Objective To evaluate the role of sleep cyclic alternating pattern (CAP) in patients with isolated REM sleep behavior disorder (IRBD) and ascertain whether CAP metrics might represent a marker of phenoconversion to a defined neurodegenerative condition. Methods Sixty-seven IRBD patients were included and classified into patients who phenoconverted to a neurodegenerative disease (RBD converters: converter REM sleep behavior disorder [cRBD]; n = 34) and remained disease-free (RBD non-converters: non-converter REM sleep behavior disorder [ncRBD]; n = 33) having a similar follow-up duration. Fourteen age- and gender-balanced healthy controls were included for comparisons. Results Compared to controls, CAP rate and CAP index were significantly decreased in IRBD mainly due to a decrease of A1 phase subtypes (A1 index) despite an increase in duration of both CAP A and B phases. The cRBD group had significantly lower values of CAP rate and CAP index when compared with the ncRBD group and controls. A1 index was significantly reduced in both ncRBD and cRBD groups compared to controls. When compared to the ncRBD group, A3 index was significantly decreased in the cRBD group. The Kaplan-Meier curve applied to cRBD estimated that a value of CAP rate below 32.9% was related to an average risk of conversion of 9.2 years after baseline polysomnography. Conclusion IRBD is not exclusively a rapid eye movement (REM) sleep parasomnia, as non-rapid eye movement (non-REM) sleep microstructure can also be affected by CAP changes. Further studies are necessary to confirm that a reduction of specific CAP metrics is a marker of neurodegeneration in IRBD.

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The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.

Objective Incomplete hippocampal inversion (IHI) is a relatively frequent radiological finding at visual inspection in both epilepsy and healthy controls, but its clinical significance is unclear. Here, we systematically retrieve and assess the association between epilepsy and IHI using a meta‐analytic approach. Additionally, we estimate the prevalence of IHI in patients with malformation of cortical development (MCD). Methods We systematically searched two databases (Embase and PubMed) to identify potentially eligible studies from their inception to December 2019. For inclusion, studies were population‐based, case–control, observational studies reporting on epilepsy and IHI. The risk of developing epilepsy in IHI (estimated with odds ratio [ORs]) and the frequency of IHI among patients with MCD are provided. Results We screened 3601 records and assessed eligibility of 2812 full‐text articles. The final material included 13 studies involving 1630 subjects. Seven studies (1329 subjects: 952 epileptic and 377 nonepileptic) were included for the estimation of the risk of developing epilepsy in the presence of IHI. The estimated OR of active epilepsy in IHI was 1.699 (95% confidence interval = 0.880–3.281), with moderate heterogeneity across studies (I2 = 71%). Seven studies (591 patients) provided information about the frequency of IHI in MCD. Up to one third of patients with MCD (27.9%) presented coexistent IHI. Significance The present findings confirm that IHI is commonly observed in patients with MCD especially in periventricular nodular heterotopia or polymicrogyria. However, the estimated OR indicates overall weak increased odds of epilepsy in people with IHI, suggesting that the presence of isolated IHI cannot be considered a strong independent predictor for epilepsy development. Clear‐cut neuroradiological criteria for IHI and advanced postprocessing analyses on structural magnetic resonance imaging scans are recommended to highlight differences between epileptogenic and nonepileptogenic IHI.

Objective.MRI fails to reveal hippocampal pathology in 30-50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of covert hippocampal pathology in TLE.Methods.We trained a surface-based linear discriminant classifier that uses T1-weighted (morphology) and T2-weighted as well as FLAIR/T1 (intensity) features. The classifier was trained on 60 TLE patients (mean age: 35.6; 58% female) with histologically-verified hippocampal sclerosis (HS). Images were deemed as MRI-negative in 42% of cases based on neuroradiological reading (40% based on hippocampal volumetry). The predictive model automatically labelled patients as left or right TLE. Lateralization accuracy was compared to electro-clinical data, including side of surgery. Accuracy of the classifier was further assessed in two independent TLE cohorts with similar demographics and electro-clinical characteristics (n=57; 58% MRI-negative).Results.The overall lateralization accuracy was 93% (95%; CI 92% - 94%), regardless of HS visibility. In MRI-negative TLE, the combination of T2 and FLAIR/T1 intensities provided the highest accuracy both in the training (84%, area-under-the-curve (AUC): 0.95±0.02) and the validation cohorts (Cohort 1: 90%, AUC: 0.99; Cohort 2: 76%, AUC: 0.94).Conclusion.This prediction model for TLE lateralization operates on readily available conventional MRI contrasts and offers gain in accuracy over visual radiological assessment. The combined contribution of decreased T1- and increased T2-weighted intensities makes the synthetic FLAIR/T1 contrast particularly effective in MRI-negative HS, setting the basis for broad clinical translation.

Introduction: Differential diagnosis between disorders of arousal (DoA) and sleep-related hypermotor epilepsy (SHE) often represents a clinical challenge. The two conditions may be indistinguishable from a semiological point of view and the scalp video-polysomnography is often uninformative. Both disorders are associated with variable hypermotor manifestations ranging from major events to fragments of a hierarchical continuum of increasing intensity, complexity, and duration. Given their semiological overlap we decided to explore the sleep texture of DoA and SHE seeking for similarities and differences.Methods: We analyzed sleep macrostructure and CAP (cyclic alternating pattern) parameters in a cohort of 35 adult DoA patients, 40 SHE patients and 24 healthy sleepers, all recorded and scored in the same sleep laboratory. Nocturnal behavioral manifestations included minor motor events, paroxysmal arousals and major attacks in SHE, and simple, rising, or complex arousal movements in DoA.Results: Compared to healthy controls, DoA and SHE showed similar amounts of sleep efficiency, light sleep, deep sleep, REM sleep, CAP subtypes. Both groups also showed slow wave sleep fragmentation and an increased representation of stage N3 in the second part of the night. The only discriminating elements between the two conditions regarded sleep length (more reduced in DoA) and sleep instability (more elevated in SHE). In DoA recordings, all motor episodes arose from NREM sleep: 37% during light NREM stages and 63% during stage N3 (simple arousal movements: 94%). In SHE recordings, 57% of major attacks occurred during stage N3.Conclusions: So far, emphasis has been placed on the differentiation of sleep-related epilepsy and NREM arousal disorders. However, the impressive analogies between DoA and SHE suggest the existence of an underestimated continuum across the conditions, linked by increased levels of sleep instability, higher amounts of slow wave sleep and NREM/REM sleep imbalance. Sleep texture is extremely similar in the two conditions, although CAP metrics disclose quantitative differences. In particular, SHE patients show a higher arousal instability compared to DoA subjects. Given their clinical and epidemiological overlap, a common genetic background is also hypothesized. In such a perspective, we suggest that the consolidated dichotomy DoA vs. SHE should be reappraised.

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

Purpose of reviewTo review main knowledges and gaps in the field of sleep microstructure, represented by the cyclic alternating pattern (CAP), in obstructive sleep apnea (OSA). Recent findingsThe (electroencephalographic and autonomic) 'intensity' of arousals in OSA patients, measured through the metrics of CAP, correlate with OSA severity and with disease burden. Continuous positive airway pressure determines variations in sleep architecture (conventional parameters) and at the microstructural level, at different time points. SummaryCAP is not only an 'attractor' of arousals, but also organizes distribution of K-complexes and delta bursts in non-rapid eye movement sleep. Although attention is always concentrated on the A-phase of CAP, a crucial role is play by the phase B, which reflects a period of transient inhibition. Respiratory events in OSA are a typical example of phase B-associated condition, as they occur during the interval between successive A-phases. Accordingly sleep microstructure provides useful insights in the pathophysiology and estimation of OSA severity and may be exploited to follow-up treatment efficacy. In the complex relationship among sleep fragmentation, excessive daytime sleepiness, cognition and cardiovascular risk the CAP framework can offer an integrative perspective in a multidisciplinary scenario.