scholarly journals 0840 Sleep Quality in Clinically Indicated In-Laboratory Polysomnography

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A320-A320
Author(s):  
R H Roth ◽  
E Harrison ◽  
H Kang ◽  
J Lobo ◽  
J Logan ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Sleep Quality ◽  
Total Sleep Time ◽  
Multivariable Analysis ◽  
Sleep Time ◽  
Apnea Hypopnea Index ◽  
Poor Sleep ◽  
Future Studies ◽  
Antidepressant Use ◽  
Male Sex

Abstract Introduction Few studies have explored how patients sleep or what characteristics might be predictive of poor sleep during clinically-indicated polysomnography (PSG) in an in-laboratory setting. Methods We reviewed clinically indicated diagnostic PSG studies completed over a 10-year period in a single academic sleep center. Total sleep time (TST) and sleep efficiency (SE) were used as proxies for sleep quality. Patients were categorized as normal or poor sleepers based on TST <4 hours or SE <50%. Multivariate linear and logistic regression analyses were performed to determine factors associated with sleep quality while controlling for demographics, medications, comorbidities and measures of sleep. Results We included 4957 patients, who were mostly female (58.9%), middle-aged (52.9 y), Caucasian (69.3%), and overweight or obese (91.3%). 3682 patients (74.2%) were diagnosed with sleep apnea (Apnea Hypopnea Index(AHI)>5/hr). Average TST was 5.75±1.43 hours (Interquartile range [IQR] = 4.94 - 6.73) and average SE was 75.1%±16.1% (IQR=66.9 - 87.2). TST and SE were lower for males compared to females (5.48 vs 5.93 hr, p<0.001; 73% vs 77%, p<0.001). In multivariable analysis, older age (TST: OR = 1.04, 95% CI:[1.03,1.05]; SE: OR = 1.04, 95% CI:[1.04,1.05]), male sex (TST: 1.38,[1.14,1.68]; SE: 1.34,[1.07,1.68]), normal body habitus (TST: 1.47,[1.02,2.08]; SE: 1.51,[1.01,2.27]) and a higher AHI (TST: 1.02,[1.02,1.03]; SE: 1.02,[1.003,1.03]) were significantly associated with being a poor sleeper for both TST and SE. Antidepressant use was associated with poor sleep for TST (0.77, [0.59,1]), but not for SE (0.98, [0.73,1.3]). Conclusion Sleep quality during the in-laboratory PSG differed by sex, age and presence of sleep apnea. Sleep quality during in-lab PSG is thought to be compromised by obtrusive monitoring and an unfamiliar environment, but average sleep quality may be higher than expected for patients in the laboratory. Future studies should consider examining in-lab sleep quality in different patient populations. Support N/A

scholarly journals 0567 Hypoxic Burden and Apnea-Hypopnea Duration in Patients with Positional Obstructive Sleep Apnea

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A217-A218
Author(s):  
J A Ramzy ◽  
R Rengan ◽  
M Mandal ◽  
S Rani ◽  
M E Vega Sanchez ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Apnea Hypopnea Index ◽  
Apnea Test ◽  
Positional Obstructive Sleep Apnea ◽  
Obstructive Sleep ◽  
Respiratory Event ◽  
The Mean

Abstract Introduction Recently, the measurement of the hypoxic burden and apnea-hypopnea duration has been shown to correlate with mortality in patients with obstructive sleep apnea (OSA). We hypothesized that in patients with mild positional OSA (apnea-hypopnea index [AHI] < 5 events/hr in the non-supine position) the hypoxic burden would be increased and apnea-hypopnea duration shortened and similar to patients with non-positional OSA. Methods Fourteen patients with positional OSA and 24 patients non-positional OSA with similar severity of OSA based on the respiratory event index (REI) were included. All patients had a home sleep apnea test for suspected OSA. The hypoxic burden was calculated by the multiplication of REI and the mean area under the desaturation curves. Results Thirty-eight patients [12 (35%) males, 50±12 yrs, BMI 35±7 kg/m2, Epworth Sleepiness Scale (ESS) 11±8, REI 10±3 events/hr, apnea-hypopnea duration 19±4 sec, mean SaO2 94±2%, lowest SaO2 79±8%, % total sleep time (TST) SaO2 < 90% 11±16%, hypoxic burden 30±17 %min/hr] completed the study. Fourteen patients [9 (64%) males, 46±14 yrs, BMI 31±6 kg/m2, ESS 7±5, REI 9±3 events/hr, mean SaO2 94±2%, lowest SaO2 81±6%, %TST SaO2 < 90% 4±6%] had positional OSA (supine REI 16±7 events/hr, non-supine REI 3±1 events/hr) and 24 patients had non-positional OSA [3 (13%) males, 52±10 yrs, BMI 38±7 kg/m2, ESS 12±9, REI 10±3 events/hr, mean SaO2 94±2%, lowest SaO2 77±9%, %TST SaO2 < 90% 14±19%]. The hypoxic burden was elevated in both the positional and non-positional OSA patients with no difference between the groups (26±19 %min/hr and 32±15 %min/hr, respectively, p=0.13). The apnea-hypopnea duration was similar in positional and non-positional OSA patients (20±3 sec and 18±4 sec, respectively, p=0.08 sec). Conclusion In patients with mild positional OSA the hypoxic burden, which has been associated with cardiovascular mortality, is elevated and similar to patients with non-positional OSA. Support None

Testing the contiguity of the sleep and fatigue relationship: a daily diary study

SLEEP ◽  
2020 ◽  
Author(s):  
Andrea L Harris ◽  
Nicole E Carmona ◽  
Taryn G Moss ◽  
Colleen E Carney
Keyword(s):  
Sleep Quality ◽  
Hierarchical Linear Modeling ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Cognitive Factors ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Daily Diary Study ◽  
Insomnia Disorder ◽  
The Relationship

Abstract Study Objectives There is mixed evidence for the relationship between poor sleep and daytime fatigue, and some have suggested that fatigue is simply caused by lack of sleep. Although retrospective measures of insomnia and fatigue tend to correlate, other studies fail to demonstrate a link between objectively disturbed sleep and fatigue. The current study prospectively explored the relationship between sleep and fatigue among those with and without insomnia disorder. Methods Participants meeting Research Diagnostic Criteria for insomnia disorder (n = 33) or normal sleepers (n = 32) completed the Consensus Sleep Diary (CSD) and daily fatigue ratings for 2 weeks. Baseline questionnaires evaluated cognitive factors including unhelpful beliefs about sleep and rumination about fatigue. Hierarchical linear modeling tested the within- and between-participant relationships between sleep quality, total sleep time, and daily fatigue ratings. Mediation analyses tested if cognitive factors mediated the relationship between insomnia and fatigue. Results Self-reported nightly sleep quality significantly predicted subsequent daily fatigue ratings. Total sleep time was a significant predictor of fatigue within, but not between, participants. Unhelpful sleep beliefs and rumination about fatigue mediated the relationship between insomnia and fatigue reporting. Conclusions The results suggest that perception of sleep plays an important role in predicting reports of daytime fatigue. These findings could be used in treatment to help shift the focus away from total sleep times, and instead, focus on challenging maladaptive sleep-related cognitions to change fatigue perception.

scholarly journals 0722 The Association Between Obstructive Sleep Apnea and Neurobehavioural Function in Men: A Large, Population-Based Cohort Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A274-A275
Author(s):  
J L Parker ◽  
R J Adams ◽  
S L Appleton ◽  
Y A Melaku ◽  
A Vakulin
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Inspection Time ◽  
Sleep Disruption ◽  
Clinical Samples ◽  
Apnea Hypopnea Index ◽  
Cross Sectional ◽  
Obstructive Sleep

Abstract Introduction Obstructive sleep apnea (OSA) is linked with impaired vigilance, attention, memory and executive function. However, this evidence largely comes from small experimental studies or larger studies in clinical samples and therefore the scope and magnitude of OSA driven neurobehavioural dysfunction in the general population remains unclear. This study aimed to examine the cross-sectional association between OSA and neurobehavioural function in a large community sample of men. Methods A total of 837 participants from the Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) study, a longitudinal cohort of men 40+ years, underwent full overnight polysomnography. Participants completed the inspection time (IT) test, mini-mental state examination (MMSE), Fuld object memory evaluation (FOME), and trail-making test (TMT) part A (TMT-A) and part B (TMT-B). Using regression models adjusted for multiple important covariates, we examined the association between neurobehavioural function scores, clinical metrics of OSA severity (Apnea-Hypopnea Index (AHI); percentage total sleep time with oxygen saturation <90% (TST90), and measures of sleep disruption (duration of rapid eye movement (REM) and non-REM (NREM) sleep; and total sleep time (TST). Results In multivariable linear regressions, greater TST was associated with worse IT scores (B=13.688, 95% CI [0.134, 27.241], P=0.048) and TMT-B scores (B=19.255, 95% CI [0.931, 37.578], P=0.040). In logistic regressions, greater TST was associated with better MMSE scores (Odds ratio [OR]=0.440, 95% CI [0.194, 0.997], P=0.049); and higher AHI was strongly associated with worse FOME scores in fully adjusted models (OR=1.358, 95% CI [1.252, 1.472], P<0.001). Conclusion The AHI and TST were positively, significantly associated with neurobehavioural function across different domains. This cross-sectional data shows that neurobehavioural function deficits in OSA are directly related to sleep and breathing disruptions. Future large prospective studies are needed to determine if OSA and sleep disruption predict future onset of neurobehavioural dysfunction and cognitive decline. Support National Health and Medical Research Council and the Adelaide Institute for Sleep Health.

scholarly journals Characteristics of Obstructive Sleep Apnea Patients With Hypertension and Factors Associated With Autotitration Acceptance

2022 ◽  
Vol 12 ◽  
Author(s):  
Xuan Zhang ◽  
Ning Zhang ◽  
Yang Yang ◽  
Shuo Wang ◽  
Ping Yu ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Eye Movement ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Apnea Hypopnea Index ◽  
Rapid Eye Movement ◽  
Obstructive Sleep ◽  
Severe Group

In order to explore the characteristics and treatment status of obstructive sleep apnea (OSA) patients with hypertension, a retrospective study was conducted on 306 patients admitted from October 2018 to December 2019. According to the apnea hypopnea index (AHI), OSA patients with hypertension were divided into three groups. 69 cases were mild OSA (5 ≤ AHI < 15), 86 cases were moderate (15 ≤ AHI < 30), and 151 cases were severe (AHI ≥ 30). Compared with patients in the mild and moderate groups, the severe group had more male patients, with higher body mass index (BMI) and non-rapid eye movement stage 1 accounted for total sleep time (N1%), and lower non-rapid eye movement stage 2 accounted for total sleep time (N2%), average and minimum blood oxygen. Among all the patients, those who underwent the titration test accounted for 20.6% (63/306). Multivariate analysis showed that sleep efficiency (p < 0.001) and AHI (p < 0.001) were independent factors for patients to accept titration test. OSA patients with hypertension had a low acceptance of titration therapy. These people with higher sleep efficiency and AHI were more likely to receive autotitration.

scholarly journals An investigation of the relationship between sleep and fatigue in those with and without insomnia

2021 ◽  
Author(s):  
Andrea L. Harris
Keyword(s):  
Sleep Quality ◽  
Linear Models ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Sleep Quantity ◽  
Cognitive Behavioural ◽  
Multi Method Approach ◽  
The Relationship

There is currently mixed evidence for the relationship between poor sleep and daytime fatigue. It is well documented that retrospective measures of insomnia and fatigue are highly correlated with one another. However, other studies fail to demonstrate a link between objectively less sleep and fatigue; that is, individuals with shorter sleep times do not necessarily report increased fatigue. As such, the relationship between these two constructs remains unclear. The current investigation will help to elucidate the complex relationship between sleep and fatigue among those with and without insomnia by advancing the existing literature in two important ways. First, this study proposed to examine the temporal relationship between sleep and fatigue across two weeks, thereby investigating whether sleep and fatigue occur in accordance with one anotherover time. Second, this study utilized a multi-method approach by collecting subjective (i.e.,sleep diary) and objective (i.e., actigraphy) measures of sleep, as well as retrospective (i.e.,visual analogue scales: VAS) and prospective (i.e., momentary ratings) measures of fatigue. Two separate hierarchical linear models were used to test whether sleep (measured by sleep quality and total sleep time) predicted daytime fatigue on the VAS and actigraph, respectively. The secondary objective asked whether cognitive-behavioural variables (i.e., maladaptive sleep beliefs, fear and avoidance of fatigue, and fatigue-based rumination) may help account for the relationship between sleep and fatigue using mediation. The results of the primary analyses suggested that sleep quality significantly predicted VAS fatigue ratings, whereas total sleep time was a significant predictor of fatigue within- but not between-persons. No significant relationships were found between objective measures of sleep and momentary fatigue ratings. Finally, each of the cognitive-behavioural variables, with the exception of avoidance of fatigue, were significant mediators of the relationship between sleep and fatigue. The results demonstrated that compared to sleep quantity, our perception of sleep may play a more important role in predicting reports of daytime fatigue. These findings could help decrease the burden that individuals with insomnia place on their total sleep times, and instead, treatment could focus on challenging maladaptive sleep-related cognitions, which ultimately could lessen the overall sleep-related anxiety.

scholarly journals Hospitalized COVID-19 Patients Were Five Times More Likely to Suffer From Total Sleep Deprivation Compared to Non-COVID-19 Patients; an Observational Comparative Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Eva S. van den Ende ◽  
Kim D. I. van Veldhuizen ◽  
Belle Toussaint ◽  
Hanneke Merten ◽  
Peter M. van de Ven ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Comparative Study ◽  
Sleep Deprivation ◽  
Total Sleep Time ◽  
Short Form ◽  
Sleep Time ◽  
Hospital Environment ◽  
Poor Sleep ◽  
Total Sleep Deprivation ◽  
Patient Reported

Objectives: Sleeping disorders are a common complaint in patients who suffer from an acute COVID-19 infection. Nonetheless, little is known about the severity of sleep disturbances in hospitalized COVID-19 patients, and whether these are caused by disease related symptoms, hospitalization, or the SARS-CoV-2 virus itself. Therefore, the aim of this study was to compare the quality and quantity of sleep in hospitalized patients with and without COVID-19, and to determine the main reasons for sleep disruption.Methods: This was an observational comparative study conducted between October 1, 2020 and February 1, 2021 at the pulmonary ward of an academic hospital in the Netherlands. This ward contained both COVID-19-positive and -negative tested patients. The sleep quality was assessed using the PROMIS-Sleep Disturbance Short Form and sleep quantity using the Consensus Sleep Diary. Patient-reported sleep disturbing factors were summarized.Results: A total of 79 COVID-19 patients (mean age 63.0, male 59.5%) and 50 non-COVID-19 patients (mean age 59.5, male 54.0%) participated in this study. A significantly larger proportion of patients with COVID-19 reported not to have slept at all (19% vs. 4% of non-COVID-19 patients, p = 0.011). The Sleep quality (PROMIS total score) and quantity (Total Sleep Time) did not significantly differ between both groups ((median PROMIS total score COVID-19; 26 [IQR 17-35], non-COVID-19; 23 [IQR 18-29], p = 0.104), (Mean Total Sleep Time COVID-19; 5 h 5 min, non-COVID-19 mean; 5 h 32 min, p = 0.405)). The most frequently reported disturbing factors by COVID-19 patients were; ‘dyspnea’, ‘concerns about the disease’, ‘anxiety’ and ‘noises of other patients, medical staff and medical devices’.Conclusion: This study showed that both patients with and without an acute COVID-19 infection experienced poor quality and quantity of sleep at the hospital. Although the mean scores did not significantly differ between groups, total sleep deprivation was reported five times more often by COVID-19 patients. With one in five COVID-19 patients reporting a complete absence of night sleep, poor sleep seems to be a serious problem. Sleep improving interventions should focus on physical and psychological comfort and noise reduction in the hospital environment.

scholarly journals Sleep in children with Smith–Magenis syndrome: a case–control actigraphy study

SLEEP ◽  
2019 ◽  
Vol 43 (4) ◽  
Author(s):  
Jayne Trickett ◽  
Chris Oliver ◽  
Mary Heald ◽  
Hayley Denyer ◽  
Andrew Surtees ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Individual Variability ◽  
Poor Sleep ◽  
Inverse Association ◽  
Linear Modeling ◽  
Hygiene Practices ◽  
And Behavior

Abstract Study Objectives The objectives of the study were (1) to compare both actigraphy and questionnaire-assessed sleep quality and timing in children with Smith–Magenis syndrome (SMS) to a chronologically age-matched typically developing (TD) group and (2) to explore associations between age, nocturnal and diurnal sleep quality, and daytime behavior. Methods Seven nights of actigraphy data were collected from 20 children with SMS (mean age 8.70; SD 2.70) and 20 TD children. Daily parent/teacher ratings of behavior and sleepiness were obtained. Mixed linear modeling was used to explore associations between total sleep time and daytime naps and behavior. Results Sleep in children with SMS was characterized by shorter total sleep time (TST), extended night waking, shorter sleep onset, more daytime naps, and earlier morning waking compared to the TD group. Considerable inter-daily and inter-individual variability in sleep quality was found in the SMS group, so caution in generalizing results is required. An expected inverse association between age and TST was found in the TD group, but no significant association was found for the SMS group. No between-group differences in sleep hygiene practices were identified. A bidirectional negative association between TST and nap duration was found for the SMS group. In the SMS group, increased afternoon sleepiness was associated with increased irritability (p = .007) and overactivity (p = .005). Conclusion These findings evidence poor sleep quality in SMS and the need to implement evidence-based interventions in this population.

Sleep disturbances in anorexia nervosa

2017 ◽  
Vol 41 (S1) ◽  
pp. S561-S561 ◽  
Author(s):  
M.F. Vieira ◽  
P. Afonso
Keyword(s):  
Anorexia Nervosa ◽  
Sleep Quality ◽  
Slow Wave ◽  
Sleep Disturbances ◽  
Negative Impact ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Falling Asleep

IntroductionIn clinical practice, insomnia is a common feature in anorexia nervosa (AN). Sleep self-reports in AN suggest that these patients report poor sleep quality and reduced total sleep time. Weight loss, starvation and malnutrition can all affect sleep. Patients with eating disorders who have sleep disturbances have more severe symptomatology.ObjectivesThe authors intend to review sleep disturbances observed in AN, describe possible pathophysiological mechanisms and evaluate the clinical impact of sleep disturbances on the treatment and prognosis of the disease.MethodsIn this study, a non-systematic search of published literature from January 1970 and August 2015 was carried out, through PubMed, using the following keywords: ‘sleep’, ‘anorexia nervosa’ and ‘insomnia’.ResultsThese patients subjectively report having poor sleep quality, with difficulty falling asleep, interrupted sleep, early morning waking or reduced total sleep time. Sleep disturbances found in AN using polysomnography are: reduction in total sleep time, decrease in slow wave sleep, slow wave activity and reduced sleep efficiency.ConclusionsPrivation of adequate and restful sleep has a negative impact on the quality of life of patients, may contribute to the appearance of comorbidities, such as depression and anxiety, and to a poor prognosis for AN.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Self-report sleep quality combined with sleep time variability distinguishes differences in fatigue, anxiety, and depression in individuals with multiple sclerosis: A secondary analysis

2018 ◽  
Vol 4 (4) ◽  
pp. 205521731881592 ◽  
Author(s):  
Catherine F Siengsukon ◽  
Mohammed Alshehri ◽  
Mayis Aldughmi
Keyword(s):  
Multiple Sclerosis ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Total Sleep Time ◽  
Secondary Analysis ◽  
Sleep Time ◽  
Anxiety And Depression ◽  
Time Variability ◽  
Poor Sleep ◽  
Poor Sleep Quality

Background Nearly 70% of individuals with multiple sclerosis report sleep disturbances or poor sleep quality. Sleep disturbances may exacerbate or complicate the management of multiple sclerosis-related symptoms. While sleep variability has been associated with several health outcomes, it is unclear how sleep variability is associated with multiple sclerosis-related symptoms. Objective The purpose of this study was to determine how total sleep time variability combined with self-reported sleep quality is associated with fatigue, depression, and anxiety in individuals with multiple sclerosis. Methods This study involved a secondary analysis of actigraphy data and questionnaires to assess sleep quality, fatigue, anxiety, and depression. Results There were significant differences between the Good Sleepers (good sleep quality/low sleep time variability; n=14) and Bad Sleepers (poor sleep quality/high sleep time variability; n=23) in overall fatigue ( p=0.003), cognitive ( p=0.002) and psychosocial fatigue ( p=0.01) subscales, and in trait anxiety ( p=0.007). There were significant differences in state ( p=0.004) and trait ( p=0.001) anxiety and depression ( p=0.002) between the Good Sleepers and Poor Reported Sleepers (poor sleep quality/low sleep time variability; n=24). Conclusion These results indicate different factors are associated with poor sleep quality in individuals with low versus high total sleep time variability. Considering the factors that are associated with sleep quality and variability may allow for better tailoring of interventions aimed at improving sleep issues or comorbid conditions.

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