SEMIAUTOMATIC ANALYSIS OF SLEEP MICROSTRUCTURE PARAMETERS: AROUSAL, CYCLIC ALTERNATING PATTERN AND REM MUSCLE ATONIA.

This thesis project is focused on systems of automatic analysis of sleep parameters and it is composed by two main parts: the first is focused on the process of creation of a software for the analysis of Cyclic Alternating Pattern (CAP) a particular parameter of sleep microstructure and the second part is focused on the use of automatic analysis of muscle activity during sleep. CAP is defined as periodic EEG activity of NREM sleep characterized by sequences of transient electrocortical events, that are distinct from the background electroencephalogram (EEG) activity and occurs at up to 1-minute intervals. CAP represents the microstructure of sleep, and its analysis gives fundamental information that are otherwise neglected with the analysis of sleep macrostructure (sleep staging) alone. CAP is considered a marker for the evaluation of sleep stability and its oscillatory presence is fundamental preservation of sleep stability through the night and in response to arousal stimuli. Analysis of CAP is a very time consuming procedure and it is still used mainly for research purpose rather than in the clinical practice. The development of a software for the analysis of CAP was the main focus of the work in collaboration with Micromed® (an international company for the manufacturing of hardware and software for neurophysiology based in Mogliano Veneto (TV)). During the months spent at Micromed® the PhD student worked with the software programmers and engineers for the creation and validation of the software, individuating all the clinical parameters from guidelines and verifying their correct application and the validity of the results. In the first part of this thesis all the creation process is described in detail. The second part of this thesis is focused on the automatic analysis of muscle EMG tone during both REM and NREM sleep. Muscle tone during sleep gradually diminishes throughout the different sleep stages reaching its minimum with REM muscle atonia. Evaluation of muscle tone during REM sleep is fundamental for the diagnosis of REM sleep Behavior Disorder (RBD) in which there is loss of muscle atonia during REM associated to dream enacting behavior. Muscle activity is measured in polysomnography (PSG) through the recording of different EMG channels. This activity is evaluated almost exclusively during REM sleep using a manual method of visual scoring that require high expertise is highly time consuming. A validated method developed by R. Ferri and co. allows automatic analysis of chin EMG activity through the calculation of Atonia index. Few studies evaluated muscle tone during NREM sleep, and little is known about the neurophysiology of muscle control. Manual methods would be difficult to apply to NREM sleep; the method developed by Ferri is capable to perform an analysis of muscle tone for all sleep stages. RBD is associated to neurodegenerative disorders, synucleinopathies such as Parkinson disease (PD), Multiple System Atrophy (MSA). MSA patients have a more severe loss of atonia during REM sleep compared to PD with RBD. Starting from the fortuitous observation of a prominent facial activity during NREM sleep, we decided to evaluate the facial activity recorded in vPSG in patients with PD, MSA and controls and to evaluate the muscle tone in both REM and NREM sleep using the automatic method for the calculation of atonia index. Our results showed that MSA have a more sustained muscle tone compared to healthy controls in all sleep stages and compared to PD in all NREM stages. Moreover a particular facial expression was noted to be significantly more frequent in MSA compared to PD. This results may help the differential diagnosis between PD and MSA. This is the first study to evaluate muscle tone during all sleep stages using Atonia index and this analysis may open to different perspectives for the understanding of REM behavior disorder and the mechanism underlying the control of muscle tone in NREM slee

Considering REM Sleep Behavior Disorder in the Management of Parkinson's Disease

Rapid eye movement (REM) sleep behavior disorder (RBD) is the result of the loss of physiological inhibition of muscle tone during REM sleep, characterized by dream-enacting behavior and widely recognized as a prodromal manifestation of alpha-synucleinopathies. Indeed, patients with isolated RBD (iRBD) have an extremely high estimated risk to develop a neurodegenerative disease after a long follow up. Nevertheless, in comparison with PD patients without RBD (PDnoRBD), the occurrence of RBD in the context of PD (PDRBD) seems to identify a unique, more malignant phenotype, characterized by a more severe burden of disease in terms of both motor and non-motor symptoms and increased risk for cognitive decline. However, while some medications (eg, melatonin, clonazepam, etc.) and non-pharmacological options have been found to have some therapeutic benefits on RBD there is no available treatment able to modify the disease course or, at least, slow down the neurodegenerative process underlying phenoconversion. In this scenario, the long prodromal phase may allow an early therapeutic window and, therefore, the identification of multimodal biomarkers of disease onset and progression is becoming increasingly crucial. To date, several clinical (motor, cognitive, olfactory, visual, and autonomic features) neurophysiological, neuroimaging, biological (biofluids or tissue biopsy), and genetic biomarkers have been identified and proposed, also in combination, as possible diagnostic or prognostic markers, along with a potential role for some of them as outcome measures and index of treatment response. In this review, we provide an insight into the present knowledge on both existing and future biomarkers of iRBD and highlight the difference with PDRBD and PDnoRBD, including currently available treatment options

Prevalence of sleep disruption and determinants of sleepiness in a cohort of Italian hospital physicians: The PRESOMO study

Nightshift work can cause daytime somnolence and decreased alertness, and can increase risk of medical errors, occupational injuries and car accidents. We used a structured questionnaire, including the Epworth Sleepiness Scale (ESS), to assess the prevalence and the determinants of sleep disruption in 268 Italian University hospital physicians from Cagliari (N = 57), Milan (N = 180) and Pisa (N = 31), who participated in the multicentre study on the prevalence of sleep disturbance among hospital physicians (PRESOMO); 198 of them (74%) were engaged in nightshift work. We explored the association between history of nightshift work and poor sleep quality and daytime somnolence with multivariate logistic regression, adjusting by personal and lifestyle covariates. Age, female gender, taking medication interfering with sleep and an elevated ESS score were significant predictors of poor sleep quality and daytime somnolence. Nightshift work was associated with a higher prevalence of unrestful sleep (84% versus 70%; odds ratio [OR] = 2.4, 95% confidence interval [CI] 1.18-5.05) and daytime dozing (57% versus 35%; OR = 1.9, 95% CI 1.03-3.64), with an upward trend by years of engagement in nightshift work for both conditions (p = .043 and 0.017, respectively), and by number of nightshifts/year for unrestful sleep (p = .024). Such an association was not detected with the ESS scale. Our results suggest that nightshift work significantly affects sleep quality and daytime somnolence in hospital physicians, who might underestimate their daytime dozing problem, when asked to subjectively scale it

Neurophysiological Aspects of REM Sleep Behavior Disorder (RBD): A Narrative Review

REM sleep without atonia (RSWA) is the polysomnographic (PSG) hallmark of rapid eye movement (REM) sleep behavior disorder (RBD), a feature essential for the diagnosis of this condition. Several additional neurophysiological aspects of this complex disorder have also recently been investigated in depth, which constitute the focus of this narrative review, together with RSWA. First, we describe the complex neural network underlying REM sleep and its muscle atonia, focusing on the disordered mechanisms leading to RSWA. RSWA is then described in terms of its polysomnographic features, and the methods (visual and automatic) currently available for its scoring and quantification are exposed and discussed. Subsequently, more recent and advanced neurophysiological features of RBD are described, such as electroencephalography during wakefulness and sleep, transcranial magnetic stimulation, and vestibular evoked myogenic potentials. The role of the assessment of neurophysiological features in the study of RBD is then carefully discussed, highlighting their usefulness and sensitivity in detecting neurodegeneration in the early or prodromal stages of RBD, as well as their relationship with other proposed biomarkers for the diagnosis, prognosis, and monitoring of this condition. Finally, a future research agenda is proposed to help clarify the many still unclear aspects of RBD

Quantification of REM sleep without atonia: A review of study methods and meta-analysis of their performance for the diagnosis of RBD

: The present review focuses on REM sleep without atonia (RSWA) scoring methods. In consideration of the numerous papers published in the last decade, that used different methods for the quantification of RSWA, their systematic revision is an emerging need. We made a search using the PubMed, Embase, Scopus and Web of Science Databases, from 2010 until December 2021, combining the search term "RSWA" with "scoring methods", "IRBD", "alfasyn disease", and "neurodegenerative disease", and with each of the specific sleep disorders, diagnosed according to current criteria, with the identification of the references of interest for the topic. Furthermore, a Meta-analysis of the diagnostic performance of RSWA scoring methods, in terms of sensitivity and specificity, was carried out. The comparison of the hierarchical summary receiver-operating characteristic curves obtained for visual methods and that obtained for the automated REM sleep atonia index (RAI), shows substantially similar prediction areas indicating a comparable performance. This systematic review and meta-analysis support the validity of a series of visual methods and of the automated RAI in the quantification of RSWA with the purpose to guide clinicians in the interpretation of their results and their correct and efficient use within the diagnostic work-up for REM sleep behavior disorder

Gender and Nightshift Work: A Cross Sectional Study on Sleep Quality and Daytime Somnolence

A few studies suggested that female nightshift workers suffer more frequently from sleep deprivation and insomnia. We conducted a cross-sectional survey in two different occupational settings to address gender-related differences in nightshift work adaptation. We used the Epworth Sleepiness Scale and the Pittsburgh Sleep Quality Index questionnaires to quantify daytime sleepiness and sleep quality among 156 workers, 91 from a ceramic tile factory and 65 healthcare workers, including hospital doctors, nurses, and nurse assistants. Seventy-three percent of participants (40 women and 74 men) were engaged in nightshift work. We used logistic regression analysis to predict daytime sleepiness and poor sleep quality as a function of personal and lifestyle variables and nightshift work. The female gender showed a strong association with both daytime sleepiness and poor sleep quality. Results were also suggestive of an increase in the risk of daytime sleepiness associated with nightshift work and being married. Our results confirm that women are especially vulnerable to sleep disruption. Promoting adaptation to nightshift work requires special attention towards gender issues

Neuropsychological and Behavioral Profile in Sleep-Related Hypermotor Epilepsy (SHE) and Disorders of Arousal (DOA): A Multimodal Analysis

Study Objectives: Disorder of arousal (DOA) and sleep-related hypermotor epilepsy (SHE) are complex, often bizarre, involuntary sleep behaviors, whose differential diagnosis may be challenging because they share some clinical features, such as sleep fragmentation. Mounting evidence highlights the critical role of sleep in cognitive functions. Controversial findings are raised about the cognitive profile in SHE; however, no studies have investigated the cognitive profile in DOA. This study aimed to assess whether sleep instability affects cognitive functions in patients with SHE or DOA. Methods: This study analyzed 11 patients with DOA, 11 patients with SHE, and 22 healthy controls (HC). They underwent full-night video polysomnography (vPSG) and comprehensive neuropsychological and behavioral evaluation. Differences in the variables of interest among the SHE group, DOA group, and their respective control groups were evaluated. The auto-contractive map (auto-CM) system was used to evaluate the strength of association across the collected data. Results: The SHE group had reduced sleep efficiency and increased wake after sleep onset (WASO); both the SHE and DOA groups showed increased % of N2 and REM sleep compared to the HC group. Neuropsychological and behavioral evaluations showed a different cognitive profile in the SHE group with respect to the HC group. The auto-CM showed that Pittsburgh Sleep Quality Index (PSQI), Beck depression inventory (BDI), MWCST_PE, Epworth sleepiness scale (ESS), WASO, N1, and % REM were strictly correlated with SHE, whereas the SE and arousal index (AI) were strictly related to DOA. Conclusions: Patients with SHE and DOA present different cognitive and psychiatric profiles, with subtle and selective cognitive impairments only in those with SHE, supporting the discriminative power of cognitive and psychiatric assessment in these two conditions

Severity of REM sleep without atonia correlates with measures of cognitive impairment and depressive symptoms in REM sleep behaviour disorder

This study aimed to correlate REM sleep without atonia (RSWA) and neuropsychological data in patients with idiopathic/isolated REM sleep behaviour disorder (iRBD) and those with RBD associated with Parkinson's disease (PDRBD), in order to assess whether higher degrees of RSWA are related to poorer cognitive performance. A total of 142 subjects were enrolled: 48 with iRBD, 55 with PDRBD, and 39 PD without RBD (PDnoRBD). All participants underwent video-polysomnographic recording, clinical and neuropsychological assessment. RSWA was quantified according to two manual scoring methods (Montreal, SINBAR) and one automated (REM atonia index, RAI). Mild cognitive impairment (MCI) was diagnosed according to diagnostic criteria for MCI in Parkinson's disease. The relationship between neuropsychological scores and RSWA metrics was explored by multiple linear regression analysis and logistic regression models. Patients with iRBD showed significantly lower visuospatial functions and working memory, compared with the others. More severe RSWA was associated with a higher risk of reduced visuospatial abilities (OR 0.15), working memory (OR 2.48), attention (OR 2.53), and semantic fluency (OR 0.15) in the iRBD. In the whole group, a greater RSWA was associated with an increased risk for depressive symptoms (OR 3.6). A total of 57(40%) MCI subjects were found (17 iRBD, 26 PDRBD, and 14 PDnoRBD). Preserved REM-atonia was associated with a reduced odds of multi-domain MCI in the whole study population (OR 0.54). In conclusion, a greater severity of RSWA was associated with an increased risk for poor cognitive performance and depressive mood in patients with RBD. Moreover, higher RAI was associated with a lower risk of multi-domain MCI

COVID‐19 lockdown consequences on body mass index and perceived fragility related to physical activity: A worldwide cohort study

International audienceBackground: This paper is a follow-up study continuing the COVISTRESS network previous research regarding health-related determinants.Objective: The aim was to identify the main consequences of COVID-19 lockdown on Body Mass Index and Perceived Fragility, related to Physical Activity (PA), for different categories of populations, worldwide.Design: The study design included an online survey, during the first wave of COVID-19 lockdown, across different world regions.Setting and participants: The research was carried out on 10 121 participants from 67 countries. The recruitment of participants was achieved using snowball sampling techniques via social networks, with no exclusion criteria other than social media access.Main outcome measures: Body Mass Index, Physical Activity, Perceived Fragility and risk of getting infected items were analysed. SPSS software, v20, was used. Significance was set at P < .05.Results: Body Mass Index significantly increased during lockdown. For youth and young adults (18-35 years), PA decreased by 31.25%, for adults (36-65 years) by 26.05% and for the elderly (over 65 years) by 30.27%. There was a high level of Perceived Fragility and risk of getting infected for female participants and the elderly. Correlations between BMI, Perceived Fragility and PA were identified.Discussion and conclusions: The research results extend and confirm evidence that the elderly are more likely to be at risk, by experiencing weight gain, physical inactivity and enhanced Perceived Fragility. As a consequence, populations need to counteract the constraints imposed by the lockdown by being physically active

The major worldwide stress of healthcare professionals during the first wave of the COVID-19 pandemic - the international COVISTRESS survey

IntroductionThe COVID-19 pandemic has initiated an upheaval in society and has been the cause of considerable stress during this period. Healthcare professionals have been on the front line during this health crisis, particularly paramedical staff. The aim of this study was to assess the high level of stress of healthcare workers during the first wave of the pandemic.Materials and methodsThe COVISTRESS international study is a questionnaire disseminated online collecting demographic and stress-related data over the globe, during the pandemic. Stress levels were evaluated using non-calibrated visual analog scale, from 0 (no stress) to 100 (maximal stress).ResultsAmong the 13,537 individuals from 44 countries who completed the survey from January to June 2020, we included 10,051 workers (including 1379 healthcare workers, 631 medical doctors and 748 paramedical staff). The stress levels during the first wave of the pandemic were 57.8 33 in the whole cohort, 65.3 +/- 29.1 in medical doctors, and 73.6 +/- 27.7 in paramedical staff. Healthcare professionals and especially paramedical staff had the highest levels of stress (p &lt; 0.001 vs non-healthcare workers). Across all occupational categories, women had systematically significantly higher levels of work-related stress than men (p &lt; 0.001). There was a negative correlation between age and stress level (r = -0.098, p &lt; 0.001). Healthcare professionals demonstrated an increased risk of very-high stress levels (&gt;80) compared to other workers (OR = 2.13, 95% CI 1.87-2.41). Paramedical staff risk for very-high levels of stress was higher than doctors' (1.88, 1.50-2.34). The risk of high levels of stress also increased in women (1.83, 1.61-2.09; p &lt; 0.001 vs. men) and in people aged &lt;50 (1.45, 1.26-1.66; p &lt; 0.001 vs. aged &gt;50).ConclusionsThe first wave of the pandemic was a major stressful event for healthcare workers, especially paramedical staff. Among individuals, women were the most at risk while age was a protective factor