Late-onset fabry disease due to the p.Phe113Leu variant: the first italian cluster of five families.

BACKGROUND: The GLA c.337T > C (p.Phe113Leu) is a known pathogenic variant associated to late-onset Fabry disease phenotype with predominant cardiac manifestations. A founder effect was demonstrated in a large cohort in the Portuguese region of Guimarães. Herein we report an in-depth phenotype description of a cluster of five Southern Italy families. METHODS: Family pedigrees of five index males with the p.Phe113Leu variant were obtained and all at-risk relatives underwent biochemical and genetical screening test. Carriers of GLA p.Phe113Leu variant underwent subsequent multidisciplinary clinical and instrumental evaluation. RESULTS: Thirty-one (16 M, 15 F) individuals with p.Phe113Leu pathogenic variant were identified. Sixteen out of 31 patients (51.6%) had cardiac manifestations. Notably, myocardial fibrosis was found in 7/8 patients, of whom 2 were under 40 years. Stroke occurred in 4 patients. White matter lesions were detected in 12/19 patients and occurred in 2/10 of subjects under 40 years. Seven females complained of acroparesthesias. Renal involvement occurred in 10 patients. Angiokeratomas were evident in 9 subjects. Eyes, ear, gastrointestinal and pulmonary involvement occurred in the minority of subjects. CONCLUSION: This study demonstrates that a cluster of subjects with p.Phe113Leu pathogenic variant is also present in Southern Italy. Disease manifestations are frequent in both sexes and may occur early in life. Cardiac involvement represents the core manifestation, but neurological and renal involvement is also frequent, suggesting that extra-cardiac complications deserve clinical attention.

Late epileptic seizures following cerebral venous thrombosis: a systematic review and meta-analysis.

BACKGROUND: Identifying late epileptic seizures (LS) following cerebral venous thrombosis (CVT) can be useful for prognosis and management. We systematically reviewed the literature to identify risk factors for LS due to CVT. METHODS: We systematically searched PubMed, Scholar, and Scopus databases (May 2021) to identify studies reporting data on prevalence and risk factors for CVT-LS. The methodological quality was assessed with the Ottawa-Newcastle Scale. The risk of developing CVT-LS was summarized in meta-analyses and expressed as odds ratio (OR) and corresponding 95% confidence intervals (CIs) using random-effects models. RESULTS: Out of the 332 records retrieved, four studies were eventually included with a total of 1309 patients with CVT and 142 (11%) with CVT-LS. The most relevant predictors of CVT-LS were symptomatic seizures (OR 5.66, 95% CI 3.83-8.35), stupor/coma (OR 6.81, 95% CI 1.18-39.20), focal neurologic signs (OR 6.81, 95% CI 1.18-39.2), hemorrhagic component (OR 3.52, 95% CI 2.45-5.06), and superior sagittal sinus involvement (OR 1.52, 95% CI 1.04-2.21). CONCLUSION: There are several risk factors for CVT-LS that should be considered in clinical practice. Further high-quality studies are warranted to develop predictive models for individualized risk stratification and prediction of CVT-LS.

Rapid versus slow withdrawal of antiepileptic monotherapy in two-year seizure-free adults patients with epilepsy (RASLOW) study: A pragmatic multicentre, prospective, randomized, controlled study.

PURPOSE: To establish whether a slow or a rapid withdrawal of antiepileptic monotherapy influences relapse rate in seizure-free adults with epilepsy and calculates compliance and differences in the severity of relapses, based on the occurrence of status epilepticus, seizure-related injuries, and death. METHODS: This is a multicentre, prospective, randomized, open label, non-inferiority trial in people aged 16 + years who were seizure-free for more than 2 years. Patients were randomized to slow withdrawal (160 days) or rapid withdrawal (60 days) and were followed for 12 months. The primary outcome was the probability of a first seizure relapse within the 12-months follow-up. The secondary outcomes included the cumulative probability of relapse at 3, 6, 9, and 12 months. A non-inferiority analysis was performed with non-inferiority margin of - 0.15 for the difference between the probabilities of seizure recurrence in slow versus rapid withdrawal. RESULTS: The sample comprised 48 patients, 25 randomized to slow withdrawal and 23 to rapid withdrawal. Median follow-up was 11.9 months. In the intention-to-treat population, 3 patients in the slow-withdrawal group and 1 in the rapid withdrawal group experienced seizure relapses. The corresponding probabilities of seizure recurrence were 0.12 for slow withdrawal and 0.04 for rapid withdrawal, giving a difference of 0.08 (95% CI - 0.12; 0.27), which is entirely above the non-inferiority margin. No patients developed status epilepticus and seizure-related injuries or died. Risks were similar in the Per-Protocol population. CONCLUSIONS: Seizure-relapse rate after drug discontinuation is lower than in other reports, without complications and unrelated to the duration of tapering.

Late-onset Fabry disease due to a new (p.Pro380Leu) pathogenic variant of GLA Gene.

Fabry disease is a rare X-linked lysosomal storage disorder due to pathogenic variants of the galactosidase alpha (GLA) gene, leading to a deficiency of alpha-galactosidase A. The inadequate enzymatic activity leads to progressive glycosphingolipids accumulation within tissues and subsequent multi-systemic dysfunction, with predominant involvement of heart, kidney, and nervous system. Two subtypes are recognized: the classic type and the late-onset type. We here describe the clinical characteristics of a patient with late-onset Fabry disease carrying a not previously identified GLA gene variant. This 50-year-old man came to hospital because of an acute ischemic stroke. He also complained of acroparesthesia and had angiokeratomas in the nape and the back. Blood alpha-galactosidase A activity was low, plasmatic lyso-Gb3 level was borderline, cardiac MRI showed cardiac fibrosis, brain MRI documented cerebrovascular disease, and skin biopsy revealed small fiber neuropathy without globotriaosylceramide-3 skin deposits. Genetic study by means of targeted next-generation sequencing analysis disclosed a missense substitution c.1139C>T (p.Pro380Leu) in the GLA gene. We suggest that this novel variant should be considered as pathogenic and associated with a late-onset variant of Fabry disease with a predominant neurological phenotype.

Permutation Entropy-Based Interpretability of Convolutional Neural Network Models for Interictal EEG Discrimination of Subjects with Epileptic Seizures vs. Psychogenic Non-Epileptic Seizures.

The differential diagnosis of epileptic seizures (ES) and psychogenic non-epileptic seizures (PNES) may be difficult, due to the lack of distinctive clinical features. The interictal electroencephalographic (EEG) signal may also be normal in patients with ES. Innovative diagnostic tools that exploit non-linear EEG analysis and deep learning (DL) could provide important support to physicians for clinical diagnosis. In this work, 18 patients with new-onset ES (12 males, 6 females) and 18 patients with video-recorded PNES (2 males, 16 females) with normal interictal EEG at visual inspection were enrolled. None of them was taking psychotropic drugs. A convolutional neural network (CNN) scheme using DL classification was designed to classify the two categories of subjects (ES vs. PNES). The proposed architecture performs an EEG time-frequency transformation and a classification step with a CNN. The CNN was able to classify the EEG recordings of subjects with ES vs. subjects with PNES with 94.4% accuracy. CNN provided high performance in the assigned binary classification when compared to standard learning algorithms (multi-layer perceptron, support vector machine, linear discriminant analysis and quadratic discriminant analysis). In order to interpret how the CNN achieved this performance, information theoretical analysis was carried out. Specifically, the permutation entropy (PE) of the feature maps was evaluated and compared in the two classes. The achieved results, although preliminary, encourage the use of these innovative techniques to support neurologists in early diagnoses.

Comorbidities in patients with epilepsy: Frequency, mechanisms and effects on long-term outcome.

OBJECTIVE: To assess frequency, types, and mechanisms of comorbidities in people with epilepsy and verify their association with disease features and outcome. METHODS: This cohort study was performed in 13 Italian epilepsy centers with nationwide distribution and accurate records. Eligible patients were children and adults diagnosed before December 31, 2005, and followed for a minimum of 10 years. Two pairs of raters independently reviewed patients' records and classified each comorbidity. In case of disagreement, a third reviewer made the final decision. Comorbidities were classified according to type (organ/system) and underlying mechanism (causal, shared risk factors, chance association). Comorbidity types and mechanisms were described in the entire sample and according to epilepsy prognostic patterns (sustained remission, relapsing-remitting course, no remission). RESULTS: Of 1006 included patients, 266 (26.4%) had at least one comorbidity. The most common were developmental/perinatal (7.5% of cases), psychiatric (6.2%), cardiovascular (5.3%), and endocrine/metabolic (3.8%). Among 408 reported comorbidities, the underlying mechanisms were, in decreasing order, chance association (42.2%), shared risk factors (31.1%), and causal (26.7%). Psychiatric diseases were present in 13.3% of patients with no remission, 5.9% of patients with relapsing-remitting course, and 4.8% of patients with sustained remission (p = .016). The corresponding numbers for endocrine/metabolic diseases were respectively, 9.6%, 3.4%, and 2.9% (p = .013); for respiratory diseases were 3.6%, .3%, and .3% (p = .001), and for urogenital diseases were 3.6%, .7%, and 1.6% (p = .048). The association of endocrine/metabolic, psychiatric, and respiratory comorbidities with epilepsy prognosis was confirmed by multivariable analysis adjusted for the main demographic and clinical variables, with patients with these comorbidities showing a lower probability of achieving remission. SIGNIFICANCE: Comorbidities in epilepsy are not uncommon and reflect differing underlying mechanisms. Psychiatric, endocrine/metabolic, and respiratory disorders are associated with a worse long-term epileptological outcome.

Discontinuation of antiseizure medications in seizure-free patients with long-term follow-up: Patients' profile, seizure recurrence, and risk factors.

OBJECTIVE: To compare withdrawal of antiseizure medications (ASM) to continued treatment in newly diagnosed individuals achieving seizure freedom, and assess the risk of relapse and factors associated with relapse. METHODS: This is a multicenter retrospective cohort study with long-term follow-up. Patients with newly diagnosed epilepsy were identified from the medical records of 13 Italian epilepsy centers and followed up until the most recent visit or death. Seizure-free patients discontinuing treatment were compared to patients who maintained treatment for baseline characteristics. Treatment was stopped upon clinical judgment. The probability of relapse was calculated with the Kaplan-Meier method. Demographic, clinical, and instrumental variables associated with relapse were assessed with Cox proportional hazards models. RESULTS: One thousand and six patients aged 1 month to 72 years at diagnosis were enrolled and followed up for 17,892 person-years (median follow-up, 9.9 years). Three hundred and twenty patients (31.8%) underwent one or more treatment discontinuations. Factors associated with ASM withdrawal were younger age at remission and normal psychiatric examination. The probability of relapse after the first withdrawal was 16% at six months, 24% at 12 months, and 36%, 45%, and 53% at three, five, and ten years, respectively. The probability of remission after the first relapse was 59% at one month, 67%, 72, and 76% at three, six, and 12 months, respectively. Variables associated with relapse were age 14+ years, structural etiology, abnormal neuroimaging, ASM initiation after a single seizure, and symptomatic/cryptogenic epilepsy. CONCLUSIONS: About one half of seizure-free patients stopping ASM relapse in 10 years. However, the possibility of remission after relapse is high, particularly in children and patients with idiopathic/cryptogenic epilepsy. Treatment deprescription might be encouraged at least in these patients.

Different circuitry dysfunction in drug-naive patients with juvenile myoclonic epilepsy and juvenile absence epilepsy.

RATIONALE: Juvenile myoclonic epilepsy (JME) and juvenile absence epilepsy (JAE) are generalized epileptic syndromes presenting in the same age range. To explore whether uneven network dysfunctions may underlie the two different phenotypes, we examined drug-naive patients with JME and JAE at the time of their earliest presentation. METHODS: Patients were recruited based on typical JME (n = 23) or JAE (n = 18) presentation and compared with 16 age-matched healthy subjects (HS). We analyzed their awake EEG signals by Partial Directed Coherence and graph indexes. RESULTS: Out-density and betweenness centrality values were different between groups. With respect to both JAE and HS, JME showed unbalanced out-density and out-strength in alpha and beta bands on central regions and reduced alpha out-strength from fronto-polar to occipital regions, correlating with photosensitivity. With respect to HS, JAE showed enhanced alpha out-density and out-strength on fronto-polar regions. In gamma band, JAE showed reduced Global/Local Efficiency and Clustering Coefficient with respect to HS, while JME showed more scattered values. CONCLUSIONS: Our data suggest that regional network changes in alpha and beta bands underlie the different presentation distinguishing JME and JAE resulting in motor vs non-motor seizures characterizing these two syndromes. Conversely, impaired gamma-activity within the network seems to be a non-local marker of defective inhibition.

A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls.

Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures (PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help differentiate PNES cases from healthy subjects. In this paper, we have investigated the power spectrum density (PSD), in resting-state EEGs, to evaluate the abnormalities in PNES affected brains. Additionally, we have used functional connectivity tools, such as phase lag index (PLI), and graph-derived metrics to better observe the integration of distributed information of regular and synchronized multi-scale communication within and across inter-regional brain areas. We proved the utility of our method after enrolling a cohort study of 20 age- and gender-matched PNES and 19 healthy control (HC) subjects. In this work, three classification models, namely support vector machine (SVM), linear discriminant analysis (LDA), and Multilayer perceptron (MLP), have been employed to model the relationship between the functional connectivity features (rest-HC versus rest-PNES). The best performance for the discrimination of participants was obtained using the MLP classifier, reporting a precision of 85.73%, a recall of 86.57%, an F1-score of 78.98%, and, finally, an accuracy of 91.02%. In conclusion, our results hypothesized two main aspects. The first is an intrinsic organization of functional brain networks that reflects a dysfunctional level of integration across brain regions, which can provide new insights into the pathophysiological mechanisms of PNES. The second is that functional connectivity features and MLP could be a promising method to classify rest-EEG data of PNES form healthy controls subjects.

Younger age at stroke onset but not thrombolytic treatment predicts poststroke epilepsy: An updated meta-analysis.

AIMS: Stroke is the most commonly identified cause of late-onset epilepsy. Risk factors for poststroke epilepsy (PSE) are partially elucidated, and many studies have been performed in recent years. We aimed to update our previous systematic review and meta-analysis on risk factors for PSE. METHODS: PubMed, Google Scholar, and Scopus databases were searched. Articles published in English (1987-2019) were included. Odds ratios (OR) and mean values were calculated for examined variables. RESULTS: Thirty studies with different designs were included, enrolling 26,045 patients who experienced stroke, of whom 1800 had PSE, corresponding to a prevalence of 7%. Cortical lesions (OR: 3.58, 95% confidence interval (CI): 2.35-5.46, p < 0.001), hemorrhagic component (OR: 2.47, 95% CI: 1.68-3.64, p < 0.001), early seizures (ES) (OR: 4.88, 95% CI: 3.08-7.72, p < 0.001), and younger age at stroke onset (difference in means: 2.97 years, 95% CI: 0.78 to 5.16, p = 0.008) favor PSE. Sex and acute treatment with recombinant tissue plasminogen activator (rtPA) do not predict the occurrence of PSE. CONCLUSION: Despite limitations due to the uneven quality and design of the studies, the present meta-analysis confirms that cortical involvement, hemorrhagic component, and ES are associated with a higher risk of PSE. In this update, younger age at stroke onset but not thrombolytic treatment seems to increase the risk for PSE. This article is part of the Special Issue "Seizures & Stroke".

Incidence of early poststroke seizures during reperfusion therapies in patients with acute ischemic stroke: An observational prospective study: (TESI study: "Trombolisi/Trombectomia e crisi Epilettiche precoci nello Stroke Ischemico").

INTRODUCTION: The aim of this study was to prospectively investigate the occurrence of early poststroke seizures (within 7 days of stroke) in patients undergoing reperfusion therapies (intravenous rtPA [recombinant tissue plasminogen activator] and/or endovascular thrombectomy) in comparison to those not undergoing these procedures. METHODS: Patients aged ≥18 years with acute ischemic stroke admitted in five Italian centers were prospectively recruited. Clinical data, details on stroke type and etiology, stroke treatment, and radiological data were collected. The frequency of early poststroke seizures was assessed, and predictive factors for their occurrence were evaluated. RESULTS: Five hundred and sixteen patients (262 in the reperfusion therapies group) were included. Stroke severity on admission and at discharge was higher among patients undergoing reperfusion therapies. Ten patients (3.8%) undergoing reperfusion therapies and 6 (2.3%) of those not receiving these treatments experienced early poststroke seizures (p = 0.45). There were no differences in any of the baseline characteristics between patients experiencing and those not experiencing early seizures. CONCLUSION: The incidence of early poststroke seizures was overall rare, and no significant differences emerged between patients receiving and those not receiving reperfusion therapies. This article is part of the Special Issue "Seizures and Stroke".

Antidepressant effect of vagal nerve stimulation in epilepsy patients: a systematic review.

BACKGROUND: Vagal nerve stimulation (VNS) is an effective palliative therapy in drug-resistant epileptic patients and is also approved as a therapy for treatment-resistant depression. Depression is a frequent comorbidity in epilepsy and it affects the quality of life of patients more than the seizure frequency itself. The aim of this systematic review is to analyze the available literature about the VNS effect on depressive symptoms in epileptic patients. MATERIAL AND METHODS: A comprehensive search of PubMed, Medline, Scopus, and Google Scholar was performed, and results were included up to January 2020. All studies concerning depressive symptom assessment in epileptic patients treated with VNS were included. RESULTS: Nine studies were included because they fulfilled inclusion criteria. Six out of nine papers reported a positive effect of VNS on depressive symptoms. Eight out of nine studies did not find any correlation between seizure reduction and depressive symptom amelioration, as induced by VNS. Clinical scales for depression, drug regimens, and age of patients were broadly different among the examined studies. CONCLUSIONS: Reviewed studies strongly suggest that VNS ameliorates depressive symptoms in drug-resistant epileptic patients and that the VNS effect on depression is uncorrelated to seizure response. However, more rigorous studies addressing this issue are encouraged.

A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects.

The diagnosis of psychogenic nonepileptic seizures (PNES) by means of electroencephalography (EEG) is not a trivial task during clinical practice for neurologists. No clear PNES electrophysiological biomarker has yet been found, and the only tool available for diagnosis is video EEG monitoring with recording of a typical episode and clinical history of the subject. In this paper, a data-driven machine learning (ML) pipeline for classifying EEG segments (i.e., epochs) of PNES and healthy controls (CNT) is introduced. This software pipeline consists of a semiautomatic signal processing technique and a supervised ML classifier to aid clinical discriminative diagnosis of PNES by means of an EEG time series. In our ML pipeline, statistical features like the mean, standard deviation, kurtosis, and skewness are extracted in a power spectral density (PSD) map split up in five conventional EEG rhythms (delta, theta, alpha, beta, and the whole band, i.e., 1-32 Hz). Then, the feature vector is fed into three different supervised ML algorithms, namely, the support vector machine (SVM), linear discriminant analysis (LDA), and Bayesian network (BN), to perform EEG segment classification tasks for CNT vs. PNES. The performance of the pipeline algorithm was evaluated on a dataset of 20 EEG signals (10 PNES and 10 CNT) that was recorded in eyes-closed resting condition at the Regional Epilepsy Centre, Great Metropolitan Hospital of Reggio Calabria, University of Catanzaro, Italy. The experimental results showed that PNES vs. CNT discrimination tasks performed via the ML algorithm and validated with random split (RS) achieved an average accuracy of 0.97 ± 0.013 (RS-SVM), 0.99 ± 0.02 (RS-LDA), and 0.82 ± 0.109 (RS-BN). Meanwhile, with leave-one-out (LOO) validation, an average accuracy of 0.98 ± 0.0233 (LOO-SVM), 0.98 ± 0.124 (LOO-LDA), and 0.81 ± 0.109 (LOO-BN) was achieved. Our findings showed that BN was outperformed by SVM and LDA. The promising results of the proposed software pipeline suggest that it may be a valuable tool to support existing clinical diagnosis.

Establishment and characterization of induced pluripotent stem cells (iPSCs) from central nervous system lupus erythematosus.

Involvement of the central nervous system (CNS) is an uncommon feature in systemic lupus erythematosus (SLE), making diagnosis rather difficult and challenging due to the poor specificity of neuropathic symptoms and neurological symptoms. In this work, we used human-induced pluripotent stem cells (hiPSCs) derived from CNS-SLE patient, with the aim to dissect the molecular insights underlying the disease by gene expression analysis and modulation of implicated pathways. CNS-SLE-derived hiPSCs allowed us to provide evidence of Erk and Akt pathways involvement and to identify a novel cohort of potential biomarkers, namely CHCHD2, IDO1, S100A10, EPHA4 and LEFTY1, never reported so far. We further extended the study analysing a panel of oxidative stress-related miRNAs and demonstrated, under normal or stress conditions, a strong dysregulation of several miRNAs in CNS-SLE-derived compared to control hiPSCs. In conclusion, we provide evidence that iPSCs reprogrammed from CNS-SLE patient are a powerful useful tool to investigate the molecular mechanisms underlying the disease and to eventually develop innovative therapeutic approaches.

Prognostic patterns and predictors in epilepsy: a multicentre study (PRO-LONG).

OBJECTIVES: To describe the long-term prognosis of epilepsy and prognostic patterns in a large cohort of newly diagnosed patients and identify prognostic factors. METHODS: Study participants were 13 Italian epilepsy centres with accessible records dating back to 2005 or earlier, complete data on seizure outcome and treatments, precise epilepsy diagnosis, and follow-up of at least 10 years. Records were examined by trained neurology residents for demographics, seizure characteristics, neurological signs, psychiatric comorbidity, first electroencephalogram (EEG) and MRI/CT, epilepsy type and aetiology, antiepileptic drugs (AEDs), and 1-year, 2-year, 5-year and 10-year seizure remissions. Five predefined prognostic patterns were identified: early remission, late remission, relapsing-remitting course, worsening course and no remission. Prognostic factors were assessed using multinomial logistic regression models. RESULTS: 1006 children and adults were followed for 17 892 person-years (median 16 years; range 10-57). During follow-up, 923 patients (91.7%) experienced 1-year remission. 2-year, 5-year and 10-year remissions were present in 89.5%, 77.1% and 44.4% of cases. 5-year remission was associated with one to two seizures at diagnosis, generalised epilepsy, no psychiatric comorbidity, and treatment with one or two AEDs during follow-up. 10-year remission was associated with one or two AEDs. The most common prognostic pattern was relapsing-remitting (52.2%), followed by early remission (24.5%). 8.3% of cases experienced no remission. Predictors of a relapsing-remitting course were <6 seizures at diagnosis, (presumed) genetic aetiology and no psychiatric comorbidity. CONCLUSIONS: Few seizures at diagnosis, generalised epilepsy and no psychiatric comorbidity predict early or late seizure freedom in epilepsy. Achieving remission at any time after the diagnosis does not exclude further relapses.

Eyelid myoclonia with absences: Electroclinical features and prognostic factors.

OBJECTIVE: Eyelid myoclonia with absences (EMA) is a syndrome characterized by eyelid myoclonia with or without absences, eye closure-induced generalized electroencephalographic (EEG) paroxysms and photosensitivity. Few data are available about the prognostic factors of this syndrome. The main objectives of our study were to describe the clinical and EEG features of a group of patients with EMA and to evaluate the presence of prognostic factors. METHODS: We retrospectively selected a cohort of patients with diagnosis of EMA evaluated in the epilepsy service of the Neurological Clinic of Catania, in the Neurology and Clinical Neurophysiopathology Unit of Oasi Research Institute, Troina and in the Regional Epilepsy Centre of Bianchi-Melacrino-Morelli Hospital of Reggio Calabria. We considered the features of the patients during the first year of disease, and at the last follow-up visit. We stratified the patients into two groups: "seizure-free", defined as the absence of seizures for at least 2 years, and "not seizure-free" and we evaluated the evolution of their characteristics and the presence of factors associated with outcome. RESULTS: We enrolled 51 patients (40 women (78%); mean age: 30.8 years ± 15.5 [range 10-79]). The mean follow-up time was 8.7 ± 5.8 years. Eleven patients (21.6%) achieved the condition of seizure-free. Family history of epilepsy was associated with the condition of seizure-free (P = 0.05). At the last follow-up visit, EEG photosensitivity and eye closure sensitivity were significantly associated with the condition of "not seizure-free". SIGNIFICANCE: The results of our study revealed that a positive family history of epilepsy might be associated with a better outcome in EMA. Furthermore, the persistence of photosensitivity and eye closure sensitivity might indicate persistence of seizures, offering an aid in therapeutic management.

Hypertension, seizures, and epilepsy: a review on pathophysiology and management.

BACKGROUND: Epilepsy and hypertension are common chronic conditions, both showing high prevalence in older age groups. This review outlines current experimental and clinical evidence on both direct and indirect role of hypertension in epileptogenesis and discusses the principles of drug treatment in patients with hypertension and epilepsy. METHODS: We selected English-written articles on epilepsy, hypertension, stroke, and cerebrovascular disease until December, 2018. RESULTS: Renin-angiotensin system might play a central role in the direct interaction between hypertension and epilepsy, but other mechanisms may be contemplated. Large-artery stroke, small vessel disease and posterior reversible leukoencephalopathy syndrome are hypertension-related brain lesions able to determine epilepsy by indirect mechanisms. The role of hypertension as an independent risk factor for post-stroke epilepsy has not been demonstrated. The role of hypertension-related small vessel disease in adult-onset epilepsy has been demonstrated. Posterior reversible encephalopathy syndrome is an acute condition, often caused by a hypertensive crisis, associated with the occurrence of acute symptomatic seizures. Chronic antiepileptic treatment should consider the risk of drug-drug interactions with antihypertensives. CONCLUSIONS: Current evidence from preclinical and clinical studies supports the vision that hypertension may be a cause of seizures and epilepsy through direct or indirect mechanisms. In both post-stroke epilepsy and small vessel disease-associated epilepsy, chronic antiepileptic treatment is recommended. In posterior reversible encephalopathy syndrome blood pressure must be rapidly lowered and prompt antiepileptic treatment should be initiated.

Management of epilepsy in brain tumors.

Epilepsy in brain tumors (BTE) may require medical attention for a variety of unique concerns: epileptic seizures, possible serious adverse effects of antineoplastic and antiepileptic drugs (AEDs), physical disability, and/or neurocognitive disturbances correlated to tumor site. Guidelines for the management of tumor-related epilepsies are lacking. Treatment is not standardized, and overall management might differ according to different specialists. The aim of this document was to provide directives on the procedures to be adopted for a correct diagnostic-therapeutic path of the patient with BTE, evaluating indications, risks, and benefits. A board comprising neurologists, epileptologists, neurophysiologists, neuroradiologists, neurosurgeons, neuro-oncologists, neuropsychologists, and patients' representatives was formed. The board converted diagnostic and therapeutic problems into seventeen questions. A literature search was performed in September-October 2017, and a total of 7827 unique records were retrieved, of which 148 constituted the core literature. There is no evidence that histological type or localization of the brain tumor affects the response to an AED. The board recommended to avoid enzyme-inducing antiepileptic drugs because of their interference with antitumoral drugs and consider as first-choice newer generation drugs (among them, levetiracetam, lamotrigine, and topiramate). Valproic acid should also be considered. Both short-term and long-term prophylaxes are not recommended in primary and metastatic brain tumors. Management of seizures in patients with BTE should be multidisciplinary. The panel evidenced conflicting or lacking data regarding the role of EEG, the choice of therapeutic strategy, and timing to withdraw AEDs and recommended high-quality long-term studies to standardize BTE care.