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Although international guidelines exist, the clinical heterogeneity of Lennox-Gastaut syndrome (LGS) and the increasing availability of new and repurposed drugs (e.g., fenfluramine and cannabidiol) requires a practical guide to patient management in the clinical context. We report the results of a consensus survey among 42 Italian experts in the diagnosis and treatment of LGS.The consensus procedure followed a modified Delphi approach. Statements were formulated, based on the most recent published evidence and the clinicians' personal experience, then discussed, and agreed upon by the experts through a two-round voting procedure. Approval of a statement was reached with an average score ≥7.Thirteen statements dealing with three main topics (i.e., clinical diagnosis and prognosis, impact on the Quality of Life (QoL), and treatment strategies) were generated. Six statements achieved a level of agreement sufficient for approval on the first voting round. Following the discussion and a few consequent amendments, most of the statements increased their level of agreement and all 13 were approved.Overall, the statements draw a slightly more benign picture of this rare and severe disease, highlighting the possibility of remission - albeit modest -, an apparent trend towards lower mortality, and the availability of several effective drugs, to which greater accessibility would be hoped for. Valproate remains a major therapeutic option in LGS patients although lamotrigine, rufinamide, topiramate, cannabidiol, and clobazam are popular therapeutic options in Italy, allowing for a tailor-made antiseizure therapy.

Introduction The role of computed tomography perfusion (CTP) in prediction of hemorrhagic transformation (HT) has been evolving. We aimed to study the role of automated perfusion post-processing software in prediction of HT using the commercially available RAPID software. Methods Two hundred eighty-two patients with anterior circulation ischemic stroke, who underwent CTP with RAPID automated post-processing, were retrospectively enrolled and divided into HT ( n = 91) and non-HT groups ( n = 191). The automated RAPID-generated perfusion maps were reviewed. Mismatch volume and ratio, time to maximum (Tmax) > 4‐10s volumes, hypoperfusion index, cerebral blood flow (CBF) < 20–38% volumes, cerebral blood volume (CBV) < 34%–42% volumes, and CBV index were recorded and analyzed. Results The volumes of brain tissues suffering from reduction of cerebral blood flow (CBF < 20%–38%), reduction in cerebral blood volumes (CBV < 34–42%), and delayed contrast arrival times (Tmax > 4–10s) were significantly higher in the HT group. The mismatch volumes were also higher in the HT group ( p = .001). Among these parameters, the Tmax > 6s volume was the most reliable and sensitive predictor of HT ( p = .001, AUC = 0.667). However, the combination of the perfusion parameters can slightly improve the diagnostic efficiency (AUC = 0.703). There was no statistically significant difference between the non-HT group and either the parenchymal or the symptomatic subtypes. Conclusion The RAPID automated CTP parameters can provide a reliable predictor of HT overall but not the parenchymal or the symptomatic subtypes. The infarct area involving the penumbra and core represented by the Tmax > 6s threshold is the most sensitive predictor; however, the combination of the perfusion parameters can slightly improve the diagnostic efficiency.

Objective: Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross‐sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE‐HS) correlate with clinical features. Methods: We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1‐weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA‐Epilepsy consortium, comprising 804 people with MTLE‐HS and 1625 healthy controls from 25 centers. Features with a moderate case–control effect size (Cohen d ≥ .5) were used to train an event‐based model (EBM), which estimates a sequence of disease‐specific biomarker changes from cross‐sectional data and assigns a biomarker‐based fine‐grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance. Results: In MTLE‐HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10−16), age at onset (ρ = −.18, p = 9.82 × 10−7), and ASM resistance (area under the curve = .59, p = .043, Mann–Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE‐HS with mild or nondetectable abnormality on T1W MRI. Significance: From cross‐sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE‐HS subjects in other cohorts and help establish connections between imaging‐based progression staging and clinical features.

Fatigue is frequently reported by patients with multiple sclerosis, aquaporin-4-antibody neuromyelitis optica spectrum disorder and myelin-oligodendrocyte-glycoprotein antibody disease; thus they could share a similar pathophysiological mechanism. In this cross-sectional cohort study, we assessed the association of fatigue with resting-state functional MRI, diffusion and structural imaging measures across these three disorders. Sixteen patients with multiple sclerosis, 17 with aquaporin-4-antibody neuromyelitis optica spectrum disorder and 17 with myelin-oligodendrocyte-glycoprotein antibody disease assessed, outside of relapses, at the Oxford Neuromyelitis Optica Service underwent Modified Fatigue Impact Scale, Hospital Anxiety and Depression Scale and Expanded Disability Status Scale scoring. A 3T brain and spinal cord MRI was used to derive cortical, deep grey and white matter volumetrics, lesions volume, fractional anisotropy, brain functional connectivity metrics, cervical spinal cord cross-sectional area, spinal cord magnetic transfer ratio and average functional connectivity between the ventral and the dorsal horns of the cervical cord. Linear relationships between MRI measures and total-, cognitive- and physical-fatigue scores were assessed. All analyses were adjusted for correlated clinical regressors. No significant differences in baseline clinical characteristics, fatigue, depression and anxiety questionnaires and disability measures were seen across the three diseases, except for older age in patients with aquaporin-4-antibody neuromyelitis optica spectrum disorder (P = 0.0005). In the total cohort, median total-fatigue score was 35.5 (range 3–72), and 42% of patients were clinically fatigued. A positive correlation existed between the total-fatigue score and functional connectivity of the executive/fronto-temporal network in the in left middle temporal gyrus (P = 0.033) and between the physical-fatigue score and functional connectivity of the sensory-motor network (P = 0.032) in both pre- and post-central gyri. A negative relationship was found between the total-fatigue score and functional connectivity of the salience network (P = 0.023) and of the left fronto-parietal network (P = 0.026) in the right supramarginal gyrus and left superior parietal lobe. No clear relationship between fatigue subscores and the average functional connectivity of the spinal cord was found. Cognitive-fatigue scores were positively associated with white matter lesion volume (P = 0.018) and negatively associated with white matter fractional anisotropy (P = 0.032). Structural, diffusion and functional connectivity alterations were not influenced by the disease group. Functional and structural imaging metrics associated with fatigue relate to brain rather than spinal cord abnormalities. Salience and sensory-motor networks alterations in relation to fatigue might indicate a disconnection between the perception of the interior body state and activity and the actual behavioural responses and performances (reversible or irreversible). Future research should focus on functional rehabilitative strategies.

Introduction Evidence of the intravenous tissue plasminogen activator (tPA) efficacy beyond the 4.5 hours window is emerging. We aim to study the factors affecting the outcome of delayed thrombolysis in patients of clear onset acute ischemic stroke (AIS). Methods Data of patients with AIS who received intravenous thrombolytic after 4.5 hours were reviewed including: demographics, risk factors, clinical, laboratory, investigational and radiological data, evidence of mismatch, treatment type and onset, National Institutes of Health Stroke Scale (NIHSS) score at baseline, 24 hours, 7 days after thrombolysis and before discharge, and 3 months follow-up modified Rankin Scale (mRS). Results We report 136 patients treated by intravenous tPA between 4.53 and 19.75 hours with average duration of 5.7 h. The ASPECT score of our patients was ≥ 7. Sixty-four cases showed intracranial arterial occlusion . Perfusion mismatch was detected in 117 (84.6%) patients, while clinical imaging mismatch was detected in 19 (15.4%). Early neurological improvement after 24 hours occurred in 114 (83.8%) patients. At 90 days, 91 patients (67%) achieved good outcome (mRS 0–2), while 45 (33%) had bad outcome (mRS 3–6). Age, endovascular treatment, NIHSS, AF , and HT were significantly higher in the bad outcome group. Age ( P = 0.001, OR: 1.099, 95% CI: 1.042–1.160) and baseline NIHSS were predictive of the poor outcome (P = 0.002, OR: 1.151, 95% CI: 1.055–1.256). The best cutoff value of age was 72.5 with AUC of 0.76, sensitivity 73.3% and specificity 60.4%. While for NIHSS at admission, the cutoff value of 7 showed the best results with AUC of 0.73, sensitivity 71.1% and specificity 63.7%. Combination of age and admission NIHSS raised the sensitivity and specificity to 84.4% and 63.7%, respectively. Conclusion Increased age and admission NIHSS may adversely affect the outcome of delayed thrombolysis and narrow the eligibility criteria. Age and baseline NIHSS based stratification of the patients may provide further evidence as regards the efficacy of the delayed thrombolysis.

Together with hippocampus, the amygdala is important in the epileptogenic network of patients with temporal lobe epilepsy. Recently, an increase in amygdala volumes (i.e. amygdala enlargement) has been proposed as morphological biomarker of a subtype of temporal lobe epilepsy patients without MRI abnormalities, although other data suggest that this finding might be unspecific and not exclusive to temporal lobe epilepsy. In these studies, the amygdala is treated as a single entity, while instead it is composed of different nuclei, each with peculiar function and connection. By adopting a recently developed methodology of amygdala’s subnuclei parcellation based of high-resolution T1-weighted image, this study aims to map specific amygdalar subnuclei participation in temporal lobe epilepsy due to hippocampal sclerosis (n = 24) and non-lesional temporal lobe epilepsy (n = 24) with respect to patients with focal extratemporal lobe epilepsies (n = 20) and healthy controls (n = 30). The volumes of amygdala subnuclei were compared between groups adopting multivariate analyses of covariance and correlated with clinical variables. Additionally, a logistic regression analysis on the nuclei resulting statistically different across groups was performed. Compared with other populations, temporal lobe epilepsy with hippocampal sclerosis showed a significant atrophy of the whole amygdala (pBonferroni = 0.040), particularly the basolateral complex (pBonferroni = 0.033), while the non-lesional temporal lobe epilepsy group demonstrated an isolated hypertrophy of the medial nucleus (pBonferroni = 0.012). In both scenarios, the involved amygdala was ipsilateral to the epileptic focus. The medial nucleus demonstrated a volume increase even in extratemporal lobe epilepsies although contralateral to the seizure onset hemisphere (pBonferroni = 0.037). Non-lesional patients with psychiatric comorbidities showed a larger ipsilateral lateral nucleus compared with those without psychiatric disorders. This exploratory study corroborates the involvement of the amygdala in temporal lobe epilepsy, particularly in mesial temporal lobe epilepsy and suggests a different amygdala subnuclei engagement depending on the aetiology and lateralization of epilepsy. Furthermore, the logistic regression analysis indicated that the basolateral complex and the medial nucleus of amygdala can be helpful to differentiate temporal lobe epilepsy with hippocampal sclerosis and with MRI negative, respectively, versus controls with a consequent potential clinical yield. Finally, the present results contribute to the literature about the amygdala enlargement in temporal lobe epilepsy, suggesting that the increased volume of amygdala can be regarded as epilepsy-related structural changes common across different syndromes whose meaning should be clarified.

The worsening of neurological status that occurs early after acute ischemic stroke (AIS) remains a serious issue, and the inflammatory response plays a key role in stroke pathobiology. Recently, endovascular treatment (EVT) has revolutionized the management and outcome of patients with AIS due to either extracranial carotid disease or intracranial disease. The neutrophil-to-lymphocyte ratio (NLR) represents an easily available inflammatory biomarker. The aim of the study was to assess the relationship between the NLR at admission and the occurrence of early neurological deterioration (END) in patients with AIS who underwent EVT. Patients with AIS and proximal arterial occlusion in the anterior circulation undergoing EVT were retrospectively identified. Absolute neutrophil count (ANC) and absolute lymphocyte count (ALC) were collected from admission blood work to calculate the NLR. The study outcome was END defined as an increase in at least 4 points in NIHSS score or death between baseline and 24 h after the ischemic event. Patients included were 211, and END occurred in 30 (14.2%). Patients with older age (OR = 1.07, 95% CI: 1.02–1.13), higher serum glucose (OR = 1.01, 95% CI: 1.01–1.02), and higher NLR (OR = 1.011, 95% CI: 1.04–1.18) had an increased risk of END. The best predictive cut-off value of NLR was 6.4, and END occurred in 24.1% and 3.9% of the patients with NLR ≥ 6.4 and

Super-refractory status epilepticus (SRSE) is a status epilepticus (SE) that continues or recurs ≥24 h after the onset of anesthesia. We aimed to identify the predictors of progression to SRSE and the risk of 30-day mortality in patients with SRSE by using a machine learning technique.We reviewed consecutive SE episodes in patients aged ≥14 years at Baggiovara Civil Hospital (Modena, Italy) from 2013 to 2021. A classification and regression tree analysis was performed to develop a predictive model of progression to SRSE in SE patients. In SRSE patients, a multivariate analysis was conducted to identify predictors of 30-day mortality.We included 705 patients, 16% of whom (113/705) progressed to SRSE. Acute symptomatic hypoxic etiology and age ≤ 68.5 years predicted the highest risk (87.1%) of progression to SRSE. Etiology other than acute symptomatic hypoxic and absence of NCSE predicted the lowest risk (3.6%) of progression to SRSE. The predictive model was accurate in 96.1% of patients not evolving to SRSE and in 48.7% of those evolving to SRSE. Among patients with SRSE, 46.9% (53/113) died within 30 days compared to 25.2% (149/592) of patients without SRSE (p 0.001). Among patients with SRSE, older age was associated with increased 30-day mortality (odds ratio 1.075; 95% confidence interval: 1.031-1.112; p = 0.001).Acute symptomatic hypoxic etiology and younger age are major predictors of progression to SRSE. In patients with SRSE, older age is associated with increased risk of short-term mortality.

This study was undertaken to validate the accuracy of the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) in predicting the risk of death at 30 days in a large cohort of patients with status epilepticus (SE) using a machine learning system.We included consecutive patients with SE admitted from 2013 to 2021 at Modena Academic Hospital. A decision tree analysis was performed using the 30-day mortality as a dependent variable and the EMSE predictors as input variables. We evaluated the accuracy of EMSE in predicting 30-day mortality using the area under the receiver operating characteristic curve (AUC ROC), with 95% confidence interval (CI). We performed a subgroup analysis on nonhypoxic SE.A total of 698 patients with SE were included, with a 30-day mortality of 28.9% (202/698). The mean EMSE value in the entire population was 57.1 (SD = 36.3); it was lower in surviving compared to deceased patients (47.1, SD = 31.7 vs. 81.9, SD = 34.8; p .001). The EMSE was accurate in predicting 30-day mortality, with an AUC ROC of .782 (95% CI = .747-.816). Etiology was the most relevant predictor, followed by age, electroencephalogram (EEG), and EMSE comorbidity group B. The decision tree analysis using EMSE variables correctly predicted the risk of mortality in 77.9% of cases; the prediction was accurate in 85.7% of surviving and in 58.9% of deceased patients within 30 days after SE. In nonhypoxic SE, the most relevant predictor was age, followed by EEG, and EMSE comorbidity group B; the prediction was correct in 78.9% of all cases (89.6% in survivors and 46.1% in nonsurvivors).This validation study using a machine learning analysis shows that the EMSE is a valuable prognostic tool, and appears particularly accurate and effective in identifying patients with 30-day survival, whereas its performance in predicting 30-day mortality is lower and needs to be further improved.

Background: The study aimed to develop a model and build a nomogram to predict the probability of drug resistance in people with post-stroke epilepsy (PSE). Methods: Subjects with epilepsy secondary to ischemic stroke or spontaneous intracerebral hemorrhage were included. The study outcome was the occurrence of drug-resistant epilepsy defined according to International League Against Epilepsy criteria. Results: One hundred and sixty-four subjects with PSE were included and 32 (19.5%) were found to be drug-resistant. Five variables were identified as independent predictors of drug resistance and were included in the nomogram: age at stroke onset (odds ratio (OR): 0.941, 95% confidence interval (CI) 0.907–0.977), intracerebral hemorrhage (OR: 6.292, 95% CI 1.957–20.233), severe stroke (OR: 4.727, 95% CI 1.573–14.203), latency of PSE (>12 months, reference; 7–12 months, OR: 4.509, 95% CI 1.335–15.228; 0–6 months, OR: 99.099, 95% CI 14.873–660.272), and status epilepticus at epilepsy onset (OR: 14.127, 95% CI 2.540–78.564). The area under the receiver operating characteristic curve of the nomogram was 0.893 (95% CI: 0.832–0.956). Conclusions: Great variability exists in the risk of drug resistance in people with PSE. A nomogram based on a set of readily available clinical variables may represent a practical tool for an individualized prediction of drug-resistant PSE.

To develop a nomogram using the parameters of the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) and to evaluate its accuracy compared with the EMSE alone in the prediction of 30-day mortality in patients with status epilepticus (SE).We included a cohort of patients with SE aged ≥ 21 years admitted from 2013 to 2021. Regression coefficients from the multivariable logistic regression model were used to generate a nomogram predicting the risk of 30-day mortality. Discrimination of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUCROC) with 95% confidence interval. Internal validation was performed by bootstrap resampling.Among 698 patients with SE, the 30-day mortality rate was 28.9% (202 of 698). On the multivariable analysis, all EMSE parameters (except for the comorbidity group including metastatic solid tumor or AIDS) were associated with a significantly higher risk of 30-day mortality and were included in the nomogram. The discriminatory capability of the nomogram with bootstrap resampling (5000 resamples) had an AUCROC of 0.830 (95% confidence interval 0.798-0.862). Conversely, the AUCROC of the EMSE was 0.777 (95% confidence interval 0.742-0.813). Thus, the probability that a patient who died within 30 days from SE had a higher score than a patient who survived was 83%, indicating good discriminatory power of the nomogram. Conversely, the risk predicted using the EMSE alone was 77%. The nomogram was well calibrated.A nomogram based on EMSE parameters appears superior to the EMSE in predicting the risk of 30-day mortality after SE. The discrimination and calibration of the nomogram shows a better predictive accuracy than the EMSE alone.

BACKGROUND: The management of epilepsy in older adults has become part of daily practice because of an aging population. Older patients with epilepsy represent a distinct and more vulnerable clinical group as compared with younger patients, and they are generally under-represented in randomized placebo-controlled trials. Real-world studies can therefore be a useful complement to characterize the drug's profile. Brivaracetam is a rationally developed compound characterized by high-affinity binding to synaptic vesicle protein 2A and approved as adjunctive therapy for focal seizures in adults with epilepsy. OBJECTIVE: The aim of this study was to assess the 12-month effectiveness and tolerability of adjunctive brivaracetam in older patients (≥65 years of age) with epilepsy treated in a real-world setting. METHODS: The BRIVAFIRST (BRIVAracetam add-on First Italian netwoRk STudy) was a 12-month retrospective multicenter study including adult patients prescribed adjunctive brivaracetam. Effectiveness outcomes included the rates of seizure response (≥50% reduction in baseline seizure frequency), seizure freedom, and treatment discontinuation. Safety and tolerability outcomes included the rate of treatment discontinuation due to adverse events and the incidence of adverse events. Data were compared for patients aged ≥65 years of age ('older') vs those aged

The objective of this study was to validate the value of the Status Epilepticus Severity Score (STESS) in the prediction of the risk of in-hospital mortality in patients with nonhypoxic status epilepticus (SE) using a machine learning analysis.We included consecutive patients with nonhypoxic SE (aged ≥ 16 years) admitted from 2013 to 2021 at the Modena Academic Hospital. A decision tree analysis was performed using in-hospital mortality as a dependent variable and the STESS predictors as input variables. We evaluated the accuracy of STESS in predicting in-hospital mortality using the area under the receiver operating characteristic curve (AUROC) with 95% confidence interval (CI).Among 629 patients with SE, the in-hospital mortality rate was 23.4% (147 of 629). The median STESS in the entire cohort was 2.9 (SD 1.6); it was lower in surviving compared with deceased patients (2.7, SD 1.5 versus 3.9, SD 1.6; p 0.001). Of deceased patients, 82.3% (121 of 147) had scores of 3-6, whereas 17.7% (26 of 147) had scores of 0-2 (p 0.001). STESS was accurate in predicting mortality, with an AUROC of 0.688 (95% CI 0.641-0.734) only slightly reduced after bootstrap resampling. The most significant predictor was the seizure type, followed by age and level of consciousness at SE onset. Nonconvulsive SE in coma and age ≥ 65 years predicted a higher risk of mortality, whereas generalized convulsive SE and age 65 years were associated with a lower risk of death. The decision tree analysis using STESS variables correctly classified 90% of survivors and 34% of nonsurvivors after the SE, with an overall risk of error of 23.1%.This validation study using a machine learning system showed that STESS is a valuable prognostic tool. The score appears particularly accurate and effective in identifying patients who are alive at discharge (high negative predictive value), whereas it has a lower predictive value for in-hospital mortality.

Objective: Post-stroke epilepsy (PSE) is one of the most common causes of acquired epilepsy and accounts for about 10-15% of all newly diagnosed epilepsy cases. However, evidence about the clinical profile of antiseizure medications in the PSE setting is currently limited. Brivaracetam (BRV) is a rationally developed compound characterized by high-affinity binding to synaptic vesicle protein 2A. The aim of this study was to assess the 12-month effectiveness and tolerability of adjunctive BRV in patients with PSE treated in a real-world setting. Methods: This was a subgroup analysis of patients with PSE included in the BRIVAracetam add-on First Italian netwoRk Study (BRIVAFIRST). The BRIVAFIRST was a 12-month retrospective, multicentre study including adult patients prescribed adjunctive BRV. Effectiveness outcomes included the rates of seizure response (≥50% reduction in baseline seizure frequency), seizure‐freedom, and treatment discontinuation. Safety and tolerability outcomes included the rate of treatment discontinuation due to adverse events (AEs) and the incidence of AEs. Results: Patients with PSE included in the BRIVAFIRST were 75 and had a median age of 57 (interquartile range, 42-66) years. The median daily doses of BRV at 3, 6, and 12 months from starting treatment were 100 (100-150) mg, 125 (100-200) mg and 100 (100-200) mg, respectively. At 12 months, 32 (42.7%) patients had a reduction in their baseline seizure frequency by at least 50%, and the seizure freedom rates was 26/75 (34.7%). During the 1-year study period, 10 (13.3%) patients discontinued BRV. The reasons of treatment withdrawal were insufficient efficacy in 6 (8.0%) patients and poor tolerability in 4 (5.3%) patients. Adverse events were reported by 13 (20.3%) patients and were rated as mild in 84.6% and moderate in 15.4% of cases. Significance: Adjunctive BRV was efficacious and generally well-tolerated when used in patients with PSE in clinical practice. Adjunctive BRV can be a suitable therapeutic option for patients with PSE.

The maintenance of seizure control over time is a clinical priority in patients with epilepsy. The aim of this study was to assess the sustained seizure frequency reduction with adjunctive brivaracetam (BRV) in real-world practice. Patients with focal epilepsy prescribed add-on BRV were identified. Study outcomes included sustained seizure freedom and sustained seizure response, defined as a 100% and a ≥50% reduction in baseline seizure frequency that continued without interruption and without BRV withdrawal through the 12-month follow-up. Nine hundred ninety-four patients with a median age of 45 (interquartile range = 32-56) years were included. During the 1-year study period, sustained seizure freedom was achieved by 142 (14.3%) patients, of whom 72 (50.7%) were seizure-free from Day 1 of BRV treatment. Sustained seizure freedom was maintained for ≥6, ≥9, and 12months by 14.3%, 11.9%, and 7.2% of patients from the study cohort. Sustained seizure response was reached by 383 (38.5%) patients; 236 of 383 (61.6%) achieved sustained ≥50% reduction in seizure frequency by Day 1, 94 of 383 (24.5%) by Month 4, and 53 of 383 (13.8%) by Month 7 up to Month 12. Adjunctive BRV was associated with sustained seizure frequency reduction from the first day of treatment in a subset of patients with uncontrolled focal epilepsy.

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

the efficacy of delayed intravenous tissue plasminogen activator (tPA), beyond the 4.5 h window, is evolving. Advanced age and high admission National Institutes of Health Stroke Scale (NIHSS) score are proposed to adversely affect the outcome of delayed thrombolysis and limit the inclusion criteria. The summation of patient age and admission NIHSS score was introduced as the SPAN-100 index as a tool of prediction of the clinical outcome after acute ischemic stroke (AIS). We aimed to assess the SPAN-100 index in AIS thrombolysed patients after 4.5 h.The SPAN-100 index was applied to AIS patients receiving delayed IV thrombolysis (IVT) after 4.5 h. Patients demographics, risk factors, clinical, laboratory and radiological data, mismatch evidence, treatment onset and modality, NIHSS score at baseline and at discharge, and 3 months follow-up modified Rankin Scale (mRS) were reviewed. SPAN-100 score ≥ 100 is classified as SPAN-100 positive while score100 is SPAN-100 negative. Clinical outcomes, death and intracerebral hemorrhage (ICH) incidences were compared between SPAN-100 positive and negative groups.SPAN-100-positive delayed IVT-patients (11/136) had a 6-fold increased risk for unfavorable outcome compared to SPAN-negative patients (OR 6.34; 95% CI 1.59-25.24 p=0.004), however there was no relation between the SPAN-100 positivity and mortality or ICH.SPAN-100-positive patients are more likely to achieve non-favorable outcome with delayed IVT in comparison to the SPAN-100-negative patients. SPAN-100 index may influence the eligibility criteria of delayed thrombolysis.

Ictal respiratory disturbances have increasingly been reported, in both generalized and focal seizures, especially involving the temporal lobe. Recognition of ictal breathing impairment has gained importance for the risk of sudden unexpected death in epilepsy (SUDEP). The aim of this study was to evaluate the incidence of ictal apnea (IA) and related hypoxemia during seizures.We collected and analyzed electroclinical data from consecutive patients undergoing long-term video-electroencephalographic (video-EEG) monitoring with cardiorespiratory polygraphy. Patients were recruited at the epilepsy monitoring unit of the Civil Hospital of Baggiovara, Modena Academic Hospital, from April 2020 to February 2022.A total of 552 seizures were recorded in 63 patients. IA was observed in 57 of 552 (10.3%) seizures in 16 of 63 (25.4%) patients. Thirteen (81.2%) patients had focal seizures, and 11 of 16 patients showing IA had a diagnosis of temporal lobe epilepsy; two had a diagnosis of frontal lobe epilepsy and three of epileptic encephalopathy. Apnea agnosia was reported in all seizure types. Hypoxemia was observed in 25 of 57 (43.9%) seizures with IA, and the severity of hypoxemia was related to apnea duration. Apnea duration was significantly associated with epilepsy of unknown etiology (magnetic resonance imaging negative) and with older age at epilepsy onset (p lt; 0.001).Ictal respiratory changes are a frequent clinical phenomenon, more likely to occur in focal epilepsies, although detected even in patients with epileptic encephalopathy. Our findings emphasize the need for respiratory polygraphy during long-term video-EEG monitoring for diagnostic and prognostic purposes, as well as in relation to the potential link of ictal apnea with the SUDEP risk.

Amyotrophic lateral sclerosis (ALS) is known to represent a collection of overlapping syndromes. Various classification systems based on empirical observations have been proposed, but it is unclear to what extent they reflect ALS population substructures. We aimed to use machine-learning techniques to identify the number and nature of ALS subtypes to obtain a better understanding of this heterogeneity, enhance our understanding of the disease, and improve clinical care.In this retrospective study, we applied unsupervised Uniform Manifold Approximation and Projection [UMAP]) modelling, semi-supervised (neural network UMAP) modelling, and supervised (ensemble learning based on LightGBM) modelling to a population-based discovery cohort of patients who were diagnosed with ALS while living in the Piedmont and Valle d'Aosta regions of Italy, for whom detailed clinical data, such as age at symptom onset, were available. We excluded patients with missing Revised ALS Functional Rating Scale (ALSFRS-R) feature values from the unsupervised and semi-supervised steps. We replicated our findings in an independent population-based cohort of patients who were diagnosed with ALS while living in the Emilia Romagna region of Italy.Between Jan 1, 1995, and Dec 31, 2015, 2858 patients were entered in the discovery cohort. After excluding 497 (17%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 2361 (83%) patients were available for the unsupervised and semi-supervised analysis. We found that semi-supervised machine learning produced the optimum clustering of the patients with ALS. These clusters roughly corresponded to the six clinical subtypes defined by the Chiò classification system (ie, bulbar, respiratory, flail arm, classical, pyramidal, and flail leg ALS). Between Jan 1, 2009, and March 1, 2018, 1097 patients were entered in the replication cohort. After excluding 108 (10%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 989 patients were available for the unsupervised and semi-supervised analysis. All 1097 patients were included in the supervised analysis. The same clusters were identified in the replication cohort. By contrast, other ALS classification schemes, such as the El Escorial categories, Milano-Torino clinical staging, and King's clinical stages, did not adequately label the clusters. Supervised learning identified 11 clinical parameters that predicted ALS clinical subtypes with high accuracy (area under the curve 0·982 [95% CI 0·980-0·983]).Our data-driven study provides insight into the ALS population substructure and confirms that the Chiò classification system successfully identifies ALS subtypes. Additional validation is required to determine the accuracy and clinical use of these algorithms in assigning clinical subtypes. Nevertheless, our algorithms offer a broad insight into the clinical heterogeneity of ALS and help to determine the actual subtypes of disease that exist within this fatal neurodegenerative syndrome. The systematic identification of ALS subtypes will improve clinical care and clinical trial design.US National Institute on Aging, US National Institutes of Health, Italian Ministry of Health, European Commission, University of Torino Rita Levi Montalcini Department of Neurosciences, Emilia Romagna Regional Health Authority, and Italian Ministry of Education, University, and Research.For the Italian and German translations of the abstract see Supplementary Materials section.

Knowledge regarding consequences among status epilepticus (SE) survivors is still scarce. We assessed the risk of recurrence in a cohort of first-ever adult SE survivors, comparing the clinical features of patients with recurrent and incident events.We reviewed our prospective register of consecutive SE patients, from September 1st 2013 to September 1st 2020. We excluded post-anoxic events and those patients with a SE prior the study period. We examined the effect of clinical predictors on the risk of subsequent SE through Cox proportional hazard regression, while the risk of recurrence was estimated through a survival analysis.430 patients were considered (mean follow-up: 23.3 months). 44 patients experienced SE recurrence, whereas 386 patients presented an isolated event. The highest risk of recurrence was observed within 6 months from the index event (7.9%), whereas the cumulative recurrence rate was 9.5%, 13%, and 20.5% at 6 months, 1 year, and 4-years respectively. SE recurrence was independently associated to remote (HR 2.8 - 95% CI 1.4 to 6.0) or progressive symptomatic etiologies (HR 3.9 - 95% CI 1.8 to 8.7) and it was higher for Super-Refractory SE (SRSE) cases (HR 3.3 - 95% CI 1.4 to 7.8). High STESS values (p = 0.01) and SE refractoriness (p = 0.01) were associated with early relapses (within 6 months from the index event).SE recurrence involved a significantly proportion of our cohort. Etiology other than acute symptomatic and SRSE were independently associated with a higher risk of recurrence, in particular within 6 months from the index event.

New onset refractory status epilepticus (NORSE), is a rare and challenging condition occurring in previously healthy people. The etiology often remains undiscovered and is frequently associated with an unfavorable outcome. We report the electroclinical and neuroradiological evolution of an ultra-long case of NORSE of unknown etiology. A 38-year-old woman with a prodrome of fever, vomiting and diarrhea was admitted to our Intensive Care Unit for refractory convulsive status epilepticus (SE). Her past medical history was unremarkable. Extensive examinations were negative for potential viral, autoimmune and metabolic etiologies. Despite multiple therapeutical attempts with antiseizures medications, anesthetics and immunotherapy, seizures persisted. After nearly 6 months of enduring seizures, SE finally ceased and the patient gradually recovered to a minimum state of awareness. She was then able to communicate through one-word utterances and to understand simple tasks. At a three-years follow-up, she developed multifocal drug-resistant epilepsy, subcortical myoclonus and severe spastic quadraparesis, becoming completely dependent for activities of daily living. To our knowledge, this represents one of the longest cases of NORSE with final status resolution at this time. However, ultra-long SE in this case led to severe and disabling neurological sequelae. Future studies focused on disease modifying treatments for refractory SE are needed.

The altered numbers and functions of cells belonging to immunoregulatory cell networks such as T regulatory (Tregs) and invariant Natural Killer T (iNKT) cells have been reported in Multiple Sclerosis (MS), an immune-mediated disease. We aimed to assess the frequencies of Tregs and iNKT cells in MS patients throughout a one-year treatment with fingolimod (FTY) and to correlate immunological data with efficacy and safety data. The percentage of Tregs (defined as Live Dead-CD3 + CD4 + FoxP3 + CD25++/CD127− cells) increased steadily throughout the year, while there was no significant difference in the absolute number or percentage of iNKT cells (defined as CD3 + CD14−CD19− Vα24-Jα18 TCR+ cells). However, out of all the iNKT cells, the CD8+ iNKT and CD4−CD8− double-negative (DN) cell percentages steadily increased, while the CD4+ iNKT cell percentages decreased significantly. The mean percentage of CD8+ T cells at all time-points was lower in patients with infections throughout the study. The numbers and percentages of DN iNKT cells were more elevated, considering all time-points, in patients who presented a clinical relapse. FTY may, therefore, exert its beneficial effect in MS patients through various mechanisms, including the increase in Tregs and in iNKT subsets with immunomodulatory potential such as CD8+ iNKT cells. The occurrence of infections was associated with lower mean CD8+ cell counts during treatment with FTY.

Developmental and epileptic encephalopathies are a group of rare, severe epilepsies, which are characterized by refractory seizures starting in infancy or childhood and developmental delay or regression. Developmental changes might be independent of epilepsy. However, interictal epileptic activity and seizures can further deteriorate cognition and behavior. Recently, the concept of developmental and epileptic encephalopathies has moved from the lesions associated with epileptic encephalopathies toward the epileptic network dysfunctions on the functioning of the brain. Early recognition and differentiation of patients with developmental and epileptic encephalopathies is important, as precision therapies need to be holistic to address the often devastating symptoms. In this review, we discuss the evolution of the concept of developmental and epileptic encephalopathies in recent years, as well as the current understanding of the genetic basis of developmental and epileptic encephalopathies. Finally, we will discuss the role of epileptic network dysfunctions on prognosis for these severe conditions.