Supplementary Material for: Long-Term Occupational Sleep Loss and Post-Retirement Cognitive Decline or Dementia

Introduction: Recent evidence suggests that poor sleep is a risk factor that contributes to the development of Alzheimer’s disease (AD). Most studies have focused on short-term effects of sleep deprivation on cognitive function, whereas longitudinal studies are limited to self-reported sleep and the risk of later-life dementia. Because sleep loss could be an early manifestation of neurodegenerative disease, reverse causality in these studies cannot be excluded. Objective: In this explorative, observational study, we investigated the effects of extended periods of extrinsically (work-related) caused sleep loss on later-life cognitive function, early dementia symptoms, and current sleep quality. Methods: We approached a community of retired male maritime pilots (approx. n = 500) through a newsletter. We investigated 50 respondents (mean age 71.7 years ± 7.7), with a history of > 25 years of work on irregular schedules, which resulted in extended periods of sleep loss. Validated questionnaires on cognitive complaints (Cognitive Failure Questionnaire [CFQ]), early dementia symptoms (Early Dementia Questionnaire [EDQ]), current sleep quality (Pittsburgh Sleep Quality Index [PSQI] and sleep-wake diaries), quality of life (QoL, EQ-5D), and mood (Hospital Anxiety and Depression Scale [HADS]) were administered by a single investigator (J.T.), who also completed an observer rating of cognitive function. Results: Scores on the CFQ, EDQ, PSQI, EQ-5D, and HADS were within normal ranges adjusted for age, sex, and education. The observer rating was not indicative of cognitive decline. Conclusion: We found no evidence that long-term exposure to work-related sleep loss had resulted in cognitive decline or early dementia symptoms in this sample of retired maritime pilots

Data for: Neu3CA-RT: A Framework for Real-Time fMRI Analysis

Neu3-CA-RT sample Matlab script containing a full explanation of how to run the script and where to find sample dat

Conceptions of sleep experience: a layman perspective

Objective To date, there is little information on how lay people understand and discuss sleep in the context of daily life. Efforts to conceptualize sleep quality have been largely driven by clinical considerations of sleep disorders. As such, they are not necessarily of how normal sleepers without clinical expertise conceptualize sleep quality. A phenomenological approach was taken to understand the essence of the sleep experience and the concepts held by lay people without sleep disorders. A sentence completion questionnaire was developed and administered to a quota sample of 64 respondents who were selected aiming for sufficient representation of different gender, ages, and education levels. Results Significant sentences and meaningful units were derived inductively, resulting in a classification of nine categories. The major facets of sleep experience of lay people were ‘daytime functioning’, ‘interruptions during the night’ and ‘before bed state’. This implies that the experienced sleep quality is not only depending on the progress of the night. These results can guide future research to provide suitable psychometric measures for normal sleepers, as well as the design of sleep data visualization applications in the context of health self-monitoring

Pitfalls in EEG Analysis in Patients With Nonconvulsive Status Epilepticus: A Preliminary Study

Objective: Electroencephalography (EEG) interpretations through visual (by human raters) and automated (by computer technology) analysis were still not reliable for the diagnosis of nonconvulsive status epilepticus (NCSE). This study aimed to identify typical pitfalls in the EEG analysis and make suggestions as to how those pitfalls might be avoided. Methods: We analyzed the EEG recordings of individuals who had clinically confirmed or suspected NCSE. Epileptiform EEG activity during seizures (ictal discharges) was visually analyzed by 2 independent raters. We investigated whether unreliable EEG visual interpretations quantified by low interrater agreement can be predicted by the characteristics of ictal discharges and individuals’ clinical data. In addition, the EEG recordings were automatically analyzed by in-house algorithms. To further explore the causes of unreliable EEG interpretations, 2 epileptologists analyzed EEG patterns most likely misinterpreted as ictal discharges based on the differences between the EEG interpretations through the visual and automated analysis. Results: Short ictal discharges with a gradual onset (developing over 3 s in length) were liable to be misinterpreted. An extra 2 min of ictal discharges contributed to an increase in the kappa statistics of >0.1. Other problems were the misinterpretation of abnormal background activity (slow-wave activities, other abnormal brain activity, and the ictal-like movement artifacts), continuous interictal discharges, and continuous short ictal discharges. Conclusion: A longer duration criterion for NCSE-EEGs than 10 s that is commonly used in NCSE working criteria is recommended. Using knowledge of historical EEGs, individualized algorithms, and context-dependent alarm thresholds may also avoid the pitfalls

Effects of long-term sleep disruption on cognitive function and brain amyloid-β burden: a case-control study

Abstract Background Recent evidence indicates that disrupted sleep could contribute to the development of Alzheimer’s disease by influencing the production and/or clearance of the amyloid-β protein. We set up a case-control study to investigate the association between long-term work-induced sleep disruption, cognitive function, and brain amyloid-β burden. Methods Nineteen male maritime pilots (aged 48–60 years) with chronic work-related sleep disruption and a sex-, age-, and education-matched control sample (n = 16, aged 50–60 years) with normal sleep completed the study. Primary sleep disorders were ruled out with in-lab polysomnography. Additional sleep measurements were obtained at home using actigraphy, sleep-wake logs, and a single-lead EEG device. Cognitive function was assessed with a neuropsychological test battery, sensitive to early symptomatic Alzheimer’s disease. Brain amyloid-β burden was assessed in maritime pilots using 18F-flutemetamol amyloid PET-CT. Results Maritime pilots reported significantly worse sleep quality (Pittsburgh Sleep Quality Index (PSQI) = 8.8 ± 2.9) during work weeks, compared to controls (PSQI = 3.2 ± 1.4; 95% CI 0.01 to 2.57; p = 0.049). This was confirmed with actigraphy-based sleep efficiency (86% ± 3.8 vs. 89.3% ± 4.3; 95% CI 0.43 to 6.03; p = 0.03). Home-EEG recordings showed less total sleep time (TST) and deep sleep time (DST) during work weeks compared to rest weeks (TST 318.56 (250.21–352.93) vs. TST 406.17 (340–425.98); p = 0.001; DST 36.75 (32.30–58.58) vs. DST 51.34 (48.37–69.30); p = 0.005)). There were no differences in any of the cognitive domains between the groups. For brain amyloid-β levels, mean global cortical standard uptake value ratios of 18F-flutemetamol were all in the normal range (1.009 ± 0.059; 95% CI 0.980 to 1.037), confirmed by visual reads. Conclusions Capitalizing on the particular work-rest schedule of maritime pilots, this study with a small sample size observed that long-term intermittent sleep disruption had no effects on global brain amyloid-β levels or cognitive function

A Potential Multimodal Test for Clinical Assessment of Visual Attention in Neurological Disorders

Attention is an important aspect of human brain function and often affected in neurological disorders. Objective assessment of attention may assist in patient care, both for diagnostics and prognostication. We present a compact test using a combination of a choice reaction time task, eye-tracking and EEG for assessment of visual attention in the clinic. The system quantifies reaction time, parameters of eye movements (i.e. saccade metrics and fixations) and event related potentials (ERPs) in a single and fast (15 min) experimental design. We present pilot data from controls, patients with mild traumatic brain injury and epilepsy, to illustrate its potential use in assessing attention in neurological patients. Reaction times and eye metrics such as fixation duration, saccade duration and latency show significant differences (p < .05) between neurological patients and controls. Late ERP components (200–800 ms) can be detected in the central line channels for all subjects, but no significant group differences could be found in the peak latencies and mean amplitudes. Our system has potential to assess key features of visual attention in the clinic. Pilot data show significant differences in reaction times and eye metrics between controls and patients, illustrating its promising use for diagnostics and prognostication