Objective Sleep Metrics Research Articles

305 Subjective sleep predicts Cadet performance during U.S. Army Reserve Officer Training Corps Advanced Camp

Abstract Introduction U.S. Army Reserve Officer Training Corps (ROTC) Advanced Camp (AC) is a 29-day training that assesses military skills and leadership potential in college students training to become Commissioned Officers (i.e. Cadets). Military trainings are widely known to disrupt normative sleep. Additionally, operational sleep disruption is linked to performance decrements. This study examined the ability for objective and subjective sleep during ROTC AC to predict Cadet performance. Methods One hundred and fifty-nine ROTC Cadets (age 22.06±2.49 years; 76.1% male) wore an actiwatch device continuously for 29 days during AC. Paper surveys administered at the end of AC captured subjective sleep metrics during the training. ROTC instructors evaluated Cadet performance and provided scores of overall class rank and summary performance. Multiple and ordinal linear regressions assessed the predicative utility of subjective (sleep duration [SD]; Global score [Global] from the Pittsburgh Sleep Quality Index) and objective (Total Sleep Time [TST]; Sleep Efficiency [SE]; Sleep Latency Onset [SOL]; Wake After Sleep Onset [WASO] from actigraphy) sleep on performance. Results The interaction of SD and Global, when controlling for age and gender, significantly predicted increased Cadet rank, F(4,153) = 3.09, p = 0.018. Models testing the prediction of SD and Global on summary performance score were non-significant. Further, regressing of both Cadet rank and summary performance individually on objective sleep metrics, when controlling for age and gender, resulted in non-significant findings. Conclusion Subjective and objective sleep showed no significant individual predictive utility on performance. However, the combined subjective model significantly predicted that Cadets who slept worse (lower SD; higher Global) during AC received a lower rank at the end of the training. These findings suggest there may be a unique combined predictive utility of subjective sleep on performance when compared to the predictive power of individual variables. Therefore, subjective sleep may be better for predicting operational performance than objective sleep. Future analyses will refine these models and examine how performance on individual AC events may be influenced by sleep. Support for this study came from the Military Operational Medicine Research Program (MOMRP) of the United States Army Medical Research and Development Command (USAMRDC). Support (if any):

Does Poor Sleep Quality Predict Functional Limitations?

Previous work from our group (Friedman, 2016) linked sleep complaints to declines in mobility and risk of incident limitations over a 9-10 year follow-up among middle-aged and older adults. While these results suggest that poor sleep might undermine functional capacity, the self-report nature of the data leaves the robustness of this association unclear. The current study addressed this uncertainty by examining links between sleep and mobility limitations using subjective and objective assessments of both. Data were from the Midlife in the United States (MIDUS) study: the biomarker sub-sample (N = 664) from the original cohort (collected 2004-2006) and the Refresher cohort (collected 2011-2013). Sleep was assessed using the Pittsburgh Sleep Quality Index (PSQI; subjective) and 7 consecutive days of actigraphy (objective). Functional capacity was assessed by self-report of limitations and measured gait speed, grip strength, and chair stands. In linear regression models adjusting for demographic and health factors, lower PSQI scores (better sleep quality) predicted fewer reported limitations, stronger grip, quicker gait, and faster chair stands (all p<.01). Of the objective sleep metrics, time to fall asleep and time spent awake during the night predicted more self-report limitations, weaker grip (latency only), and slower gait speed and chair stands. These results extend our prior work by showing a) subjective sleep is linked to measured as well as self-reported physical function, and b) objective assessments of sleep predict reduced physical function, albeit to a lesser extent. They also brighten the spotlight on sleep as a key health determinant in older adults.

Rhinologic disease and its impact on sleep: a systematic review.

Rhinologic disease can be responsible for systemic symptoms affecting mood, cognition, and sleep. It is unclear whether sleep disturbance in specific rhinologic disorders (chronic rhinosinusitis [CRS], rhinitis, and nasal septal deviation [NSD]) is an obstructive phenomenon or due to other mechanisms. In this review we examine the impact of CRS, rhinitis, and NSD on objective and subjective sleep outcome metrics and draw comparisons to normal controls and patients with known obstructive sleep apnea (OSA). A systematic review of 4 databases (PubMed, Scopus, Cochrane Library, and Web of Science) was performed. Studies reporting on objective (apnea-hypopnea index [AHI], respiratory disturbance index [RDI], oxygen nadir) and subjective (Epworth Sleepiness Scale [EpSS], Pittsburgh Sleep Quality Index [PSQI], Fatigue Severity Scale [FSS]) sleep parameters and disease-specific patient-reported outcome measures (PROMs; 22-item Sino-Nasal Outcome Test [SNOT-22], Rhinoconjunctivitis Quality of Life Questionnaire [RQLQ], Nasal Obstruction Symptom Evaluation [NOSE]) were included. The database search yielded 1414 unique articles, of which 103 were included for analysis. Baseline PROMs were at the high end of normal to abnormal for all 3 conditions: EpSS: CRS (9.8 ± 4.0), rhinitis (9.7 ± 4.3), and NSD (8.9 ± 4.6); and PSQI: CRS (11.0 ± 4.5), rhinitis (6.1 ± 3.7), and NSD (8.6 ± 3.5). Objective measures demonstrated a mild to moderate OSA in the studied diseases: AHI: CRS (10.4 ± 11.5), rhinitis (8.6 ± 8.8), and NSD (13.0 ± 6.9). There were significant differences when compared with reported norms in all measured outcomes (p < 0.001). Sleep quality is impacted by rhinologic (CRS, rhinitis, NSD) disease. There is likely a mild obstructive component contributing to poor sleep, but other contributing factors may be involved.

Macro and micro sleep architecture and cognitive performance in older adults.

We sought to determine which facets of sleep neurophysiology were most strongly linked to cognitive performance in 3,819 older adults from two independent cohorts, using whole-night electroencephalography. From over 150 objective sleep metrics, we identified 23 that predicted cognitive performance, and processing speed in particular, with effects that were broadly independent of gross changes in sleep quality and quantity. These metrics included rapid eye movement duration, features of the electroencephalography power spectra derived from multivariate analysis, and spindle and slow oscillation morphology and coupling. These metrics were further embedded within broader associative networks linking sleep with aging and cardiometabolic disease: individuals who, compared with similarly aged peers, had better cognitive performance tended to have profiles of sleep metrics more often seen in younger, healthier individuals. Taken together, our results point to multiple facets of sleep neurophysiology that track coherently with underlying, age-dependent determinants of cognitive and physical health trajectories in older adults.

Objectively measured sleep–wake patterns in patients with drug-resistant epilepsy – Interaction with quality of life and antiepileptic treatment

RationalePatients with epilepsy experience frequent episodes of fragmented sleep which may contribute to chronic sleep loss. Enhancing sleep patterns might lead to improved quality of life in these patients. Currently, unlike some other antiepileptic drugs (AEDs), there are no data on the effects of clobazam, a novel AED on sleep. Therefore, we tested the hypothesis that patients with epilepsy will have longer, more consolidated sleep after treatment with clobazam. MethodsIn this prospective study, we included adults with drug-resistant epilepsy who were being considered for treatment with clobazam. Patients with known untreated moderate/severe sleep apnea or with major circadian rhythm disorders were excluded. We tested a set of the following subjective sleep measures: Pittsburgh Sleep Quality Inventory (PSQI), Epworth Sleepiness Scale (ESS), Karolinska Sleepiness Scale (KSS), Insomnia Severity Index (ISI), and Quality of Life in Epilepsy (QOLIE) prior to starting the treatment, as well as after achieving a stable clobazam dose. We also measured sleep pattern using wrist actigraphy – before starting therapy and after achieving stable dose. ResultsA total of 12 participants completed all parts of the study. After treatment, a lower number of awakenings and less wake after sleep onset (WASO) were seen, as well as a lower number of seizures. Average pretreatment bedtime was 23:45, and average wake time was 8:24. A higher seizure frequency significantly correlated with all subjective sleep measures, as well as with a higher amount actigraphy measured WASO and less total sleep time (TST) measured both by sleep log and by actigraphy. Those with higher baseline WASO by actigraphy also had more depressive symptoms, worse quality of life, longer duration of epilepsy, and a higher seizure frequency. ConclusionBoth objective and subjective sleep metrics correlate with depressive symptoms and quality of life. After treatment, there were fewer awakenings as well as fewer seizures.

Association Between Free-living Weekday 24-hour Urinary Hydration Markers And Weekend Sleep Measures

PURPOSE: Inadequate sleep and underhydration have been independently associated with adverse health outcomes. However, the relation between hydration status and sleep has yet to be investigated over the course of several days in young adults. Thus, the purpose of this study was to assess the association between 24h urinary hydration markers and both perceived and objective sleep quality. METHODS: Eighteen participants (female, n=7; age, 23±3; height, 174.6±15.3cm; body mass, 73.5±15.9kg; body fat, 19.4± 9.4%) provided a 24h urine sample on seven consecutive days for measures of urine volume (UVOL), urine osmolality (UOSMO), urine specific gravity (USG) and urine color (UCOL). Objective sleep metrics (wrist-worn actigraphy) and subjective sleep assessments (Karolinska Sleep Diary) were recorded each day. Actigraph measures included periods of wakefulness after defined sleep onset (WASO), sleep time, wake time, and sleep efficiency. The Karolinska Sleep Diary included nine questions used to assess perceived sleep quality from the previous night. Mean values were calculated for each participant for all variables on weekdays (Monday-Friday) and weekend days (Saturday/Sunday). RESULTS: Higher weekday USG and darker UCOL were both associated with greater weekend time spent sleeping (USG, adj R2 = 0.203, p = 0.024; UCOL, adj R2 = 0.274, p = 0.015). Decreased weekday UVOL was associated with increased weekend time spent sleeping (adj R2 = 0.220, p = 0.028). Higher weekday UOSMO was associated with greater weekend WASO actigraph measures (adj R2 = 0.205, p = 0.045). CONCLUSIONS: Mean 24-hour urinary hydration markers depicting a state of underhydration (elevated USG and reduced UVOL) across weekdays were associated with an increased number of awakenings during the weekend nights, albeit, having a longer sleep time. Determining how day-to-day variations in hydration status and other general health behaviors influence sleep has yet to be explained.

0134 Self-Reported Sleep is Associated with Central, But Not Peripheral Blood Pressure Values in Healthy Children

Abstract Introduction Shortened and poor quality sleep have emerged as nontraditional risk factors for the development of high blood pressure (BP) in adults, but it is unclear if these relations exist in younger children. Self-report and objective sleep measurements are both clinically relevant and may inform interventions to improve sleep in this population, but do not always coincide with one another. The purpose of this study was to evaluate both self-reported and objective sleep metrics and their associations with central and peripheral BP values in younger children. Methods Participants included 21 healthy 7-12-year-old children (10±0.5 yrs, 10M/11F). Self-reported sleep was evaluated using the Children’s Sleep Health Questionnaire and a total sleep score was generated, where a higher score indicates worse sleep (a score &amp;gt;41 indicates a pediatric sleep disorder). Objective sleep was recorded for 7 consecutive days and nights outside of the laboratory via wrist accelerometry and reported as sleep duration (SD) and sleep efficiency (SE). Following sleep monitoring, peripheral BP was measured and using pulse wave analysis (PWA) central BP was estimated, both of which were averaged over 3 trials. Pearson’s r correlations were used to assess relations between self-reported sleep score, objective sleep metrics, and BP values. Significance was set at p&amp;lt;0.05. Results Self-reported sleep score averaged 40±1 points, objective SD averaged 7.9±0.1 hours/night, and SE averaged 82±2%. Sleep score was significantly associated with central systolic and diastolic BP (r = .485, p = 0.03, and r = .517, p = 0.02, respectively), but not peripheral BP values. Objective SD and SE were not significantly associated with central or peripheral BP values. Conclusion In this sample, self-reported sleep score, but not objective sleep metrics, was associated with higher central BP values in healthy children age 7–12. Support Provided in part by P20GM113125.

Effects of probiotics and paraprobiotics on subjective and objective sleep metrics: a systematic review and meta-analysis.

Inadequate sleep (i.e., duration and/or quality) is becoming increasingly recognized as a global public health issue. Interaction via the gut-brain axis suggests that modification of the gut microbial environment via supplementation with live microorganisms (probiotics) or nonviable microorganisms/microbial cell fractions (paraprobiotics) may improve sleep health. This systematic review and meta-analysis aimed to clarify the effect of consuming probiotics/paraprobiotics on subjective and objective sleep metrics. Online databases were searched from 1980 to October 2019 for studies involving adults who consumed probiotics or paraprobiotics in controlled trials, during which, changes in subjective and/or objective sleep parameters were examined. A total of 14 studies (20 trials) were included in meta-analysis. Random effects meta-analyses indicated that probiotics/paraprobiotics supplementation significantly reduced Pittsburgh Sleep Quality Index (PSQI) score (i.e., improved sleep quality) relative to baseline (-0.78-points, 95% confidence interval: 0.395-1.166; p < 0.001). No significant effect was found for changes on other subjective sleep scales, nor objective parameters of sleep (efficiency/latency) measured using polysomnography or actigraphy. Subgroup analysis for PSQI data suggested that the magnitude of the effect was greater (although not statistically) in healthy participants than those with a medical condition, when treatment contained a single (rather than multiple) strain of probiotic bacteria, and when the duration of treatment was ≥8 weeks. Probiotics/paraprobiotics supplementation may have some efficacy in improving perceived sleep health, measured using the PSQI. While current evidence does not support a benefit of consuming probiotics/paraprobiotics when measured by other subjective sleep scales, nor objective measures of sleep; more studies using well-controlled, within-subject experimental designs are needed.

Abstract P548: Poorer Objective Sleep is Associated With Greater Arterial Stiffness and Worsening Cardiac Diastolic Function

Aim: Few studies have examined the association between objective sleep metrics and arterial and echocardiographic (left ventricular systolic/diastolic function) markers of sub-clinical cardiovascular disease (CVD). The present study examined the association of wrist actigraphy-assessed sleep metrics with arterial stiffness, endothelial dysfunction, and left ventricular systolic/diastolic function. Methods: Fifteen young, healthy adults (21-39y; 60% women) with no history of CVD, and no current sleep-disordered breathing (WatchPat200, Itamar Medical) or sleep complaints wore Actiwatch Spectrum Plus actigraphs for eight nights (Philips Respironics, Bend OR) with accompanying sleep logs. Participants underwent fasting vascular testing including central augmented aortic pressure (AP), carotid-femoral pulse wave velocity (cfPWV) to assess arterial stiffness (SphymocorXCEL TM ), brachial artery flow mediated dilation (FMD) to assess endothelial function, and 2D echocardiography to assess left ventricular function (Terason uSmart 3300 TM ). Left ventricular function was assessed by ejection fraction (EF%), left atrial volume index (LAVI), deceleration time (DT), and mitral valve E/e’ ratio (MVE/e’) using standardized methods. Bivariate correlations investigating the association between mean total sleep time (TST), sleep efficiency % (SE), sleep-onset latency (SOL), and wake after sleep time (WASO) with cardiovascular indices were conducted. Curvilinear regression models examining quadratic relationships between TST and the cardiovascular indices were conducted. Results: On average, participants obtained 6 hrs 44 min of TST (SD=29.1), with 86.0% SE (SD=3.1), 10.6 min SOL (SD=8.5), and 37.0 min WASO (SD=11.6). cfPWV (range: 4.8-7.5), EF% (range: 60.0-72.0), LAVI (range: 15.0-26.7 mL/m 2 ), and MVE/e’ (range: 3.2-7.8) were all within normal ranges according to age and sex normative standards. Mean FMD was 9.2% (SD=4.62, range: 4.3-19.8). Correlations indicated that greater SOL was associated with greater cfPWV (r=.63, p=0.01), and AP (r=.57, p=0.03). Lower SE (r= -.70, p=0.003) and higher WASO (r=.71, p=0.003) were associated with higher MVE/e’. WASO was associated with higher DT (r=.57, p=0.04). Curvilinear regression models revealed a quadratic relationship between TST and cfPWV (F[2,11]=9.78, p=0.004) such that shorter and longer TST were associated with greater cfPWV. No sleep metrics were associated with FMD, EF%, or LAVI. Conclusions: Among normal sleeping, apparently healthy young adults, with no history of CVD, lower levels of objective sleep quality and both shorter and longer sleep duration were associated with greater arterial stiffness, whereas only lower levels of objective sleep quality were related to worsening left ventricular diastolic dysfunction. These data may have implications for CVD risk reduction in young, healthy adults.

Examination of Sleep and Injury Among College Football Athletes.

Burke, TM, Lisman, PJ, Maguire, K, Skeiky, L, Choynowski, JJ, CapaldiII, VF, Wilder, JN, Brager, AJ, and Dobrosielski, DA. Examination of sleep and injury among college football athletes. J Strength Cond Res 34(3): 609-616, 2020-The purpose of this study was to characterize subjective sleep metrics in collegiate football players at the start of the season, determine the relationship between preseason subjective sleep measures and in-season objective sleep characteristics, and examine the association between subjective and objective sleep metrics and incidence of time-loss injury during the competitive season. Ninety-four Division I football players completed 5 validated sleep-related questionnaires to assess sleep quality, insomnia severity, daytime sleepiness, sleep apnea risk, and circadian preference before the start of the season. Clinical thresholds for sleep questionnaires were used to determine risk of sleep disorders. Continuous wrist actigraphy was collected throughout the season to generalize sleep behaviors. Time-loss injury incidence data were recorded and used for analysis. Results indicated that 67.4% (60 of 89) of athletes scored above clinical threshold in at least 1 questionnaire to indicate sleep disorder risk. At the start of the season, players subjectively reported an average sleep duration of 7:16 ± 1:18 hours:minutes, which was in contrast to the 6:04 ± 0:41 hours:minutes measured through actigraphy during the season. Logistic regression models adjusted for age and body mass index revealed no significant associations between injury and subjective (odds ratio [OR] = 1.00; 95% confidence interval [CI] = 0.99-1.01) and objective (OR = 1.01; 95% CI = 0.99-1.02) sleep duration or measures attained from sleep questionnaires (ORs ranged from 1.01 to 2.87). Sleep metrics (quantity and quality) were not associated with increased risk of injury in this cohort of collegiate football players.

Personality Traits and the Subjective and Objective Experience of Sleep.

There is growing evidence that five-factor model personality traits are associated with self-reported sleep. We test whether these associations extend to objective sleep measures in older adulthood and whether measures of objective sleep mediate the relation between personality and subjective sleep. A random subsample of participants in the National Social Life and Aging Project (NSHAP) wore an accelerometer for up to three nights and had information on FFM personality traits (N = 620). Participants also reported on their feelings of being rested. Higher neuroticism and lower extraversion and conscientiousness were associated with more frequent wake after sleep onset, greater fragmentation, and feeling less rested. Concurrent body mass index, disease burden, perceived stress, and depressive symptoms accounted for these associations. Personality was unrelated to total time spent asleep but conscientiousness was associated with earlier and more consistent bedtimes. None of the objective sleep metrics mediated the relation between personality and subjective sleep. The present research indicates that the associations typically found for personality and subjective sleep extend to objective sleep fragmentation. These objective measures, however, do not account for the relation between personality and feeling rested.

Accelerating Research With Technology: Rapid Recruitment for a Large-Scale Web-Based Sleep Study.

BackgroundParticipant recruitment can be a significant bottleneck in carrying out research studies. Connected health and mobile health platforms allow for the development of Web-based studies that can offer improvement in this domain. Sleep is of vital importance to the mental and physical health of all individuals, yet is understudied on a large scale or beyond the focus of sleep disorders. For this reason and owing to the availability of digital sleep tracking tools, sleep is well suited to being studied in a Web-based environment.ObjectiveThe aim of this study was to investigate a method for speeding up the recruitment process and maximizing participant engagement using a novel approach, the Achievement Studies platform (Evidation Health, Inc, San Mateo, CA, USA), while carrying out a study that examined the relationship between participant sleep and daytime function.MethodsParticipants could access the Web-based study platform at any time from any computer or Web-enabled device to complete study procedures and track study progress. Achievement community members were invited to the study and assessed for eligibility. Eligible participants completed an electronic informed consent process to enroll in the study and were subsequently invited to complete an electronic baseline questionnaire. Then, they were asked to connect a wearable device account through their study dashboard, which shared their device data with the research team. The data were used to provide objective sleep and activity metrics for the study. Participants who completed the baseline questionnaires were subsequently sent a daily single-item Sleepiness Checker activity for 7 consecutive days at baseline and every 3 months thereafter for 1 year.ResultsOverall, 1156 participants enrolled in the study within a 5-day recruitment window. In the 1st hour, the enrollment rate was 6.6 participants per minute (394 per hour). In the first 24 hours, the enrollment rate was 0.8 participants per minute (47 participants per hour). Overall, 1132 participants completed the baseline questionnaires (1132/1156, 97.9%) and 1047 participants completed the initial Sleepiness Checker activity (1047/1156, 90.6%). Furthermore, 1000 participants provided activity-specific wearable data (1000/1156, 86.5%) and 982 provided sleep-specific wearable data (982/1156, 84.9%).ConclusionsThe Achievement Studies platform allowed for rapid recruitment and high study engagement (survey completion and device data sharing). This approach to carrying out research appears promising. However, conducting research in this way requires that participants have internet access and own and use a wearable device. As such, our sample may not be representative of the general population.

Improved Mental Acuity Forecasting with an Individualized Quantitative Sleep Model

Sleep impairment significantly alters human brain structure and cognitive function, but available evidence suggests that adults in developed nations are sleeping less. A growing body of research has sought to use sleep to forecast cognitive performance by modeling the relationship between the two, but has generally focused on vigilance rather than other cognitive constructs affected by sleep, such as reaction time, executive function, and working memory. Previous modeling efforts have also utilized subjective, self-reported sleep durations and were restricted to laboratory environments. In the current effort, we addressed these limitations by employing wearable systems and mobile applications to gather objective sleep information, assess multi-construct cognitive performance, and model/predict changes to mental acuity. Thirty participants were recruited for participation in the study, which lasted 1 week. Using the Fitbit Charge HR and a mobile version of the automated neuropsychological assessment metric called CogGauge, we gathered a series of features and utilized the unified model of performance to predict mental acuity based on sleep records. Our results suggest that individuals poorly rate their sleep duration, supporting the need for objective sleep metrics to model circadian changes to mental acuity. Participant compliance in using the wearable throughout the week and responding to the CogGauge assessments was 80%. Specific biases were identified in temporal metrics across mobile devices and operating systems and were excluded from the mental acuity metric development. Individualized prediction of mental acuity consistently outperformed group modeling. This effort indicates the feasibility of creating an individualized, mobile assessment and prediction of mental acuity, compatible with the majority of current mobile devices.

Sleep apnea in patients reporting insomnia or restless legs symptoms.

Insomnia and restless legs syndrome (RLS) are defined by self-reported symptoms, and polysomnography (PSG) is not routinely indicated. Occult obstructive sleep apnea (OSA), common even in asymptomatic adults, may complicate management of patients presenting with insomnia or restless legs. To this end, we investigated objective sleep apnea metrics in a large retrospective cohort according to self-reported symptom profiles. We compared sleep apnea findings in patients referred to our center according to self-reported symptoms associated with insomnia, sleep apnea, and restless legs. The cohort included over 1900 adults who underwent diagnostic (n = 1418) or split-night (n = 504) PSGs and completed a symptom and medical history questionnaire. More than 30% of patients who did not endorse any OSA symptoms, but did endorse insomnia or restless legs symptoms, were found to have OSA based on apnea-hypopnea index (AHI) >5 during overnight laboratory testing. Regression models of the full cohort showed that the risk of OSA was related, as expected, to older age, male sex, elevated body mass index, and presence of OSA symptoms. The presence of insomnia symptoms did not alter the risk of OSA. The presence of restless legs symptoms showed a small odds ratio for lowered OSA risk. Objective evidence of OSA occurs similarly in those with insomnia or restless legs symptoms, even among those without self-reported OSA symptoms. Providers should be aware of the potential for occult OSA in populations with insomnia and restless legs, which may complicate their management in addition to presenting an independent medical risk itself.

Sleep-wake time perception varies by direct or indirect query.

The diagnosis of insomnia rests on self-report of difficulty initiating or maintaining sleep. However, subjective reports may be unreliable, and possibly may vary by the method of inquiry. We investigated this possibility by comparing within-individual response to direct versus indirect time queries after overnight polysomnography. We obtained self-reported sleep-wake times via morning questionnaires in 879 consecutive adult diagnostic polysomnograms. Responses were compared within subjects (direct versus indirect query) and across groups defined by apnea-hypopnea index and by self-reported insomnia symptoms in pre-sleep questionnaires. Direct queries required a time duration response, while indirect queries required clock times from which we calculated time durations. Direct and indirect queries of sleep latency were the same in only 41% of cases, and total sleep time queries matched in only 5.4%. For both latency and total sleep, the most common discrepancy involved the indirect value being larger than the direct response. The discrepancy between direct and indirect queries was not related to objective sleep metrics. The degree of discrepancy was not related to the presence of insomnia symptoms, although patients reporting insomnia symptoms showed underestimation of total sleep duration by direct response. Self-reported sleep latency and total sleep time are often internally inconsistent when comparing direct and indirect survey queries of each measure. These discrepancies represent substantive challenges to effective clinical practice, particularly when diagnosis and management depends on self-reported sleep patterns, as with insomnia. Although self-reported sleep-wake times remains fundamental to clinical practice, objective measures provide clinically relevant adjunctive information.

Sleep-related eye symptoms and their potential for identifying driver sleepiness.

The majority of individuals appear to have insight into their own sleepiness, but there is some evidence that this does not hold true for all, for example treated patients with obstructive sleep apnoea. Identification of sleep-related symptoms may help drivers determine their sleepiness, eye symptoms in particular show promise. Sixteen participants completed four motorway drives on two separate occasions. Drives were completed during daytime and night-time in both a driving simulator and on the real road. Ten eye symptoms were rated at the end of each drive, and compared with driving performance and subjective and objective sleep metrics recorded during driving. 'Eye strain', 'difficulty focusing', 'heavy eyelids' and 'difficulty keeping the eyes open' were identified as the four key sleep-related eye symptoms. Drives resulting in these eye symptoms were more likely to have high subjective sleepiness and more line crossings than drives where similar eye discomfort was not reported. Furthermore, drivers having unintentional line crossings were likely to have 'heavy eyelids' and 'difficulty keeping the eyes open'. Results suggest that drivers struggling to identify sleepiness could be assisted with the advice 'stop driving if you feel sleepy and/or have heavy eyelids or difficulty keeping your eyes open'.

Effects of epilepsy treatments on sleep architecture and daytime sleepiness: An evidence‐based review of objective sleep metrics

Sleep is considered restorative, and good quantity and quality sleep is required for memory consolidation and synaptic plasticity. Sleep disorders are common in patients with epilepsy. Poor sleep quality or quantity may worsen seizure control. On the other end, seizures and epilepsy may worsen the sleep quality and set a vicious cycle. In addition, antiepileptic drugs have an effect on sleep architecture. We performed a systemic literature review with a goal to evaluate the effect of antiepileptic drugs and nondrug treatments for epilepsy on sleep architecture to help better understand treatment effects, especially in patients with epilepsy and sleep problems. We searched PubMed and identified studies that evaluated objective sleep outcomes for an antiepileptic drug. We also searched for studies with objective sleep outcomes that evaluated other epilepsy treatments such as epilepsy surgery, vagus nerve stimulation, and ketogenic diet. The studies were categorized based on evidence class and study population for an individual antiepileptic drug or treatment. We identified that most antiepileptic drugs and nondrug treatments for epilepsy affect sleep architecture. We identified that gabapentin, tiagabine, pregabalin, clobazam, and carbamazepine reduce sleep latency and/or improve sleep efficiency. Phenobarbital, valproic acid, and higher-dose levetiracetam aggravate daytime sleepiness, whereas topiramate and zonisamide do not. Vagus nerve stimulation reduces daytime sleepiness, and ketogenic diet improves slow-wave sleep. Epilepsy surgery may improve nocturnal sleep only in a subgroup of patients with improved seizure frequency. Further studies are needed to evaluate the dose-dependent sleep effects of antiepileptic drugs and nondrug treatments independent of the improvement of epilepsy, and to identify if these changes are clinically significant.