before their habitual bedtime. Sleep was assessed by PSG, post-sleep questionnaire, and the Karolinska Sleep Diary (KSD). Next-day residual effects (Digit Symbol Substitution Test [DSST] and Stanford Sleepiness Scale [SSS]) and tolerability were assessed.Demographics were comparable among groups. Among PSG endpoints, wake after sleep onset (primary endpoint) (135.7 [placebo], 100.7 [250 mg], and 73.2 [500 mg] min) was significantly lower and total sleep time (TST) (311.4, 356.5, and 378.7 min) significantly greater in both gabapentin groups versus placebo. Latency to persistent sleep was not significantly different among groups. Percent slow wave sleep (12.6%, 15.4%, and 17.0%, respectively) was significantly greater and percent stage 1 (15.1%, 11.8%, and 10.8%, respectively) significantly lower relative to placebo. Gabapentin was associated with significantly higher values of KSD Sleep Quality Index and reported TST versus placebo; no other reported outcomes were significant. Neither gabapentin dose produced evidence of next-day residual effects as measured by DSST and SSS. Adverse events were infrequent (< 5%).Participants with occasional disturbed sleep treated with gabapentin showed significantly longer sleep duration and greater depth (versus placebo) in response to a phase advance manipulation known to disrupt sleep maintenance.
Project description:We validated actigraphy for detecting sleep and wakefulness versus polysomnography (PSG).Actigraphy and polysomnography were simultaneously collected during sleep laboratory admissions. All studies involved 8.5 h time in bed, except for sleep restriction studies. Epochs (30-sec; n = 232,849) were characterized for sensitivity (actigraphy = sleep when PSG = sleep), specificity (actigraphy = wake when PSG = wake), and accuracy (total proportion correct); the amount of wakefulness after sleep onset (WASO) was also assessed. A generalized estimating equation (GEE) model included age, gender, insomnia diagnosis, and daytime/nighttime sleep timing factors.Controlled sleep laboratory conditions.Young and older adults, healthy or chronic primary insomniac (PI) patients, and daytime sleep of 23 night-workers (n = 77, age 35.0 ± 12.5, 30F, mean nights = 3.2).N/A.Overall, sensitivity (0.965) and accuracy (0.863) were high, whereas specificity (0.329) was low; each was only slightly modified by gender, insomnia, day/night sleep timing (magnitude of change < 0.04). Increasing age slightly reduced specificity. Mean WASO/night was 49.1 min by PSG compared to 36.8 min/night by actigraphy (? = 0.81; CI = 0.42, 1.21), unbiased when WASO < 30 min/night, and overestimated when WASO > 30 min/night.This validation quantifies strengths and weaknesses of actigraphy as a tool measuring sleep in clinical and population studies. Overall, the participant-specific accuracy is relatively high, and for most participants, above 80%. We validate this finding across multiple nights and a variety of adults across much of the young to midlife years, in both men and women, in those with and without insomnia, and in 77 participants. We conclude that actigraphy is overall a useful and valid means for estimating total sleep time and wakefulness after sleep onset in field and workplace studies, with some limitations in specificity.
Project description:Objectives: Our count-scaled algorithm automatically scores sleep across 24 hours to process sleep timing, quantity, and quality. The aim of this study was to validate the algorithm against overnight PSG in children to determine the best site placement for sleep. Methods: 28 children (5-8 years) with no history of sleep disturbance wore two types of accelerometers (ActiGraph GT3X+ and Actical) at two sites (left hip, non-dominant wrist) for 24-h. Data were processed using the count-scaled algorithm. PSG data were collected using an in-home Type 2 device. PSG-actigraphy epoch sensitivity (sleep agreement) and specificity (wake agreement) were determined and sleep outcomes compared for timing (onset and offset), quantity [sleep period time (SPT) and total sleep time (TST)], and quality metrics [sleep efficiency and waking after sleep onset (WASO)]. Results: Overall, sensitivities were high (89.1% to 99.5%) and specificities low (21.1% to 45.7%). Sleep offset was accurately measured by actigraphy, regardless of brand or placement site. By contrast, sleep onset agreed with PSG using hip-positioned but not wrist-positioned devices (difference ActiGraph : PSG 21 min, P < .001; Actical : PSG 14 min, P < .001). The ActiGraph at the wrist accurately detected WASO and sleep efficiency, but under (-34 min, P < .001) and overestimated (5.8%, P < .001) these at the hip. The Actical under- and over-estimated these variables respectively at both sites. Results for TST varied ranging from significant differences to PSG of -26 to 21 min (ActiGraph wrist and hip respectively) and 9 min (ns) to 59 min for Actical (wrist and hip respectively). Conclusion: Overall the count-scaled algorithm produced high sensitivity at the expense of low specificity in comparison with PSG. A best site placement for estimates of all sleep variables could not be determined, but overall the results suggested ActiGraph GT3X+ at the hip may be superior for sleep timing and quantity metrics, whereas the wrist may be superior for sleep quality metrics. Both devices placed at the hip performed well for sleep timing but not for sleep quality. Differences are likely linked to freedom of movement of the wrist vs the trunk (hip) during overnight sleep.
Project description:The "first-night effect" of polysomnography (PSG) has been previously studied; however, the ability to quantify the sleep disruption level has been confounded with the use of PSG on all nights. We used actigraphy to quantify disruption level and examined characteristics associated with disruption.Totally, 778 older men (76.2 ± 5.4 years) from a population-based study at six US centers underwent one night of in-home PSG. Actigraphy was performed on the PSG night and three subsequent nights. Actigraphically measured total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), and sleep onset latency (SOL) from the PSG night and subsequent nights were compared. Linear regression models were used to examine the association of characteristics and sleep disruption.On average, sleep on the PSG night was worse than the following night (p < 0.05, TST 21 ± 85 min less, SE 2.3 ± 11.3% less, WASO 4.9 ± 51.8 min more, SOL 6.6 ± 56.2 min more). Sleep on the PSG night was significantly worse than that two and three nights later. Characteristics associated with greater sleep disruption on the PSG night included older age, higher apnea-hypopnea index, worse neuromuscular function, and more depressive symptoms. Minorities and men with excessive daytime sleepiness slept somewhat better on the PSG night.Among older men, there was sleep disruption on the PSG night, which may lead to sleep time underestimation. The increase of sleep on the night after the PSG suggests that data from the second monitoring may overestimate sleep.
Project description:Actigraphy (ACT) is a non-invasive objective assessment tool for the study of sleep-wake rhythms. It is of particular interest in children with autism spectrum disorder (ASD), as sleep disorders are highly prevalent and have a significant impact on both cognitive and behavioral functions. As polysomnography (PSG), the gold standard for the assessment of sleep, is difficult to perform in children with ASD, ACT has become a tool of choice but has not yet been validated against PSG using state-of-the-art methodology. The main objective of this study was to assess, for the first time, the validity of ACT compared to PSG for the measurement of sleep in children with ASD. During the same night of hospitalization, PSG and ACT were conducted in 26 children (6 girls and 20 boys; mean age 5.4 years ± 1.6) diagnosed with ASD according to DSM-5 criteria and standardized diagnostic scales. Sleep parameters were total sleep time (TST), sleep latency (SL), wake after sleep onset (WASO), and sleep efficiency (SE). To compare PSG and ACT, we conducted sleep parameter agreement analyses including: intraclass correlation coefficient (ICC), Bland-Altman plots, and equivalence tests. The comparison also included an epoch-by-epoch (EBE) agreement analysis to determine sensitivity (ability to detect sleep) and specificity (ability to detect wake). According to equivalence tests, the difference between ACT and PSG measures was clinically acceptable for TST (<30 min, p < 0.01), SL (<15 min, p < 0.001), and SE (10%, p < 0.01), but not for WASO (<15 min, p = 0.13). There was a good agreement between methods for SL (ICC = 0.79) and TST (ICC = 0.85) and a moderate agreement for WASO (ICC = 0.73) and SE (ICC = 0.68). The EBE agreement analysis revealed a high sensitivity (0.94 ± 0.06) and moderate specificity (0.5 ± 0.2). Since sleep disorders are one of the most common comorbidities within the ASD population and are highly prevalent, it is essential to validate objective tools of assessment. To our knowledge, our study is the first to validate ACT compared to PSG, using a state-of-the-art methodology, in children with ASD. The results suggest ACT to be a valid method to evaluate sleep within this population, with a good reliability for most sleep parameters.
Project description:Few commercially available brands of actigraphs (ACT) have been subjected to rigorous validation with infant participants. The purpose of this study was to examine the agreement between concurrent polysomnography (PSG) and one brand of ACT (AW-64, Mitter Co. Inc.) using appropriate statistical techniques among a sample of healthy infants.Twenty-two healthy infants (14.1+/-0.6 months) had one night of ankle ACT recording during research PSG at Kosair Children's Hospital Sleep Research Center in Louisville, Kentucky. Macroanalyses were conducted using the Bland-Altman concordance technique to assess agreement between total sleep time (TST) and wake after sleep onset (WASO) simultaneously measured by PSG and ACT, using two ACT algorithm settings. Microanalyses were also calculated to examine sensitivity, specificity, and accuracy of ACT within each PSG-identified sleep state. Correlations were calculated between PSG-identified arousals and the discrepancies between ACT and PSG.The Bland-Altman concordance technique revealed that ACT underestimated TST by 72.25 (SD=61.48) minutes and by > or = 60 min among 54.55% of infants. Furthermore, ACT overestimated WASO by 13.85 (SD=30.94) minutes and by > or = 30 min among 40.91% of infants. Sensitivity, specificity, and accuracy analyses revealed that ACT adequately identified sleep, but poorly identified wake. PSG and ACT discrepancies were positively associated with PSG-identified arousals (r=.45).Improved device and/or software development is needed before the AW-64 can be considered a valid method for identifying infant sleep and wake.
Project description:STUDY OBJECTIVES:To compare the quality and consistency in sleep measurement of a consumer wearable device and a research-grade actigraph with polysomnography (PSG) in adolescents. METHODS:Fifty-eight healthy adolescents (aged 15-19 years; 30 males) underwent overnight PSG while wearing both a Fitbit Alta HR and a Philips Respironics Actiwatch 2 (AW2) for 5 nights, with either 5 hours or 6.5 hours time in bed (TIB) and for 4 nights with 9 hours TIB. AW2 data were evaluated using two different wake and immobility thresholds. Discrepancies in estimated total sleep time (TST) and wake after sleep onset (WASO) between devices and PSG, as well as epoch-by-epoch agreements in sleep/wake classification, were assessed. Fitbit-generated sleep staging was compared to PSG. RESULTS:Fitbit and AW2 under default settings similarly underestimated TST and overestimated WASO (TST: medium setting (M10) ? 38 minutes, Fitbit ? 47 minutes; WASO: M10 ? 38 minutes; Fitbit ? 42 minutes). AW2 at the high motion threshold setting provided readings closest to PSG (TST: ? 12 minutes; WASO: ? 18 minutes). Sensitivity for detecting sleep was ? 90% for both wearable devices and further improved to 95% by using the high threshold (H5) setting for the AW2 (0.95). Wake detection specificity was highest in Fitbit (? 0.88), followed by the AW2 at M10 (? 0.80) and H5 thresholds (? 0.73). In addition, Fitbit inconsistently estimated stage N1 + N2 sleep depending on TIB, underestimated stage N3 sleep (21-46 min), but was comparable to PSG for rapid eye movement sleep. Fitbit sensitivity values for the detection of N1 + N2, N3 and rapid eye movement sleep were ? 0.68, ? 0.50, and ? 0.72, respectively. CONCLUSIONS:A consumer-grade wearable device can measure sleep duration as well as a research actigraph. However, sleep staging would benefit from further refinement before these methods can be reliably used for adolescents. CLINICAL TRIAL REGISTRATION:Registry: ClinicalTrials.gov; Title: The Cognitive and Metabolic Effects of Sleep Restriction in Adolescents; Identifier: NCT03333512; URL: https://clinicaltrials.gov/ct2/show/NCT03333512. CITATION:Lee XK, Chee NIYN, Ong JL, Teo TB, van Rijn E, Lo JC, Chee MWL. Validation of a consumer sleep wearable device with actigraphy and polysomnography in adolescents across sleep opportunity manipulations. J Clin Sleep Med. 2019;15(9):1337-1346.
Project description:The menopausal transition is marked by increased prevalence in disturbed sleep and insomnia, present in 40-60% of women, but evidence for a physiological basis for their sleep complaints is lacking. We aimed to quantify sleep disturbance and the underlying contribution of objective hot flashes in 72 women (age range: 43-57 years) who had (38 women), compared to those who had not (34 women), developed clinical insomnia in association with the menopausal transition. Sleep quality was assessed with two weeks of sleep diaries and one laboratory polysomnographic (PSG) recording. In multiple regression models controlling for menopausal transition stage, menstrual cycle phase, depression symptoms, and presence of objective hot flashes, a diagnosis of insomnia predicted PSG-measured total sleep time (p < 0.01), sleep efficiency (p = 0.01) and wakefulness after sleep onset (WASO) (p = 0.01). Women with insomnia had, on average, 43.5 min less PSG-measured sleep time (p < 0.001). There was little evidence of cortical EEG hyperarousal in insomniacs apart from elevated beta EEG power during REM sleep. Estradiol and follicle stimulating hormone levels were unrelated to beta EEG power but were associated with the frequency of hot flashes. Insomniacs were more likely to have physiological hot flashes, and the presence of hot flashes predicted the number of PSG-awakenings per hour of sleep (p = 0.03). From diaries, women with insomnia reported more WASO (p = 0.002), more night-to-night variability in WASO (p < 0.002) and more hot flashes (p = 0.012) compared with controls. Women who develop insomnia in the approach to menopause have a measurable sleep deficit, with almost 50% of the sample having less than 6h of sleep. Compromised sleep that develops in the context of the menopausal transition should be addressed, taking into account unique aspects of menopause like hot flashes, to avoid the known negative health consequences associated with insufficient sleep and insomnia in midlife women.
Project description:Wrist actigraphy (ACT) may overestimate sleep and underestimate wake, and the agreement may be lower in people with chronic conditions who often have poor sleep and low activity levels. The purpose of this systematic review is to compare the agreement between ACT and polysomnographic (PSG) measures of sleep in adults without chronic conditions and sleep complaints (healthy) and with chronic conditions. We conducted a systematic review and meta-analysis using PRISMA guidelines. We searched PubMed, OVIDEMBASE, OVIDMEDLINE, OVIDPsycINFO, CENTRAL, CINAHL, ClinicalTrials.gov, International Clinical Trials Registry, and Open Grey. We included 96 studies with a total of 4134 participants, of whom 762 (18.4) were healthy adults and 724 (17.5%) were adults with chronic conditions. Among adults with chronic conditions, ACT overestimated TST, compared to PSG [M = 22.42 min (CI 95%: 11.92, 32.91 min)] and SE [M = 5.21% (CI 95%: 1.41%-9.00%)]. ACT underestimated SOL [M = -7.70 min (CI 95%: -15.22, -0.18 min)], and WASO [M = -10.90 min (CI 95%: -26.01, 4.22 min)]. These differences were consistently larger between ACT and PSG sleep measures compared to healthy adults. Research is needed to better understand factors that influence the agreement between ACT and PSG among people with chronic conditions.
Project description:BACKGROUND:People with multiple sclerosis (MS) often report poor sleep, fatigue, sleepiness, depression and cognitive dysfunction. Interrelationships between symptoms and sleep are poorly understood. OBJECTIVES:To document objective parameters of sleep measured by polysomnography (PSG) and multi-sleep latency tests (MSLTs) in patients experiencing fatigue or sleepiness and to determine whether they correlate with symptoms. METHODS:Thirty-two MS patients, not on therapy, with fatigue or sleepiness completed the Modified Fatigue Impact Scale, Fatigue Severity Scale, Epworth Sleepiness Scale, Beck Depression Index and NeuroTrax cognitive tests and underwent PSG and MSLTs. RESULTS:Sleep efficiency (SE) averaged 75.1%. wake after sleep onset (WASO), sleep onset latency and multi-sleep latency were 66.2, 43.4 and 10.43?min, respectively. Stage N3 and rapid eye movement sleep were absent in 10 and four patients, respectively. Increased limb movements were observed in eight patients. Obstructive sleep apnea was observed in 12 patients. Neither SE nor WASO correlated with fatigue or sleepiness. SE correlated with the global cognitive score and with executive function and information processing subscales. CONCLUSIONS:Overall, 30/32 MS patients reporting fatigue or sleepiness had evidence of one or more sleep disturbances. PSG should be considered in MS patients reporting fatigue or sleepiness in order to rule out treatable disturbances.