324 Naturalistic Characterization of Sleep in Chronic Insomnia Using a Non-Contact Sleep Measurement Device

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A130-A130
Author(s):  
Devon Hansen ◽  
Mary Peterson ◽  
Roy Raymann ◽  
Hans Van Dongen ◽  
Nathaniel Watson
Keyword(s):  
Sleep Onset ◽  
Contact Device ◽  
Chronic Insomnia ◽  
Poor Sleep ◽  
Measurement Device ◽  
Home Setting ◽  
Time In Bed ◽  
Sleep Measurement ◽  
Measurement Devices

Abstract Introduction Individuals with insomnia report poor sleep quality and non-restorative sleep, and often exhibit irregular sleep patterns over days and weeks. First night effects and logistical challenges make it difficult to measure these sleep characteristics in the laboratory. Also, sensitivity to sleep disruption from obtrusive measurement devices confounds sleep measurements in people with insomnia in their naturalistic setting. Non-contact sleep measurement devices have the potential to address these issues and enable ecologically valid, longitudinal characterization of sleep in individuals with insomnia. Here we use a non-contact device – the SleepScore Max (SleepScore Labs) – to assess the sleep of individuals with chronic insomnia, compared to healthy sleeper controls, in their home setting. Methods As part of a larger study, 13 individuals with chronic insomnia (ages 25-60y, 7 males) and 8 healthy sleeper controls (ages 21-46y, 6 females) participated in an at-home sleep monitoring study. Enrollment criteria included an age range of 18-65y and, for the insomnia group, ICSD-3 criteria for chronic insomnia with no other clinically relevant illness. Participants used the non-contact sleep measurement device to record their sleep periods each night for 8 weeks. Sleep measurements were analyzed for group differences in both means (characterizing sleep overall) and within-subject standard deviations (characterizing sleep variability across nights), using mixed-effects regression controlling for systematic between-subject differences. Results Based on the non-contact sleep measurements, individuals with chronic insomnia exhibited greater variability in bedtime, time in bed, total sleep time, sleep latency, total wake time across time in bed, wakefulness after sleep onset, sleep interruptions, and estimated light sleep, compared to healthy sleeper controls (all F>5.7, P<0.05). No significant differences were found for group averages and for variability in estimated deep and REM sleep. Conclusion In this group of individuals with chronic insomnia, a non-contact device used to characterize sleep naturalistically captured enhanced variability across nights in multiple aspects of sleep stereotypical of sleep disturbances in chronic insomnia, differentiating the sample statistically significantly from healthy sleeper controls. Support (if any) NIH grant KL2TR002317; research devices provided by SleepScore Labs.

scholarly journals 0127 Relationship Between Sleep Metrics with Free-Living Glucose Concentrations and Glycemic Variability in Non-Diabetic Adults

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A50-A50
Author(s):  
J R Sparks ◽  
E E Kishman ◽  
X Wang
Keyword(s):  
South Carolina ◽  
Glucose Metabolism ◽  
Sleep Onset ◽  
Glycemic Variability ◽  
Sleep Efficiency ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Free Living ◽  
Experimental Conditions ◽  
Time In Bed

Abstract Introduction Insufficient sleep and poor sleep quality have been associated with impaired glucose metabolism at fasting and under experimental conditions. Continuous glucose monitoring (CGM) measures glucose concentrations over an extended, free-living period that can be used to assess glycemic health. Relationships between CGM-assessed glucose concentrations and glycemic variability, an emerging glycemic health marker, with sleep metrics have yet to be elucidated. The purpose of this study was to examine the relationships between sleep metrics with glucose concentrations and glycemic variability in non-diabetic adults. Methods Twenty-four non-diabetic adults (age=46.0±5.8 years; BMI=32.2±5.7 kg/m2) completed actigraphy, sleep diary, and CGM over 7 consecutive days. Time-in-bed (TIB), total sleep time (TST), wake duration after sleep onset, and sleep efficiency [(TST÷TIB)×100%] were determined using actigraphy assisted with sleep diary input. Nightly variability of each sleep metric was calculated as standard deviation (SD) across all nights. Glucose concentrations at waking in the morning, and 1, 2, and 3 hours prior to waking, and diurnal, nocturnal, and 24-hour means were determined. Intra-day glycemic variability, including mean amplitude of glycemic excursions and continuous overlapping of net glycemic action of 1, 2, and 4 hours, and inter-day glycemic variability, mean of daily differences, were calculated. Pearson product correlations between sleep metrics with glucose concentrations and glycemic variability were performed. Results Average TIB and TST were 462.6±61.7 minutes and 403.3±59.7 minutes, respectively. TIB negatively correlated with glucose concentrations at 2 and 3 hours prior to waking (r=-0.42, p=0.04 and r=-0.42, p=0.04, respectively). Nightly variability in sleep efficiency positively correlated with waking, and 1, 2, and 3 hours prior to waking glucose concentrations (0.44≤r≤0.48, p≤0.03 for all). No sleep metrics correlated with glycemic variability measures (p≥0.10 for all). Conclusion Findings suggest a longer amount of sleep opportunity and more consistent sleep efficiency relate to better glucose metabolism in non-diabetic adults. Support American Heart Association 14BGIA20380706 and University of South Carolina Support to Promote Advancement of Research and Creativity Grant #11530-17-43917.

Cancer related insomnia and wireless technology: A pilot study.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e21645-e21645
Author(s):  
Brenda O'Connor ◽  
Pauline Ui Dhuibhir ◽  
Declan Walsh
Keyword(s):  
High Reliability ◽  
Objective Assessment ◽  
Sleep Onset ◽  
Work Productivity ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Time In Bed ◽  
Concurrent Use ◽  
Bedside Monitor ◽  
Delayed Sleep

e21645 Background: Cancer related insomnia (CRI) includes difficulty with sleep onset, maintenance or non-restorative sleep. CRI is common with prevalence up to 95%. Consequences include cognitive dysfunction, fatigue, increased hospitalisation and lost work productivity. Early detection may help. CRI remains under-investigated as objective assessment has needed specialised laboratories. Mobile technology may provide a solution. This study aimed to determine the feasibility and acceptability of a wireless bedside monitor (SleepMinder [ResMed Sensor Technologies Ltd, Dublin]) to evaluate CRI. Methods: A prospective observational study recruited 10 consecutive hospice inpatients (IP) and 20 consecutive community participants (CP) with cancer. Participants used a wireless non-contact bedside sleep monitor for 3 consecutive nights. Three insomnia features were examined (sleep onset, maintenance, early awakening). Computerised algorithm-generated metrics were compared to visual inspection of the monitor sleep/activity report. Acceptability questionnaires were completed by patient, nurse and family. Results: The device successfully recorded sleep patterns in all 30 participants. No technical difficulties were experienced. IP: Mean age was 63 +/- 9 years. 7/10 had one or more insomnia features with delayed sleep onset most common. The monitor over-estimated Sleep Latency (77% nights), Duration (77% nights) and Final Awakening (63% nights). CP: Mean age was 64 +/- 10 years. 15/20 had one or more insomnia features with poor sleep maintenance most common. The monitor overestimated Sleep Duration (62% nights) and Final Awakening (45% nights). Lower levels were noted in CP as they spent less time in bed. Patients, nurses and family members reported high (100%) device acceptability. Conclusions: A wireless bedside monitor effectively measured sleep in seriously ill cancer patients in both inpatient and outpatient settings without the use of a sleep laboratory High reliability and acceptability supports routine clinical use Sensitivity of wakefulness detection was reduced as the device incorrectly identified sleep during awake but motionless periods Concurrent use of sleep diary and a monitor is recommended for comprehensive assessment

scholarly journals 0519 Mindfulness Based Therapy for Insomnia Improves Objective Markers of Sleep in the Elderly: Preliminary Data from the Mindfulness Sleep Therapy (MIST) Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A198-A199
Author(s):  
K F Wong ◽  
F Perini ◽  
S L Henderson ◽  
J Teng ◽  
Z Hassirim ◽  
...  
Keyword(s):  
Preliminary Data ◽  
Repeated Measures ◽  
Mixed Model ◽  
Controlled Trial ◽  
Sleep Onset ◽  
Sleep Diary ◽  
Control Group ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Time In Bed

Abstract Introduction Mindfulness-based treatment for insomnia (MBTI) is a viable intervention for improving poor sleep. We report preliminary data from an ongoing pre-registered, randomized controlled trial which investigates the effect of MBTI on elderly adults. Methods Participants above 50 years old with PSQI ≥ 5 were recruited and randomised into either MBTI or an active control group (Sleep hygiene education and exercise program, SHEEP) in sequential cohorts with about 20 participants per cohort (10 per group). Before and after the intervention, 1 night of portable polysomnography (PSG) and 1 week of actigraphy (ACT) and sleep diary (DIARY) data were collected. We report the ACT and DIARY results of the first 3 cohorts (n = 46, male = 23, mean age = 62.3, std = 6.3) and PSG data of the first 2 cohorts (n = 29, male = 12, mean age = 62.5, std = 5.7). Time in bed (TIB), total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE) were analysed with mixed-model repeated-measures ANOVA. Results We observed increases in TIBDIARY (F1,44 = 5.151, p < .05) and SEDIARY (F1,44 = 22.633, p < .0001), and significant reductions in SOLDIARY (F1,44 = 7.031, p < .05) and WASODIARY (F1,39 = 7.411, p < .05). In the actigraphy data, we found a significant interaction in SOLACT (F1,39 = 4.273, p < .05) with an increase in SHEEP SOLACT (t18= 2.36, p < .05). Significant reductions were also observed in WASOACT (F1,44 = 16.459, p < .0001) Finally, we observed a reduction in SOLPSG (F1,26 = 5.037, p <. 05). All other tests were non-significant. Conclusion Preliminary results suggest that both interventions lead to improvements in sleep with more pronounced effects in subjective sleep reports. Objective sleep data suggest that improvements in sleep is a result of improved sleep quality and not simply extending sleep opportunity. These preliminary data shows that MBTI may be a promising intervention for elderly individuals with sleep difficulties. Support This study was supported by an award from the 7th grant call of the Singapore Millennium Foundation Research Grant Programme

N-Acetylserotonin vs Melatonin: In-Vitro Controlled Release from Hydrophilic Matrix Tablets

2019 ◽  
Vol 16 (3) ◽  
pp. 347-352 ◽  
Author(s):  
M. Vlachou ◽  
G. Stavrou ◽  
A. Siamidi ◽  
S. Flitouri ◽  
V. Ioannidou ◽  
...  
Keyword(s):  
Controlled Release ◽  
Selective Serotonin Reuptake Inhibitors ◽  
Sleep Onset ◽  
Matrix Tablets ◽  
Melatonin Receptors ◽  
Solid Matrix ◽  
Poor Sleep ◽  
Prolonged Release ◽  
Hydrophilic Matrix

Background: N-Acetylserotonin (NAS, N-acetyl-5-hydroxytryptamine) is the immediate precursor of the neurohormone melatonin (MT, N-acetyl-5-methoxytryptamine), which regulates sleep and wake cycles. NAS is produced by the N-acetylation of serotonin and is converted to melatonin via the action of Acetylserotonin O-methyltransferase (ASMT). Like melatonin, NAS acts as an agonist on the melatonin receptors MT1, MT2, and MT3. However, as NAS is abundant in specific brain areas, separate from serotonin and melatonin, it may also have discrete central effects. Indicatively, it has been reported that NAS may play a role in the antidepressant effects of Selective Serotonin Reuptake Inhibitors (SSRIs) and Monoamine Oxidase Inhibitors (MAOIs). </P><P> Objective: To decipher the controlled release characteristics of the active substances (NAS and MT) in a quick initial pace, aiming at a satisfactory sleep-onset related anti-depressive profile and prolonged release, thereafter, targeting at coping with poor sleep quality problems. </P><P> Methods: A series of hydrophilic matrix tablets involving as excipients, hydroxypropylmethylcellulose (HPMC) K15M, low viscosity sodium alginate, lactose monohydrate, and polyvinylpyrrolidone (PVP) M.W.: 10.000 and 55.000) was developed and tested at two dissolution media (pH 1.2 and 7.4). </P><P> Results: The results showed that commonly used excipients with different physicochemical properties govern the controlled release of NAS and MT from solid matrix systems. </P><P> Conclusions: We have demonstrated how broadly used excipients affect the in vitro controlled release of NAS and MT from solid pharmaceutical formulations. Currently, we extend our studies on the controlled release of these drugs using various other biopolymers/formulants of different physicochemical characteristics, which will help to highlight the discrete release profiles of NAS and MT.

scholarly journals 1142 Comprehensive Phenotyping Of Ambulatory Sleep Patterns In Multiple Sclerosis

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A435-A435
Author(s):  
T J Braley ◽  
A L Kratz ◽  
D Whibley ◽  
C Goldstein
Keyword(s):  
Multiple Sclerosis ◽  
Sleep Quality ◽  
Extreme Values ◽  
Sleep Onset ◽  
External Support ◽  
Poor Sleep ◽  
Sleep Patterns ◽  
Poor Sleep Quality ◽  
Historical Cohort ◽  
The Impact

Abstract Introduction The majority of sleep research in persons with multiple sclerosis (PwMS) has been siloed, restricted to evaluation of one or a few sleep measures in isolation. To fully characterize the impact of sleep disturbances in MS, multifaceted phenotyping of sleep is required. The objective of this study was to more comprehensively quantify sleep in PwMS, using a recently developed multi-domain framework of duration, continuity, regularity, sleepiness/alertness, and quality. Methods Data were derived from a parent study that examined associations between actigraphy and polysomnography-based measures of sleep and cognitive function in MS. Actigraphy was recorded in n=55 PwMS for 7-12 days (Actiwatch2®, Philips Respironics). Sleep metrics included: duration=mean total sleep time (TST, minutes); continuity=mean wake time after sleep onset (minutes), and regularity=stddev wake-up time (hours). ‘Extreme’ values for continuity/regularity were defined as the most extreme third of the distributions. ‘Extreme’ TST values were defined as the lowest or highest sixth of the distributions. Sleepiness (Epworth Sleepiness Scale score) and sleep quality [Pittsburgh Sleep Quality Index (PSQI) sleep quality item] were dichotomized by accepted cutoffs (&gt;10 and &gt;1, respectively). Results Sleep was recorded for a mean of 8.2 days (stddev=0.95). Median (1st, 3rd quartile) values were as follows: duration 459.79 (430.75, 490.60), continuity 37.00 (23.44, 52.57), regularity 1.02 (0.75, 1.32), sleepiness/alertness 8 (4, 12), and sleep quality 1.00 (1.00, 2.00). Extreme values based on data distributions were: short sleep &lt;=426.25 minutes (18%), long sleep &gt;515.5 minutes (16%), poor sleep continuity ≥45 minutes (33%), and poor sleep regularity ≥1.17 hours (33%). Sleepiness and poor sleep quality were present in 36% and 40% respectively. For comparison, in a historical cohort of non-MS patients, the extreme third of sleep regularity was a stddev of 0.75 hours, 13% had ESS of &gt;10, and 16% had poor sleep quality. Conclusion In this study of ambulatory sleep patterns in PwMS, we found greater irregularity of sleep-wake timing, and higher prevalence of sleepiness and poor sleep quality than published normative data. Efforts should be made to include these measures in the assessment of sleep-related contributions to MS outcomes. Support The authors received no external support for this work.

scholarly journals The Cycle of Daily Stress and Sleep: Sleep Measurement Matters

2020 ◽  
Author(s):  
Danica C Slavish ◽  
Justin Asbee ◽  
Kirti Veeramachaneni ◽  
Brett A Messman ◽  
Bella Scott ◽  
...  
Keyword(s):  
Sleep Disturbances ◽  
Multilevel Models ◽  
Single Channel ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Diary ◽  
Sleep Onset Latency ◽  
Daily Stress ◽  
Sleep Diaries ◽  
Sleep Measurement

Abstract Background Disturbed sleep can be a cause and a consequence of elevated stress. Yet intensive longitudinal studies have revealed that sleep assessed via diaries and actigraphy is inconsistently associated with daily stress. Purpose We expanded this research by examining daily associations between sleep and stress using a threefold approach to assess sleep: sleep diaries, actigraphy, and ambulatory single-channel electroencephalography (EEG). Methods Participants were 80 adults (mean age = 32.65 years, 63% female) who completed 7 days of stressor and sleep assessments. Multilevel models were used to examine bidirectional associations between occurrence and severity of daily stress with diary-, actigraphy-, and EEG-determined sleep parameters (e.g., total sleep time [TST], sleep efficiency, and sleep onset latency, and wake after sleep onset [WASO]). Results Participants reported at least one stressor 37% of days. Days with a stressor were associated with a 14.4-min reduction in actigraphy-determined TST (β = −0.24, p = 0.030), but not with other actigraphy, diary, or EEG sleep measures. Nights with greater sleep diary-determined WASO were associated with greater next-day stressor severity (β = 0.01, p = 0.026); no other diary, actigraphy, or EEG sleep measures were associated with next-day stressor occurrence or severity. Conclusions Daily stress and sleep disturbances occurred in a bidirectional fashion, though specific results varied by sleep measurement technique and sleep parameter. Together, our results highlight that the type of sleep measurement matters for examining associations with daily stress. We urge future researchers to treat sleep diaries, actigraphy, and EEG as complementary—not redundant—sleep measurement approaches.

778 Poor Sleep Quality is Associated with Reduced Myelination in Patients with Psychotic Disorders

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A303-A303
Author(s):  
Cagri Yuksel ◽  
Xi Chen ◽  
Lauren Watford ◽  
Margaret Gardner ◽  
Kathryn Lewandowski ◽  
...  
Keyword(s):  
White Matter ◽  
Sleep Quality ◽  
Psychotic Disorders ◽  
Sleep Onset ◽  
Sleep Loss ◽  
Magnetization Transfer Ratio ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Healthy Controls ◽  
Poor Sleep Quality

Abstract Introduction Recent studies show that sleep favors oligodendrocyte proliferation and myelination, and sleep loss is associated with alterations in white matter structure and decreased myelination. Psychotic disorders are characterized by disrupted white matter integrity, and abnormal axon and myelin structure. Despite common sleep disturbances in these disorders, little is known about the relationship between sleep quality and white matter findings. A novel in vivo neuroimaging technique that combines diffusion tensor spectroscopy (DTS) and magnetization transfer ratio (MTR) allows separately examining the axon structure and glial function, and myelin content, respectively. Using this method, we examined the association of sleep quality with white matter biology in a sample of patients with psychotic disorders and matched healthy controls. Methods Participants included patients diagnosed with bipolar disorder with psychotic features (euthymic or depressed, n=12) and schizophrenia spectrum disorders (n=9), and age and sex matched healthy controls (n=20). DTS and MTR data was collected from the right prefrontal white matter at 4T. DTS measures included apparent diffusion coefficients of water, NAA, creatine and choline. Sleep quality was measured using Pittsburgh Sleep Quality Index (PSQI). Results PSQI total score was significantly higher in patients. and patient sample included a higher percentage of poor sleepers (PSQI total score&gt;5). In patients, total PSQI score and sleep onset latency were significantly and negatively associated with MTR (F=6.9, p=0.02 and F=9.7, p=0.007, respectively). There was no difference in any DTS measures between groups. Conclusion Our preliminary results show that poor sleep quality is associated with decreased myelin content in the frontal lobe, in patients with psychotic disorders. This finding suggests that sleep loss may be a mediator of white matter alterations in psychosis. Support (if any) This work is supported by National Institute of Mental Health K23MH119322 to Cagri Yuksel

818 A Ghost from the Past: Unmasked Insomnia Affecting Hypoglossal Nerve Stimulation Therapy Adherence

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A319-A320
Author(s):  
Elena Stuewe ◽  
Aarti Grover ◽  
Peter Ostrow ◽  
Greg Schumaker ◽  
Joel Oster ◽  
...  
Keyword(s):  
Nerve Stimulation ◽  
Hypoglossal Nerve ◽  
Sleep Onset ◽  
Chronic Insomnia ◽  
Apnea Hypopnea Index ◽  
Therapy Adherence ◽  
Hypoglossal Nerve Stimulation ◽  
Obstructive Sleep ◽  
Patient Reported ◽  
History Of

Abstract Introduction Hypoglossal nerve stimulation (HNS) is an efficacious option for treating moderate to severe obstructive sleep apnea (OSA). However, there is sparse evidence regarding tolerance and adherence to HNS therapy in patients with a diagnosis of insomnia. Report of case(s) A 57-year-old man with well-controlled depression presented for evaluation for HNS therapy. He had been diagnosed with moderate OSA with an apnea-hypopnea index of 22/hour, intolerant of continuous positive airway pressure and mandibular advancement device. He underwent uvulopalatopharyngoplasty without significant improvement. At the time of initial evaluation, he denied history of insomnia and prior sleep aid use. He subsequently underwent successful HNS device implantation and activation. One week after HNS initiation, the patient reported new symptoms of significant difficulty with sleep onset and inability to fall back asleep, which was worse than his untreated OSA symptoms. Device interrogation did not reveal any hardware problems. Adjustments to start delay, pause time and device configuration with awake endoscopy did not improve tolerance. Subsequently, the patient disclosed a remote history of insomnia, which was treated with multiple hypnotics in addition to cognitive-behavioral therapy for insomnia (CBTi) and had resolved. He was diagnosed with recurrent chronic insomnia, for which eszopiclone was initiated without significant improvement. He eventually agreed to CBTi, with partial improvement in device tolerance and improvement in insomnia symptoms. Conclusion This case highlights that HNS therapy adherence can be affected by prior history of, or a current diagnosis of insomnia. Our patient had a predisposition for insomnia that was well controlled prior to HNS therapy initiation. The onset of recurrent insomnia with HNS activation suggests that HNS was a precipitating factor for his now chronic insomnia. Although there is insufficient evidence to suggest whether history of insomnia should affect the decision to initiate HNS therapy, this case illustrates the importance of screening for insomnia at pre-implant evaluation. Our center is now routinely screening for a history of insomnia to identify patients who may benefit from treatment prior to HNS implantation. Larger studies are needed to explore a possible relationship between insomnia and HNS adherence. Support (if any):

142 Prenatal Sleep Quality and Infant Sleep: A Longitudinal Study

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A58-A59
Author(s):  
Rebecca Burdayron ◽  
Marie-Helene Pennestri ◽  
Elizabeth Keys ◽  
Lianne Tomfohr-Madsen ◽  
Gerald Giesbrecht
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Gestational Age ◽  
Sleep Onset ◽  
Depression Scale ◽  
Future Research ◽  
Poor Sleep ◽  
Infant Sleep ◽  
Maternal Sleep ◽  
Sleep Parameters

Abstract Introduction Poor sleep quality is common during pregnancy and can increase the risk of adverse obstetric and fetal outcomes. Existing research on the association between prenatal sleep and infant sleep is scarce and has focused on other aspects of prenatal sleep such as sleep duration, chronotype, and insomnia symptoms. To our knowledge, no studies have examined the association between prenatal sleep quality and infant sleep outcomes. Thus, this study aimed to investigate whether maternal sleep quality during pregnancy was prospectively associated with infant sleep dimensions, independent of relevant covariates. Methods Participants were a subset of 272 mother-infant dyads enrolled in an ongoing cohort study. Maternal prenatal sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI) in early to mid- (M gestational age = 15.12 ± 3.56 weeks) and late- (M gestational age = 32.44 ± 0.99 weeks) pregnancy. Mothers completed the Brief Infant Sleep Questionnaire (BISQ) at 3, 6, and 12 months postpartum. The following infant sleep parameters were assessed: sleep duration (day, night, 24-hour), number of night awakenings, and wake after sleep onset. Prenatal depressive symptoms were assessed with the Edinburgh Postnatal Depression Scale (EPDS) at both pregnancy time points. Other covariates included maternal age at enrollment, infant age, parity, and co-sleeping status. Results Generalized estimating equations (GEE) models revealed that poorer maternal sleep quality during early-to-mid pregnancy did not significantly predict infant sleep parameters after adjustment for covariates (p &gt; .05). However, in late pregnancy, poorer maternal sleep quality significantly predicted shorter 24-hour sleep duration and longer wake after sleep onset, but not daytime sleep duration, nighttime sleep duration, and number of night awakenings (p &lt; .05). Conclusion Study findings advance our understanding of the prospective link between maternal prenatal sleep quality and infant sleep. Results indicate that maternal sleep quality during late gestation may play a role in the development of infant sleep patterns. These findings have important implications for intervention efforts targeting maternal sleep quality during pregnancy. Future research should use objective measures of sleep, such as actigraphy, to better elucidate the effects of prenatal sleep quality on infant sleep outcomes. Support (if any) The Canadian Institutes of Health Research (CIHR)

507 Clinical Impression of Excessive Daytime Sleepiness (EDS) at initial Sleep Medicine (SM) consultation and its clinical correlates

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A199-A200
Author(s):  
Leon Rosenthal ◽  
Raúl Aguilar Roblero
Keyword(s):  
Lower Energy ◽  
Energy Levels ◽  
Sleep Onset ◽  
Sleep Time ◽  
Clinical Impression ◽  
Sleep Onset Latency ◽  
Convenience Sample ◽  
Time In Bed ◽  
Number Of Patients ◽  
Cardinal Symptom

Abstract Introduction EDS represents a cardinal symptom in SM. Use of subjective scales are prevalent, which have a modest correlation with the MSLT. While the Clinical Global Impression has been used in research, reports of clinical impression (CI) in medical practice are lacking. We report on the CI of EDS in a convenience sample of patients undergoing initial consultation. Methods Patients reported primary, secondary symptoms and completed the Sleep Wake Activity Inventory (SWAI) prior to Tele-Medicine consultation. A SM physician completed the assessment which included ascertainment of CI of EDS (presence S+ / absence S-). Results There were 39 ♂and 13 ♀. The CI identified 26 patients in each group (S+/S-). Age (52 [14]), BMI (33 [7]), reported time in bed, sleep time, sleep onset latency and # of awakenings did not differ. All identified a primary symptom (S-: 21, S+: 19 reported snoring or a previous Dx of OSA). Sleepiness as a 1ry or 2ry symptom was identified by 0 in the S- and by 13 in the S+ groups. Refreshing quality of sleep differed (χ2 &lt;0.05): un-refreshing sleep was reported by 7 (S-) and by 13 (S+). Naps/week: 0.7 [1.5] and 1.57 [1.5] for the S-, S+ groups respectively (p&lt;0.05). A main effect (p&lt;0.01) was documented on the SWAI. We report on the Sleepiness [SS] and Energy Level [EL] scales (lower scores on the SS reflect higher sleepiness while lower scores on EL denote higher energy). Higher sleepiness (p&lt;0.01) 43 [12] and lower energy levels 24 [6] (p&lt;0.05) were documented on the S+ group (S- 61 [17], and 18 [6] respectively). Available spouse’s Epworth score on 29 patients: S- patients 5.8 [4] and S+ 10.2 [6] (p&lt;0.05). Dx of OSA was identified among all but 1 in the S+ group. Also, Insomnia was diagnosed among 11 (S-) and 19 (S+) patients (p&lt;0.05) despite only 3 and 7 (respectively) identifying it as a presenting symptom. Conclusion While snoring or previous Dx of OSA were prevalent motivations for consultation, sleepiness and insomnia were clinically relevant among a substantial number of patients. Unrefreshing sleep, daytime naps, lower energy, and higher sleepiness were ubiquitous among S+ patients. Support (if any):

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