Large Muscle Group Movements during Sleep in Restless Leg Syndrome: Neurophysiological and Clinical Implications.

STUDY OBJECTIVES: Recently, criteria have been drawn up for Large Muscle group Movements during sleep (LMM), defined as movements lasting for 3-45 seconds in adults, which are often accompanied by changes in sleep stage, arousals, and increases in heart rate. The aim of this study was to characterize LMM in RLS, in order to better evaluate their impact on the neurophysiology of the disorder and, therefore, the possible clinical implications. METHODS: Consecutive, drug-free patients diagnosed with RLS and controls, aged 18 years or more, were retrospectively enrolled. Leg movement activity - short-interval (SILMS), periodic (PLMS) and isolated (ISOLMS) leg movements during sleep - and LMM were detected and scored. RESULTS: One-hundred patients and 67 controls were recruited. All movement measures were significantly higher in RLS. A significant positive correlation was found between LMM and ISOLMS index but not PLMS index in both groups. LMM index showed a significant negative correlation with total sleep time, sleep efficiency, and percentage of sleep stages N3 and R, as well as a significant positive correlation with number of awakenings, and percentage of sleep stages N1 and N2 only in patients with RLS. No significant correlation was found for either LMM or PLMS index and RLS severity. CONCLUSIONS: Different types of movements, including SILMS, ISOLMS, and LMM, play somewhat distinct roles in sleep neurophysiology in RLS. Notably, LMM, a newly recognized category of movements, demonstrate associations with sleep architecture instability and fragmentation, arousals, and awakenings, suggesting potential clinical implications.

Polysomnographic features associated with clonazepam and melatonin treatment in isolated REM sleep behavior disorder: Time for new therapeutic approaches?

AIMS: Although clonazepam (CLO) and melatonin (MLT) are the most frequently used treatments for REM sleep behavior disorder, the polysomnographic features associated with their use are little known. The aim of this study was to evaluate polysomnographic and clinical parameters of patients with idiopathic/isolated REM sleep behavior disorder (iRBD) treated chronically with CLO, sustained-release MLT, alone or in combination, and in a group of drug-free iRBD patients. METHODS: A total of 96 patients were enrolled: 43 drug-free, 21 with CLO (0.5-2 mg), 20 with sustained-release MLT (1-4 mg), and 12 taking a combination of them (same doses). Clinical variables and polysomnography were collected. RESULTS: Although clinical improvement was reported in all groups, MLT impacted sleep architecture more than the other treatments, with significant and large increase in N3 stage, moderate reduction in N2 and REM sleep, and moderate increase in REM latency. CLO moderately increased the percentage of both REM sleep and especially N2, while reducing N1 and wakefulness. Patients treated with both CLO and MLT did not show major changes in sleep architecture. CONCLUSION: These results suggest that the administration of MLT or CLO impacts (positively) on sleep parameters of iRBD patients. However, there is a need to better stratify patients, in order to treat them in a targeted manner, depending on the patient's individual sleep architecture and expected differential effects of these agents.

Periodic Leg Movements during Sleep Associated with REM Sleep Behavior Disorder: A Machine Learning Study.

Most patients with idiopathic REM sleep behavior disorder (iRBD) present peculiar repetitive leg jerks during sleep in their clinical spectrum, called periodic leg movements (PLMS). The clinical differentiation of iRBD patients with and without PLMS is challenging, without polysomnographic confirmation. The aim of this study is to develop a new Machine Learning (ML) approach to distinguish between iRBD phenotypes. Heart rate variability (HRV) data were acquired from forty-two consecutive iRBD patients (23 with PLMS and 19 without PLMS). All participants underwent video-polysomnography to confirm the clinical diagnosis. ML models based on Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) were trained on HRV data, and classification performances were assessed using Leave-One-Out cross-validation. No significant clinical differences emerged between the two groups. The RF model showed the best performance in differentiating between iRBD phenotypes with excellent accuracy (86%), sensitivity (96%), and specificity (74%); SVM and XGBoost had good accuracy (81% and 78%, respectively), sensitivity (83% for both), and specificity (79% and 72%, respectively). In contrast, LR had low performances (accuracy 71%). Our results demonstrate that ML algorithms accurately differentiate iRBD patients from those without PLMS, encouraging the use of Artificial Intelligence to support the diagnosis of clinically indistinguishable iRBD phenotypes.

A data-driven approach to neuropsychological features in isolated REM behaviour disorder: A latent class analysis.

Recent evidence demonstrated that neuropsychological assessment may be considered a valid marker of neurodegeneration in idiopathic REM sleep behaviour disorder (iRBD). However, little is known about the possible neuropsychological heterogeneity within the iRBD population. This retrospective study aimed to identify and describe different neuropsychological phenotypes in iRBD patients by means of a data-driven approach using latent class analysis. A total of 289 iRBD patients underwent a neuropsychological assessment evaluating cognitive domains: global cognition, language, short- and long-term memory, executive functions and visuospatial abilities. The presence of mild cognitive impairment (MCI) was also assessed. Latent class analysis was carried out to identify iRBD subtypes according to neuropsychological scores. The most parsimonious model identified three latent classes. Groups were labelled as follows: Class 2 "severely impaired" (n = 83/289): mean pathological scores in different tests, a high percentage of MCI multiple-domain and impairment in all neuropsychological domains. Class 1 "moderately impaired" (n = 44/289): mean neuropsychological score within the normal value, a high percentage of MCI (high risk to phenoconversion) and great impairment in the visuospatial domain. Class 3 "slightly impaired" (n = 162/289): no deficit worthy of attention except for short- and long-term memory. Our results suggest three different clinical phenotypes within the iRBD population. These findings may be relevant in the future for predicting the clinical trajectories of phenoconversion in iRBD.

Impact of pre-sleep habits on adolescent sleep: an Italian population-based study.

OBJECTIVE: Several evidences demonstrate that pre-sleep habits may negatively impact adolescent sleep, yet few data exist on Italian population. This study aimed to investigate the relationship between pre-sleep habits, use of technology/activity and sleep in Italian adolescents. METHODS: Self-report questionnaires including Italian version of School Sleep Habits Survey and use of technology/activity (eg smartphone, PC) at bedtime were administered to 972 adolescents (13-19 years) from Lombardia. We stratified the sample in five groups according to the age: Group I (13-14 years), Group II (15 years), Group III (16 years), Group IV (17 years), Group V (18-19 years). RESULTS: Our descriptive analysis reveals a different sleep profile across age-groups: Group III showed highest percentage of bad sleep (26.7%) and frequent nocturnal awakenings (24.1%), Group V had the highest percentage of insufficient sleep (40,4%) and difficulty falling asleep (42.7%) and Group IV presented an elevated difficulty in waking up in the morning (70.1%). A significant negative correlation was found in total group between use of smartphone, internet and studying/doing homework and total sleep time. The use of smartphone, internet videogames, listening to music and studying/doing homework was positively associated with delayed bedtime. CONCLUSIONS: This study confirms the great impact of pre-sleep habits, and in particular the use of technology on adolescent sleep. Our results demonstrate that sleep is strongly altered among Italian adolescents using electronic devices in evening. The type of technology may be related to specific sleep profile, emphasizing the importance of stratification analyses to identify associated factors to sleep problems.

Impact of COVID-19 lockdown on sleep quality in university students and administration staff.

INTRODUCTION: In Italy, lockdown due to COVID-19 health emergency started on March 10 and partially ended on May 3rd, 2020. There was a significant increase of psychological distress and symptoms of mental illness, and worsening of quality of sleep in the general population. METHODS: Participants completed an anonymous web-based survey that include questionnaires about sleep and anxiety and depression symptoms. Our sample included 400 subjects: 307 students (mean age 22.84 ± 2.68) and 93 university administration staff workers (mean age 37.02 ± 12.46). RESULTS: we found an increase in Bed Time hour, Sleep Latency, and Wake-Up time between before and during COVID-19 emergency and a worsening of sleep quality and of insomnia symptoms. In particular, during the lockdown, the impact of the delay in Bed Time and in Wake-Up was more pronounced in students. In workers, we observed a prevalence of maintenance insomnia before COVID-19 of 24% that significantly increase during COVID-19 reaching 40%, while workers with difficulties in sleep initiation were only 15% that increased to 42%. In our sample, 27.8% showed depressive symptoms, while 34.3% showed anxious symptoms, in particular in students. CONCLUSION: The impact of lockdown was greater in students than in workers, and in females than in males. Concerning the psycho-emotional aspects, about one-third of our sample showed depressive or anxious symptoms. The results of our study may provide support for the implementation of some interventions for well-being in pandemic condition.

Usefulness of cardiac parasympathetic index in CPAP-treated patients with obstructive sleep apnea: A preliminary study.

Cardiac autonomic indexes, including cardiac parasympathetic index and cardiac sympathetic index, have been reported to accurately identify patients with sleep disorders such as obstructive sleep apnea. Our study aimed to assess cardiac autonomic indexes in patients with obstructive sleep apnea before and during a single full-night continuous positive airway pressure therapy using a combined approach. Our simultaneous heart rate variability-polysomnographic study included 16 never-treated obstructive sleep apnea patients. Two patients dropped out. Patients underwent combined recordings in two consecutive days, at baseline and during a single full-night of acute continuous positive airway pressure treatment. We calculated cardiac parasympathetic index and cardiac sympathetic index as night/day ratio for high-frequency and low-frequency heart rate variability spectral components, respectively. Continuous positive airway pressure treatment significantly reduced cardiac autonomic indexes values in comparison with baseline values (cardiac parasympathetic index: p < .0001; cardiac sympathetic index: p = .001). After acute continuous positive airway pressure treatment, the percentage of decrease of cardiac parasympathetic index was greater than that of cardiac sympathetic index (51.02 ± 15.72 versus 34.64 ± 26.93). A positive statistical correlation was also found between decrease of cardiac parasympathetic index and decrease of apnea-hypopnea index after continuous positive airway pressure (p < .001). This study improves the knowledge on cardiac autonomic modulation during acute continuous positive airway pressure therapy in obstructive sleep apnea. Our results demonstrate that both autonomic indexes decreased significantly after a single-night of acute continuous positive airway pressure therapy. Cardiac parasympathetic index more than cardiac sympathetic index was related to decrease of apnea-hypopnea index after continuous positive airway pressure therapy, thus representing a potential help in everyday clinical practice.