Do neurologists agree in diagnosing drug resistance in adults with focal epilepsy?

OBJECTIVE: To evaluate interrater agreement in categorizing treatment outcomes and drug responsiveness status according to the International League Against Epilepsy (ILAE) definition of drug-resistant epilepsy. METHODS: A total of 1053 adults with focal epilepsy considered by the investigators to meet ILAE criteria for drug resistance were enrolled consecutively at 43 centers and followed up prospectively for 18-34 months. Treatment outcomes for all antiepileptic drugs (AEDs) used up to enrollment (retrospective assessment), and on an AED newly introduced at enrollment, were categorized by individual investigators and by 2 rotating members of a 16-member expert panel (EP) that reviewed the patient records independently. Interrater agreement was tested by Cohen's kappa (k) statistics and rated according to Landis and Koch's criteria. RESULTS: Agreement between EP members in categorizing outcomes on the newly introduced AED was almost perfect (90.1%, k = 0.84, 95% confidence interval [CI] 0.80-0.87), whereas agreement between the EP and individual investigators was moderate (70.4%, k = 0.57, 95% CI 0.53-0.61). Similarly, categorization of outcomes on previously used AEDs was almost perfect between EP members (91.7%, k = 0.83, 95% CI 0.81-0.84) and moderate between the EP and investigators (68.2%, k = 0.50, 95% CI 0.48-0.52). Disagreement was related predominantly to outcomes considered to be treatment failures by the investigators but categorized as undetermined by the EP. Overall, 19% of patients classified as having drug-resistant epilepsy by the investigators were considered by the EP to have "undefined responsiveness." SIGNIFICANCE: Interrater agreement in categorizing treatment outcomes according to ILAE criteria ranges from moderate to almost perfect. Nearly 1 in 5 patients considered by enrolling neurologists to be "drug-resistant" were classified by the EP as having "undefined responsiveness.

Breakthrough SARS-CoV-2 infections after COVID-19 mRNA vaccination in MS patients on disease modifying therapies during the Delta and the Omicron waves in Italy

Background In this study we aimed to monitor the risk of breakthrough SARS-CoV-2 infection in patients with MS (pwMS) under different DMTs and to identify correlates of reduced protection.Methods This is a prospective Italian multicenter cohort study, long-term clinical follow-up of the CovaXiMS (Covid-19 vaccine in Multiple Sclerosis) study. 1855 pwMS scheduled for SARS-CoV-2 mRNA vaccination were enrolled and followed up to a mean time of 10 months. The cumulative incidence of breakthrough Covid-19 cases in pwMS was calculated before and after December 2021, to separate the Delta from the Omicron waves and to account for the advent of the third vaccine dose.Findings 1705 pwMS received 2 m-RNA vaccine doses, 21/28 days apart. Of them, 1508 (88.5%) had blood assessment 4 weeks after the second vaccine dose and 1154/1266 (92%) received the third dose after a mean interval of 210 days (range 90-342 days) after the second dose. During follow-up, 131 breakthrough Covid-19 infections (33 during the Delta and 98 during the Omicron wave) were observed. The probability to be infected during the Delta wave was associated with SARS-CoV-2 antibody levels measured after 4 weeks from the second vaccine dose (HR=0.57, p < 0.001); the protective role of antibodies was preserved over the whole follow up (HR=0.57, 95%CI=0.43-0.75, p < 0.001), with a significant reduction (HR=1.40, 95%CI=1.01-1.94, p=0.04) for the Omicron cases. The third dose significantly reduced the risk of infection (HR=0.44, 95%CI=0.21-0.90,p=0.025) during the Omicron wave.Interpretation The risk of breakthrough SARS-CoV-2 infections is mainly associated with reduced levels of the virus-specific humoral immune response. Copyright (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/

Data monitoring roadmap. The experience of the Italian Multiple Sclerosis and Related Disorders Register

Introduction Over the years, disease registers have been increasingly considered a source of reliable and valuable population studies. However, the validity and reliability of data from registers may be limited by missing data, selection bias or data quality not adequately evaluated or checked.This study reports the analysis of the consistency and completeness of the data in the Italian Multiple Sclerosis and Related Disorders Register.MethodsThe Register collects, through a standardized Web-based Application, unique patients.Data are exported bimonthly and evaluated to assess the updating and completeness, and to check the quality and consistency. Eight clinical indicators are evaluated.ResultsThe Register counts 77,628 patients registered by 126 centres. The number of centres has increased over time, as their capacity to collect patients.The percentages of updated patients (with at least one visit in the last 24 months) have increased from 33% (enrolment period 2000-2015) to 60% (enrolment period 2016-2022). In the cohort of patients registered after 2016, there were >= 75% updated patients in 30% of the small centres (33), in 9% of the medium centres (11), and in all the large centres (2).Clinical indicators show significant improvement for the active patients, expanded disability status scale every 6 months or once every 12 months, visits every 6 months, first visit within 1 year and MRI every 12 months.ConclusionsData from disease registers provide guidance for evidence-based health policies and research, so methods and strategies ensuring their quality and reliability are crucial and have several potential applications

Disease-Modifying Therapies and Coronavirus Disease 2019 Severity in Multiple Sclerosis

Objective: This study was undertaken to assess the impact of immunosuppressive and immunomodulatory therapies on the severity of coronavirus disease 2019 (COVID-19) in people with multiple sclerosis (PwMS). Methods: We retrospectively collected data of PwMS with suspected or confirmed COVID-19. All the patients had complete follow-up to death or recovery. Severe COVID-19 was defined by a 3-level variable: mild disease not requiring hospitalization versus pneumonia or hospitalization versus intensive care unit (ICU) admission or death. We evaluated baseline characteristics and MS therapies associated with severe COVID-19 by multivariate and propensity score (PS)-weighted ordinal logistic models. Sensitivity analyses were run to confirm the results. Results: Of 844 PwMS with suspected (n = 565) or confirmed (n = 279) COVID-19, 13 (1.54%) died; 11 of them were in a progressive MS phase, and 8 were without any therapy. Thirty-eight (4.5%) were admitted to an ICU; 99 (11.7%) had radiologically documented pneumonia; 96 (11.4%) were hospitalized. After adjusting for region, age, sex, progressive MS course, Expanded Disability Status Scale, disease duration, body mass index, comorbidities, and recent methylprednisolone use, therapy with an anti-CD20 agent (ocrelizumab or rituximab) was significantly associated (odds ratio [OR] = 2.37, 95% confidence interval [CI] = 1.18\u20134.74, p = 0.015) with increased risk of severe COVID-19. Recent use (<1 month) of methylprednisolone was also associated with a worse outcome (OR = 5.24, 95% CI = 2.20\u201312.53, p = 0.001). Results were confirmed by the PS-weighted analysis and by all the sensitivity analyses. Interpretation: This study showed an acceptable level of safety of therapies with a broad array of mechanisms of action. However, some specific elements of risk emerged. These will need to be considered while the COVID-19 pandemic persists. ANN NEUROL 2021;89:780\u2013789

Overview of JET results for optimising ITER operation

The JET 2019–2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019–2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (α) physics in the coming D–T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D–T benefited from the highest D–D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER

Spectroscopic camera analysis of the roles of molecularly assisted reaction chains during detachment in JET L-mode plasmas

The roles of the molecularly assisted ionization (MAI), recombination (MAR) and dissociation (MAD) reaction chains with respect to the purely atomic ionization and recombination processes were studied experimentally during detachment in low-confinement mode (L-mode) plasmas in JET with the help of experimentally inferred divertor plasma and neutral conditions, extracted previously from filtered camera observations of deuterium Balmer emission, and the reaction coefficients provided by the ADAS, AMJUEL and H2VIBR atomic and molecular databases. The direct contribution of MAI and MAR in the outer divertor particle balance was found to be inferior to the electron-atom ionization (EAI) and electron-ion recombination (EIR). Near the outer strike point, a strong atom source due to the D+2-driven MAD was, however, observed to correlate with the onset of detachment at outer strike point temperatures of Te,osp = 0.9-2.0 eV via increased plasma-neutral interactions before the increasing dominance of EIR at Te,osp < 0.9 eV, followed by increasing degree of detachment. The analysis was supported by predictions from EDGE2D-EIRENE simulations which were in qualitative agreement with the experimental observations

New H-mode regimes with small ELMs and high thermal confinement in the Joint European Torus

New H-mode regimes with high confinement, low core impurity accumulation, and small edge-localized mode perturbations have been obtained in magnetically confined plasmas at the Joint European Torus tokamak. Such regimes are achieved by means of optimized particle fueling conditions at high input power, current, and magnetic field, which lead to a self-organized state with a strong increase in rotation and ion temperature and a decrease in the edge density. An interplay between core and edge plasma regions leads to reduced turbulence levels and outward impurity convection. These results pave the way to an attractive alternative to the standard plasmas considered for fusion energy generation in a tokamak with a metallic wall environment such as the ones expected in ITER.& nbsp;Published under an exclusive license by AIP Publishing

Disruption prediction at JET through deep convolutional neural networks using spatiotemporal information from plasma profiles

In view of the future high power nuclear fusion experiments, the early identification of disruptions is a mandatory requirement, and presently the main goal is moving from the disruption mitigation to disruption avoidance and control. In this work, a deep-convolutional neural network (CNN) is proposed to provide early detection of disruptive events at JET. The CNN ability to learn relevant features, avoiding hand-engineered feature extraction, has been exploited to extract the spatiotemporal information from 1D plasma profiles. The model is trained with regularly terminated discharges and automatically selected disruptive phase of disruptions, coming from the recent ITER-like-wall experiments. The prediction performance is evaluated using a set of discharges representative of different operating scenarios, and an in-depth analysis is made to evaluate the performance evolution with respect to the considered experimental conditions. Finally, as real-time triggers and termination schemes are being developed at JET, the proposed model has been tested on a set of recent experiments dedicated to plasma termination for disruption avoidance and mitigation. The CNN model demonstrates very high performance, and the exploitation of 1D plasma profiles as model input allows us to understand the underlying physical phenomena behind the predictor decision

The role of ETG modes in JET-ILW pedestals with varying levels of power and fuelling

We present the results of GENE gyrokinetic calculations based on a series of JET-ITER-like-wall (ILW) type I ELMy H-mode discharges operating with similar experimental inputs but at different levels of power and gas fuelling. We show that turbulence due to electron-temperature-gradient (ETGs) modes produces a significant amount of heat flux in four JET-ILW discharges, and, when combined with neoclassical simulations, is able to reproduce the experimental heat flux for the two low gas pulses. The simulations plausibly reproduce the high-gas heat fluxes as well, although power balance analysis is complicated by short ELM cycles. By independently varying the normalised temperature gradients (omega(T)(e)) and normalised density gradients (omega(ne )) around their experimental values, we demonstrate that it is the ratio of these two quantities eta(e) = omega(Te)/omega(ne) that determines the location of the peak in the ETG growth rate and heat flux spectra. The heat flux increases rapidly as eta(e) increases above the experimental point, suggesting that ETGs limit the temperature gradient in these pulses. When quantities are normalised using the minor radius, only increases in omega(Te) produce appreciable increases in the ETG growth rates, as well as the largest increases in turbulent heat flux which follow scalings similar to that of critical balance theory. However, when the heat flux is normalised to the electron gyro-Bohm heat flux using the temperature gradient scale length L-Te, it follows a linear trend in correspondence with previous work by different authors