Rapid-eye movement (REM) Sleep Behavior Disorder (RBD) is a parasomnia characterized by the loss of physiological muscle atonia during REM sleep, often resulting in dream enactment and violent behaviors. Idiopathic RBD is recognized as a prodromal marker of alpha-synucleinopathies, with conversion rates reaching 73–96% within 12–14 years. Despite its clinical relevance, diagnosis relies on polysomnography (PSG) in specialized sleep laboratories, limiting its accessibility and scalability, and its heterogeneity remains underexplored. To support remote health monitoring and early neurological assessment, this study proposes a sleep-stage-independent, unsupervised Machine Learning framework based on a single EEG channel collected during home-based PSG. In a dataset of 32 individuals with RBD, the method consistently identified two clusters with distinct neurophysiological profiles. These data-driven subgroups also showed differences in the REM Atonia Index (RAI), a quantitative marker of REM muscle atonia and RBD severity, supporting the interpretability of the identified neurophysiological patterns. These findings highlight the feasibility of low-complexity, unsupervised EEG analysis for characterizing RBD heterogeneity, suggesting the feasibility of scalable telehealth solutions for continuous monitoring and early detection of neurodegenerative risk.

Heart rate variability (HRV) is a promising biomarker for detecting subtle autonomic alterations in sleep disorders such as REM Sleep Behavior Disorder (RBD). However, the relevance of HRV-derived features depends heavily on methodological choices, including data segmentation, preprocessing, and dataset composition. This study systematically investigates how four key factors (epoch duration, inclusion of wake segments, dataset heterogeneity, and the presence of comorbidities such as Obstructive Sleep Apnea Syndrome (OSAS)), affect HRV feature discriminative power. Using multiple polysomnography datasets, we extract a comprehensive suite of 528 features per subject and evaluate their importance using a combination of statistical and machine learningbased techniques. Results show that longer epochs typically yield more robust features, though shorter windows enhance the prominence of nonlinear metrics. Including wake segments improves feature relevance in heterogeneous datasets, supporting their use in real-world conditions. Furthermore, dataset aggregation enhances generalizability for full-night recordings, but may reduce performance when analyzing sleep-only data. Finally, including OSAS subjects had minimal effect on top-ranked features, indicating the robustness of HRV-based RBD markers across varying clinical contexts. These findings highlight the importance of thoughtful experimental design in HRV-based classification models in sleep research.

Background: Sleep wake and circadian disturbances are increasingly recognised in people living with amyotrophic lateral sclerosis (plwALS), but endogenous circadian phase timing and its prognostic significance in early disease remain unclear. We assessed whether salivary dim-light melatonin onset (DLMO), an objective marker of central circadian phase, is altered in early plwALS and whether it provides prognostic information. Methods: In this prospective longitudinal observational study, plwALS within 18 months of symptom onset underwent home-based salivary melatonin sampling under dim light conditions at six predefined time points around habitual sleep onset (HSO). Melatonin profiles were modeled using cubic smoothing splines, and DLMO was defined as the first time the fitted curve reached 3 pg/mL. Clinical, respiratory, and sleep assessments were collected at baseline (T0) and after 6 months (T6); a subgroup repeated saliva sampling at T6. Age and sex matched controls underwent melatonin profiling. Associations with disease progression, incident respiratory symptoms, and survival/tracheostomy were examined using regressions and survival analyses. Results: Fifty plwALS were enrolled. Compared with controls, plwALS showed an earlier DLMO (20:24 vs 20:58; p=0.028) despite similar HSO and chronotype. Within ALS cohort, a later baseline DLMO correlated with worse functional/motor status, faster progression of disease, incident dyspnea/orthopnea by T6 (adjusted OR 3.02; p=0.017), and poorer survival/tracheostomy-free outcome. In re-sampled subgroup (n=28), DLMO and other melatonin-derived metrics did not change over 6 months. Conclusions: Circadian phase alterations are detectable in early ALS. Baseline DLMO may represent a non-invasive prognostic biomarker for progression, respiratory symptom emergence and survival, warranting validation in larger multicentre cohorts. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval was obtained by Comitato Etico Azienda Ospedaliero-Universitaria Citta della Salute e della Scienza, Torino (protocol number: 0028226 of 15th Mar 2021). All participants provided written informed consent. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Polysomnography (PSG) is the gold standard for diagnosing sleep disorders, but its complexity and cost limit widespread use. Heart rate variability (HRV) is traditionally assessed from electrocardiography (ECG), while photoplethysmography (PPG), widely available in wearable devices, offers a more accessible alternative. However, its reliability over full-night recordings remains underexplored. This study analyzes data from 50 subjects across five groups (healthy controls, rapid eye movement sleep behavior disorder, obstructive sleep apnea, periodic limb movements, and mixed comorbidities) to assess agreement between ECG-derived HRV and PPG-derived pulse rate variability (PRV), considering time-, frequency-, and nonlinear-domain features. Correlation and equivalence analyses were performed, with and without removal of artifactual segments. Correlation coefficients exceeded 0.6 for most features and improved to above 0.7 after artifact removal. Consistent improvements were observed across all subject groups. Equivalence testing further identified a subset of features showing high agreement and low bias. The results indicate that, with appropriate pre-processing, PPG can approximate ECG-derived variability in full-night sleep recordings. The identification of robust features for screening purposes supports the use of PRV for wearable-based screening and monitoring in heterogeneous sleep disorder populations.

Introduction Chronic insomnia disorder significantly affects cognitive, emotional, and physical health. Recently, the dual orexin receptor antagonist (DORA) daridorexant was approved for treating chronic insomnia in several countries. Given the limited evidence available, expert consensus was sought to clarify key clinical issues, inform practice, and guide future research. Methods Thirteen Italian sleep experts employed the Nominal Group Technique (NGT) to identify and rank important clinical questions. The process involved independent thought generation, group discussion, and online voting using a 5-point Likert scale. Results The NGT process resulted in 55 statements across five key clinical questions, with relevance scores guiding their categorization into three tiers. Key findings highlight daridorexant's mechanism of action, safety profile, efficacy on night and day parameters, and suitability for long-term use. The experts emphasized cross-tapering strategies for switching from other hypnotics, the importance of sleep psychoeducation, and using the Insomnia Severity Index and sleep diaries for treatment evaluation. Discussion Daridorexant may address insomnia without increasing sedation via its dual orexin receptor antagonism. Daridorexant seems to be effective and safe even in special patient populations, such as the elderly and those with comorbid conditions (neurodegenerative disorders and cognitive impairment, comorbid insomnia and sleep apnea, psychiatric conditions and mood disorders, epilepsy, and restless leg syndrome), thus representing a new, promising option for insomnia treatment. Conclusion The expert consensus provides a comprehensive framework for daridorexant clinical application, advocating for further research to expand the evidence base and refine best practices, as well as underscoring the importance of a multidisciplinary approach that combines both pharmacological and psychosocial interventions to optimize outcomes.

Background Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the degeneration of upper and lower motor neurons, leading to muscle atrophy, weakness, and respiratory failure. Numerous studies evaluated the impact of diseases on dream content, and the dream content analysis may be considered an interesting tool in the study of the internalization of the consequences of significant life changes. The study of ALS patients' dream content has been mostly neglected in the literature. This study investigated the dream content in a population affected by ALS. Material and Methods We evaluated all consecutive outpatients referred to our ALS Centre using a weekly diary of dreams. Dream contents were coded according to the Hall and Van de Castle coding system. Results Sixty-eight patients completed the study. We collected 127 dreams (females 39.4%) (males 60.6%). Males showed a reduced presence of friends, anatomical elements, aggression, friendship, and sexuality. Instead, we found an increased presence of family members, situations in which the dreamer initiates aggressive action and familiar settings. In the female sample, we found a decreased presence of friends, aggressive and friendly elements, sex-related content, and misfortune, while an increase in animal content. Conclusions Our results demonstrate that dream content in ALS patients differs from that of healthy subjects, and we noticed some gender differences among ALS patients. The dream content can offer insights into ALS patients' mental state and may improve clinicians' ability to support their patients during their therapeutic course.

Rapid Eye Movement (REM) Sleep Behavior Disorder (RBD) is a parasomnia characterized by the loss of physiological muscle atonia during REM sleep, often manifesting through dream-enacting behavior. Idiopathic RBD is largely considered a prodromal stage of neurodegenerative diseases, with a conversion rate to overt α-synucleinopathies of up to 96% after 14 years. Currently, the diagnostic procedure relies on time-consuming and labor-intensive inspection of polysomnography (PSG). This study proposes a Machine Learning (ML), stage-agnostic framework for the automatic detection of RBD subjects through unstaged, single-channel EEG sleep data from 58 subjects (32 RBD). The best model achieved 86.21% accuracy, 90.6% sensitivity, and 87.9% F-1 score, demonstrating strong predictive power. This study is the first to explore whole-night EEG data for RBD detection, paving the way for scalable, lightweight clinical decision support systems for early neurodegenerative screening and risk assessment.Clinical relevance— This study presents a lightweight, clinical decision support tool to enhance RBD detection and support early interventions in neurodegenerative diseases.

Background: Narcolepsy is a chronic sleep disorder characterized mainly by excessive daytime sleepiness (EDS) and cataplexy in the case of narcolepsy type 1 (NT1). Pitolisant is a histamine 3 receptor antagonist/inverse agonist that reduces EDS and cataplexy in patients with narcolepsy. Methods: We performed a prospective 5-year follow-up, non-interventional study of adults with NT1 and NT2 receiving pitolisant. The primary objectives were to collect information on the long-term safety of pitolisant and analyze the utilization patterns of pitolisant. The secondary objectives were to assess clinical benefit, adherence, impact on patients' quality of life, disease burden, and patient satisfaction. We reported the results of an interim analysis after 42.6 months. Results: The population comprised 370 patients (mean age, 40 +/- 15 years; 51.4 % women; NT1, 71.4 %; NT2, 28.6 %); 364 received >= 1 dose of pitolisant. Data were available for 356 patients (97.8 %). Most patients (68.4 %) had >= 1 comorbidity (obesity [BMI >= 30], 31.9 %; neuropsychiatric, 31 %; and cardiovascular, 22.8 %). Forty-eight patients (13.2 %) had received no prior narcoleptic treatment, while 98 (31 %) were taking a previous therapy, which was switched to pitolisant. Treatment was combined with pitolisant in 218 (69 %) patients. Pitolisant was discontinued by 131 patients (35.4 %), mainly for safety reasons (14.3 %), lack of response (8.7 %), and patient decision (7.6 %). Overall, 355 treatment-emergent adverse events (3 serious) were reported by 156 patients (42.9 % of safety population), with 218 possibly treatment-related (61.4 %) in 109 patients (29.9 %). Improvements were observed in EDS, cataplexy, and quality of life. Conclusions: Pitolisant was generally safe and well tolerated in patients with NT1 and NT2 and can be used in both types. Improvements were found in EDS, cataplexy, and quality of life, with good adherence and satisfaction.

IntroductionOne of the main challenges of “real-world” management of depression is represented by geriatric depression, which is common and under-diagnosed. Depressive disorders represent the leading contributors to mental health-related global burden, and they are often diagnosed in the context of many comorbid disorders, such as cardiovascular disorders, Stroke, Parkinson’s Disease, Major Neurocognitive Disorders and Headache, thus worsening their outcomes. Depression, and above all geriatric depression, is a challenge for “real-world” clinicians, due to the low rates of remission despite the increasing number of antidepressant strategies currently available. Indeed, current antidepressant strategies often fail to achieve acceptable rates of remission. The challenge of diagnosis and treatment of geriatric depression in real world calls for the need of a deeper exploration of its management in clinical practice. This is the purpose of the present cross-sectional survey, aimed at evaluating the clinical approach to late-life depression in a sample of expert physicians working in geriatric settings in Italy.MethodsHereafter, we provide responses from 175 geriatrics-working physicians, which were recruited to participate in the survey through their membership in the Italian Society of Geriatrics and Gerontology (SIGG). They were invited to respond to a a 20-items questionnaire which was developed based both on literature review and on the a priori knowledge of the subject by the developing team, composed by seven expert physicians in the fields of Psychiatry, Neurology and GeriatricsResults and discussionThe survey was aimed at delving into the possible unmet needs in the management of geriatric depression according to the sample of physicians surveyed, thus trying to provide useful insights on geriatric depression care.

Nocturnal core body temperature (CBT) decline is reflected in decreasing heart rate (HR) and is linked to sleep stage distribution, a relationship which is influenced by age and subject to temperature manipulation. The present study investigates the relationship between CBT, HR, and sleep stage distribution by comparing two studies with healthy males: young and middle-aged men. The aim is to examine how these physiological systems might be interrelated. Data from two independent studies were compared to examine nocturnal sleep stages, CBT, and HR time courses. The findings revealed that younger men exhibited improved sleep consolidation, characterized by longer total sleep time and more slow-wave (SWS) and REM sleep, along with a sustained nocturnal decline in CBT and HR. In contrast, middle-aged men exhibited poorer sleep continuity and a less-pronounced decline in CBT, followed by an earlier rise. The CBT changes were reflected in HR. These results suggest that the nocturnal profile of CBT may be linked to variations in HR and fluctuations in sleep stage distribution. Interventions that facilitate nocturnal heat loss and a reduction in CBT and HR could potentially support sleep quality across age groups, particularly regarding SWS.

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease, ultimately leading to muscle inefficiency and death. A vast majority of people with ALS also suffer from sleep disorders. Previous studies highlighted the presence of REM Sleep Without Atonia (RSWA) in an ALS cohort, and suggested its strong correlation with the disease severity. This study investigates the ability of electromyography (EMG) parameters recorded during Rapid-eye Movement (REM) sleep to predict disease progress and outcome rapidity in ALS. Survival models trained on a cohort of 45 ALS patients undergoing a longitudinal study, revealed a promising predictive power for the proposed EMG-derived metrics (c-index ≥ 0.65) and encouraging goodness of fit (through c-index and χ 2 ). These results suggest the possibility of employing the trained model in follow-up procedures, based on non-invasive, lightweight EMG metrics, which would significantly ease disease monitoring and help personalized symptomatic care.

This commentary aims to offer a perspective on the effect of tirzepatide on hypoxic burden and provide indirect evidence of cardiovascular risk reduction after tirzepatide for the treatment of obstructive sleep apnea and obesity. It also discusses the role of tirzepatide-induced weight loss in the management of obstructive sleep apnea. Recent Findings. In the SURMOUNT-OSA phase 3 trials, tirzepatide, a new GIP/GLP-1 receptor co-agonist, reduced the apnea–hypopnea index, hypoxic burden, and body weight in adults with moderate-to-severe obstructive sleep apnea and obesity. The change in apnea–hypopnea index is clinically relevant, but its impact on cardiovascular mortality remains unclear. Conversely, hypoxic burden predicts cardiovascular mortality across populations independent of AHI. We attempted to postulate the magnitude of cardiovascular benefits of tirzepatide based on the reduction in hypoxic burden. Tirzepatide treatment for obstructive sleep apnea and obesity seems to result in hypoxic burden values associated with a lower cardiovascular mortality rate and thus might attenuate the negative cardiovascular impact of hypoxic burden.

Substantial evidence suggests that the circadian decline of core body temperature (CBT) triggers the initiation of human sleep, with CBT continuing to decrease during sleep. Although the connection between habitual sleep and CBT patterns is established, the impact of external body cooling on sleep remains poorly understood. The main aim of the present study is to show whether a decline in body temperatures during sleep can be related to an increase in slow wave sleep (N3). This three-center study on 72 individuals of varying age, sex, and BMI used an identical type of a high-heat capacity mattress as a reproducible, non-disturbing way of body cooling, accompanied by measurements of CBT and proximal back skin temperatures, heart rate and sleep (polysomnography). The main findings were an increase in nocturnal sleep stage N3 (7.5 ± 21.6 min/7.5 h, mean ± SD; p = 0.0038) and a decrease in heart rate (− 2.36 ± 1.08 bpm, mean ± SD; p < 0.0001); sleep stage REM did not change (p = 0.3564). Subjects with a greater degree of body cooling exhibited a significant increase in nocturnal N3 and a decrease in REM sleep, mainly in the second part of the night. In addition, these subjects showed a phase advance in the NREM-REM sleep cycle distribution of N3 and REM. Both effects were significantly associated with increased conductive inner heat transfer, indicated by an increased CBT- proximal back skin temperature -gradient, rather than with changes in CBT itself. Our findings reveal a previously far disregarded mechanism in sleep research that has potential therapeutic implications: Conductive body cooling during sleep is a reliable method for promoting N3 and reducing heart rate.

Perinatal depression (PND) is a common complication of pregnancy associated with serious health consequences for both mothers and their babies. Identifying risk factors for PND is key to early detect women at increased risk of developing this condition. We applied a machine learning (ML) approach to data from a multicenter cohort study on sleep and mood changes during the perinatal period (“Life-ON”) to derive models for PND risk prediction in a cross-validation setting. A wide range of sociodemographic variables, blood-based biomarkers, sleep, medical, and psychological data collected from 439 pregnant women, as well as polysomnographic parameters recorded from 353 women, were considered for model building. These covariates were correlated with the risk of future depression, as assessed by regularly administering the Edinburgh Postnatal Depression Scale across the perinatal period. The ML model indicated the mood status of pregnant women in the first trimester, previous depressive episodes and marital status, as the most important predictors of PND. Sleep quality, insomnia symptoms, age, previous miscarriages, and stressful life events also added to the model performance. Besides other predictors, sleep changes during early pregnancy should therefore assessed to identify women at higher risk of PND and support them with appropriate therapeutic strategies.

Objective: to prospectively assess sleep and sleep disorders during pregnancy and postpartum in a large cohort of women.Methods: multicenter prospective Life-ON study, recruiting consecutive pregnant women at a gestational age between 10 and 15 weeks, from the local gynecological departments. The study included home polysomnography performed between the 23rd and 25th week of pregnancy and sleep-related questionnaires at 9 points in time during pregnancy and 6 months postpartum. Results: 439 pregnant women (mean age 33.7 +/- 4.2 yrs) were enrolled. Poor quality of sleep was reported by 34% of women in the first trimester of pregnancy, by 46% of women in the third trimester, and by as many as 71% of women in the first month after delivery. A similar trend was seen for insomnia. Excessive daytime sleepiness peaked in the first trimester (30% of women), and decreased in the third trimester, to 22% of women. Prevalence of restless legs syndrome was 25%, with a peak in the third trimester of pregnancy. Polysomno-graphic data, available for 353 women, revealed that 24% of women slept less than 6 h, and 30.6% of women had a sleep efficiency below 80%. Sleep-disordered breathing (RDI >= 5) had a prevalence of 4.2% and correlated positively with BMI. Conclusions: The Life-ON study provides the largest polysomnographic dataset coupled with longitudinal sub-jective assessments of sleep quality in pregnant women to date. Sleep disorders are highly frequent and distributed differently during pregnancy and postpartum. Routine assessment of sleep disturbances in the peri-natal period is necessary to improve early detection and clinical management.

This study aimed to assess the concordance of various psychometric scales in detecting Perinatal Depression (PND) risk and diagnosis. A cohort of 432 women was assessed at 10-15th and 23-25th gestational weeks, 33-40 days and 180-195 days after delivery using the Edinburgh Postnatal Depression Scale (EPDS), Visual Analogue Scale (VAS), Hamilton Depression Rating Scale (HDRS), Montgomery-Åsberg Depression Rating Scale (MADRS), and Mini International Neuropsychiatric Interview (MINI). Spearman's rank correlation coefficient was used to assess agreement across instruments, and multivariable classification models were developed to predict the values of a binary scale using the other scales. Moderate agreement was shown between the EPDS and VAS and between the HDRS and MADRS throughout the perinatal period. However, agreement between the EPDS and HDRS decreased postpartum. A well-performing model for the estimation of current depression risk (EPDS > 9) was obtained with the VAS and MADRS, and a less robust one for the estimation of current major depressive episode (MDE) diagnosis (MINI) with the VAS and HDRS. When the EPDS is not feasible, the VAS may be used for rapid and comprehensive postpartum screening with reliability. However, a thorough structured interview or clinical examination remains necessary to diagnose a MDE.