Implications for driving based on the risk of seizures after ischaemic stroke.

BACKGROUND: In addition to other stroke-related deficits, the risk of seizures may impact driving ability after stroke. METHODS: We analysed data from a multicentre international cohort, including 4452 adults with acute ischaemic stroke and no prior seizures. We calculated the Chance of Occurrence of Seizure in the next Year (COSY) according to the SeLECT2.0 prognostic model. We considered COSY<20% safe for private and <2% for professional driving, aligning with commonly used cut-offs. RESULTS: Seizure risks in the next year were mainly influenced by the baseline risk-stratified according to the SeLECT2.0 score and, to a lesser extent, by the poststroke seizure-free interval (SFI). Those without acute symptomatic seizures (SeLECT2.0 0-6 points) had low COSY (0.7%-11%) immediately after stroke, not requiring an SFI. In stroke survivors with acute symptomatic seizures (SeLECT2.0 3-13 points), COSY after a 3-month SFI ranged from 2% to 92%, showing substantial interindividual variability. Stroke survivors with acute symptomatic status epilepticus (SeLECT2.0 7-13 points) had the highest risk (14%-92%). CONCLUSIONS: Personalised prognostic models, such as SeLECT2.0, may offer better guidance for poststroke driving decisions than generic SFIs. Our findings provide practical tools, including a smartphone-based or web-based application, to assess seizure risks and determine appropriate SFIs for safe driving.

Exploratory study of blood biomarkers in patients with post-stroke epilepsy.

INTRODUCTION: In addition to clinical factors, blood-based biomarkers can provide useful information on the risk of developing post-stroke epilepsy (PSE). Our aim was to identify serum biomarkers at stroke onset that could contribute to predicting patients at higher risk of PSE. PATIENTS AND METHODS: From a previous study in which 895 acute stroke patients were followed-up, 51 patients developed PSE. We selected 15 patients with PSE and 15 controls without epilepsy. In a biomarker discovery setting, 5 Olink panels of 96 proteins each, were used to determine protein levels. Biomarkers that were down-regulated and overexpressed in PSE patients, and those that showed the strongest interactions with other proteins were validated using an enzyme-linked immunosorbent assay in samples from 50 PSE patients and 50 controls. A ROC curve analysis was used to evaluate the predictive ability of significant biomarkers to develop PSE. RESULTS: Mean age of the PSE discovery cohort was 68.56 ± 15.1, 40% women and baseline NIHSS 12 [IQR 1-25]. Nine proteins were down-expressed: CASP-8, TNFSF-14, STAMBP, ENRAGE, EDA2R, SIRT2, TGF-alpha, OSM and CLEC1B. VEGFa, CD40 and CCL4 showed greatest interactions with the remaining proteins. In the validation analysis, TNFSF-14 was the single biomarker showing statistically significant downregulated levels in PSE patients (p = 0.006) and it showed a good predictive capability to develop PSE (AUC 0.733, 95% CI 0.601-0.865). DISCUSSION AND CONCLUSION: Protein expression in PSE patients differs from that of non-epileptic stroke patients, suggesting the involvement of several different proteins in post-stroke epileptogenesis. TNFSF-14 emerges as a potential biomarker for predicting PSE.

Antiseizure medication withdrawal in adult patients with idiopathic generalized epilepsy: Performance of two seizure recurrence prediction models.

PURPOSE: Currently, there is a limited availability of tools to predict seizure recurrence after discontinuation of antiseizure medications (ASMs). This study aimed to establish the seizure recurrence rate following ASM cessation in adult patients with idiopathic generalized epilepsy (IGE) and to assess the predictive performance of the Lamberink and the Stevelink prediction models using real-world data. METHODS: Retrospective longitudinal study in IGE patients who underwent ASM withdrawal in a tertiary epilepsy clinic since June 2011, with the latest follow up in January 2024. The minimum follow-up period was 12 months. Clinical and demographic variables were collected, and the seizure recurrence prediction models proposed by Lamberink and Stevelink were applied and evaluated. RESULTS: Forty-seven patients (mean age 33.15 ± 8 [20-55] years; 72.35 % women) were included. During the follow-up period, seizures recurred in 25 patients (53.2 %). Median time to recurrence was 8 months [IQR 3-13.5 months], and 17 patients (68 %) relapsed within the first year. None of the relapsing patients developed drug-resistant epilepsy. The only significant risk factor associated with recurrence was a seizure-free period of less than 2 years before discontinuing medication (91.7 % vs 40 %, p =.005). The Stevelink prediction model at both 2 (p =.015) and 5 years (p =.020) achieved statistical significance, with an AUC of 0.72 (95 % CI 0.56-0.88), while the Lamberink model showed inadequate prognostic capability. CONCLUSION: In our real-world cohort, a seizure-free period of at least 2 years was the only factor significantly associated with epilepsy remission after ASM withdrawal. Larger studies are needed to accurately predict seizure recurrence in IGE patients.

Predictive Model for Estimating the Risk of Epilepsy After Aneurysmal Subarachnoid Hemorrhage: The RISE Score.

BACKGROUND AND OBJECTIVES: The occurrence of seizures after aneurysmal subarachnoid hemorrhage (aSAH) is associated with a poorer functional and cognitive prognosis and less favorable quality of life. It would be of value to promptly identify patients at risk of epilepsy to optimize follow-up protocols and design preventive strategies. Our aim was to develop a predictive score to help stratify epilepsy risk in patients with aSAH. METHODS: This is a retrospective, longitudinal study of all adults with aSAH admitted to our center (2012-2021). We collected demographic data, clinical and radiologic variables, data on early-onset seizures (EOSs), and data on development of epilepsy. Exclusion criteria were previous structural brain lesion, epilepsy, and ≤7 days' follow-up. Multiple Cox regression was used to evaluate factors independently associated with unprovoked remote seizures (i.e., epilepsy). The best fitting regression model was used to develop a predictive score. Performance was evaluated in an external validation cohort of 308 patients using receiver-operating characteristic curve analysis. RESULTS: From an initial database of 743 patients, 419 met the inclusion criteria and were included in the analysis. The mean age was 60 ± 14 years, 269 patients (64%) were women, and 50 (11.9%) developed epilepsy within a median follow-up of 4.2 years. Premorbid modified Rankin Score (mRS) (hazard ratio [HR] 4.74 [1.8-12.4], p = 0.001), VASOGRADE score (HR 2.45 [1.4-4.2], p = 0.001), surgical treatment (HR 2.77 [1.6-4.9], p = 0.001), and presence of EOSs (HR 1.84 [1.0-3.4], p = 0.05) were independently associated with epilepsy. The proposed scale, designated RISE, scores 1 point for premorbid mRS ≥ 2 (R), VASOGRADE-Yellow (I, Ischemia), surgical intervention (S), and history of EOSs (E) and 2 points for VASOGRADE-Red. RISE stratifies patients into 3 groups: low (0-1), moderate (2-3), and high (4-5) risk (2.9%, 20.8%, and 75.7% developed epilepsy, respectively). On validation in a cohort from a different tertiary care center (N = 308), the new scale yielded a similar risk distribution and good predictive power for epilepsy within 5 years after aSAH (area under the curve [AUC] 0.82; 95% CI 0.74-0.90). DISCUSSION: The RISE scale is a robust predictor of post-SAH epilepsy with immediate clinical applicability. In addition to facilitating personalized diagnosis and treatment, RISE may be of value for exploring future antiepileptogenesis strategies.

Risk assessment of long-term epilepsy after de novo status epilepticus with clinical and electroencephalographic biomarkers: The AFTER score.

BACKGROUND: The risk of developing epilepsy after de novo status epilepticus (SE) is nonnegligible. The individualized management of patients with high risk of subsequent epilepsy could improve long-term quality of life and cognitive impairment. We aimed to ascertain potential biomarkers of subsequent epilepsy and to construct a scoring system possessing predictive value for the diagnosis of post-SE epilepsy during follow-up. METHODS: The study data were obtained from a prospective registry of all SE episodes occurring in patients over 16 years attended in our tertiary center from February 2011 to April 2022. Clinical data, electroencephalography findings, treatment, and long-term clinical data were prospectively recorded. We selected SE patients at risk of developing epilepsy (acute symptomatic and cryptogenic etiologies with no previous history of epilepsy) and analyzed the risk of developing subsequent epilepsy. RESULTS: We included 230 patients. Median age was 65 years ± 16.9 SD and 112/230 (48.7 %) were women. One-hundred ninety-eight patients (86.1 %) had an acute symptomatic SE, whereas 32 patients (13.9 %) presented with a cryptogenic SE. A total of 55 patients (23.9 %) developed an unprovoked remote seizure and were diagnosed with epilepsy. After adjusting for identifiable confounders in a multivariable Cox regression analysis cryptogenic etiology (HR 2.24 [1.13-4.46], p = 0.022), first-line treatment initiation ≥1 h (HR 2.12 [1.03-4.36], p = 0.041], RDA/LPD/GPD EEG patterns (HR 1.88 [1.07-3.32], p = 0.028), and super-refractoriness (HR 2.90 [1.40-5.99], p = 0.004) emerged as independent predictors of post-SE epilepsy. Based on these findings, we constructed the AFTER score (1 point for each item) with a robust capability to predict post-SE epilepsy at 5 years (AUC 74.3 %, 95 %CI 64.3-84.3 %, p < 0.001). CONCLUSIONS: The AFTER score is a robust predictor of the development of epilepsy after new onset SE using clinical and electroencephalographic biomarkers (such as etiology, time to first-line treatment initiation, EEG pattern and super-refractoriness). Prospective studies are warranted to validate the score in other populations.

Prediction of long-term unprovoked seizures after status epilepticus.

OBJECTIVE: Possible long-term consequences of status epilepticus (SE) include cognitive and behavioral impairment and the development of chronic epilepsy. However, these aspects have not been systematically studied in clinical practice. We aimed to evaluate long-term seizure recurrence after SE and the potential risk factors for their development. METHODS: Data were obtained from a prospective registry of all SE episodes occurring in adult patients who attended our center from February 2011 to April 2022. Clinical data, electroencephalographic findings, treatment, and long-term data were prospectively recorded. We performed a cross-sectional study of consecutive SE patients without previous epilepsy diagnosis, and analyzed the development of unprovoked remote seizures. RESULTS: A total of 849 patients were registered in the database. After excluding in-hospital mortality (198/849, 23.3%) and patients with prior epilepsy history (291/849, 44.7%), 360 patients (42.4%) with a first SE episode were included. The median age was 68 years (interquartile range [IQR] = 56-79), and 176 patients (48.9%) were women. The median time to first-line treatment initiation was 2 h (IQR = .7-7.4), and it was correlated with SE duration (R = .375, p < .001). One hundred nine patients (30.3%) presented unprovoked seizures during a median follow-up of 1.8 years (IQR = .5-4.3). After adjusting for identifiable confounders in a multivariable Cox regression analysis, progressive symptomatic etiology (hazard ratio [HR] = 1.97, 95% confidence interval [CI] = 1.17-3.33, p = .011), time to first-line treatment initiation > 1.5 h (HR = 1.89, 95% CI = 1.25-2.87, p = .003), and superrefractory SE (HR = 2.34, 95% CI = 1.26-4.33, p = .007) were independently associated with a greater risk of unprovoked seizure recurrence. In contrast, older patients (HR = .99, 95% CI = .97-.99, p = .021) and an acute symptomatic etiology (HR = .44, 95% CI .28-.68, p < .001) were at lower risk of unprovoked seizure recurrence. SIGNIFICANCE: The etiology of SE, the delay in initiating SE treatment, and the presence of superrefractoriness have been identified as potentials factors associated with unprovoked remote seizures following a new onset SE. Therefore, prompt and appropriate management should be applied to avoid seizure recurrence.

Association of Mortality and Risk of Epilepsy With Type of Acute Symptomatic Seizure After Ischemic Stroke and an Updated Prognostic Model.

Importance: Acute symptomatic seizures occurring within 7 days after ischemic stroke may be associated with an increased mortality and risk of epilepsy. It is unknown whether the type of acute symptomatic seizure influences this risk. Objective: To compare mortality and risk of epilepsy following different types of acute symptomatic seizures. Design, Setting, and Participants: This cohort study analyzed data acquired from 2002 to 2019 from 9 tertiary referral centers. The derivation cohort included adults from 7 cohorts and 2 case-control studies with neuroimaging-confirmed ischemic stroke and without a history of seizures. Replication in 3 separate cohorts included adults with acute symptomatic status epilepticus after neuroimaging-confirmed ischemic stroke. The final data analysis was performed in July 2022. Exposures: Type of acute symptomatic seizure. Main Outcomes and Measures: All-cause mortality and epilepsy (at least 1 unprovoked seizure presenting >7 days after stroke). Results: A total of 4552 adults were included in the derivation cohort (2547 male participants [56%]; 2005 female [44%]; median age, 73 years [IQR, 62-81]). Acute symptomatic seizures occurred in 226 individuals (5%), of whom 8 (0.2%) presented with status epilepticus. In patients with acute symptomatic status epilepticus, 10-year mortality was 79% compared with 30% in those with short acute symptomatic seizures and 11% in those without seizures. The 10-year risk of epilepsy in stroke survivors with acute symptomatic status epilepticus was 81%, compared with 40% in survivors with short acute symptomatic seizures and 13% in survivors without seizures. In a replication cohort of 39 individuals with acute symptomatic status epilepticus after ischemic stroke (24 female; median age, 78 years), the 10-year risk of mortality and epilepsy was 76% and 88%, respectively. We updated a previously described prognostic model (SeLECT 2.0) with the type of acute symptomatic seizures as a covariate. SeLECT 2.0 successfully captured cases at high risk of poststroke epilepsy. Conclusions and Relevance: In this study, individuals with stroke and acute symptomatic seizures presenting as status epilepticus had a higher mortality and risk of epilepsy compared with those with short acute symptomatic seizures or no seizures. The SeLECT 2.0 prognostic model adequately reflected the risk of epilepsy in high-risk cases and may inform decisions on the continuation of antiseizure medication treatment and the methods and frequency of follow-up.

Relationship between visuoperceptual functions and parietal structural abnormalities in temporal lobe epilepsy.

Progressive gray matter volume reductions beyond the epileptogenic area has been described in temporal lobe epilepsy. There is less evidence regarding correlations between gray and white matter volume changepres and multi-domain cognitive performance in this setting. We aimed to investigate correlations between volume changes in parietal structures and visuospatial performance in temporal lobe epilepsy patients. we performed a cross-sectional study comparing global and regional brain volume data from 34 temporal lobe epilepsy patients and 30 healthy controls. 3D T1-weighted sequences were obtained on a 3.0 T magnet, and data were analyzed using age and sex-adjusted linear regression models. Global and regional brain volumes and cortical thickness in patients were correlated with standardized visual memory, visuoperceptual, visuospatial, and visuoconstructive parameters obtained in a per-protocol neuropsychological assessment. temporal lobe epilepsy patients had smaller volume fractions of the deep gray matter structures, putamen and nucleus accumbens, and larger cerebrospinal fluid volume fraction than controls. Correlations were found between: 1) visual memory and precuneus and inferior parietal cortical thickness; 2) visuoperceptual performance and precuneus and supramarginal white matter volumes; 3) visuospatial skills and precuneus, postcentral, and inferior and superior parietal white matter volumes; 4) visuoconstructive performance and inferior parietal white matter volume. Brain volume loss is widespread in temporal lobe epilepsy. Volumetric reductions in parietal lobe structures were associated with visuoperceptual cognitive performance.

Reponse of second-line treatment in focal status epilepticus: A tertiary hospital experience.

OBJECTIVE: To investigate the response to various antiseizure medications (ASMs) in the treatment of focal status epilepticus (SE) in the established phase, and the effect of administering several ASMs prior to sedation. METHODS: All SE cases in patients aged > 16 years treated with non-BZDs ASMs were prospectively collected in our centre from February 2011 to April 2019. In total, 281 episodes were analysed. RESULTS: Median age at SE onset was 65.1 years; 47 % were focal motor and 53 % focal non-motor episodes. SE cessation was achieved in 79 % episodes with second-line drugs, whereas a third line (anesthetics) was required in 47 episodes. SE cessation was achieved in only 27 % with the first ASM, 48 % with the second, and 51 % with the third. Prompt resolution of the SE episode with a first or second ASM was associated with a better outcome than episodes requiring a larger number of drugs (p = 0.024). The first option in our sample was levetiracetam in 70 % of cases. Among the total of non-responding SE cases treated with levetiracetam as the first ASM option, 107 were subsequently given lacosamide (seizure cessation in 53.3 %) and 34 valproic acid (seizure cessation in 29.4 %) (p = 0.015). CONCLUSION: Our findings further support the notion that early termination of SE with a first or second ASM confers a better functional outcome. The large difference in response between the first ASM and consecutive ones suggests that the sum of different ASMs might be the key to resolving focal SE.

Interictal brain activity changes in temporal lobe epilepsy: A quantitative electroencephalogram analysis.

OBJECTIVES: To evaluate the usefulness of quantitative electroencephalography (qEEG) in the analysis of baseline activity in patients with temporal lobe epilepsy (TLE) and identify measures potentially associated with disease duration and drug resistance. MATERIALS AND METHODS: Cross-sectional study of adult patients with TLE and controls who underwent video-EEG monitoring. Representative artifact-free resting wakefulness baseline EEG segments were selected for quantitative analysis. The fast Fourier transform (FFT) approach was used for the power spectral analysis, with computation of FFT power ratios and alpha-delta and alpha-theta ratios for both hemispheres. The resulting measures were compared between TLE patients and controls and their values as predictors of epilepsy duration and drug resistance analyzed. RESULTS: Thirty-nine TLE patients and 23 controls were included. The TLE patients had a lower alpha-delta ratio in the posterior quadrant ipsilateral to the epileptic focus and a lower alpha-theta ratio in the ipsilateral anterior/posterior quadrants and temporal region. A younger age at onset and longer epilepsy duration correlated with a higher theta power ratio in the contralateral anterior and posterior quadrants and temporal region. No qEEG measures predicted drug resistance. CONCLUSIONS: Quantitative electroencephalography background activity may contribute to the diagnosis of TLE and provide useful information on disease duration. A lower alpha-delta and alpha-theta ratio may be reliable baseline qEEG measures for identifying patients with TLE. A higher contralateral theta power ratio may be indicative of longer epilepsy duration.

The economic burden of newly diagnosed epilepsy in Spain.

OBJECTIVE: The aim of this study was to determine the hospital burden and economic impact of epilepsy in adults in Spain and identify characteristics associated with higher direct medical costs. METHOD: Patients newly diagnosed with epilepsy at the outpatient epilepsy unit of a tertiary hospital in Spain in 2012 were included. Sociodemographic and clinical data and use of health resources were collected retrospectively from electronic medical records from the time of diagnosis to the end of follow-up (2019). Direct costs (in 2012 Euro) were estimated and linear regression models built to explore predictors of higher costs. RESULTS: We studied 110 patients with newly diagnosed epilepsy. Their mean (SD) age was 52.6 (19.6) years and 53.6% were men. Eighty-nine patients (80.9%) had focal epilepsy and 45 (40.9%) had an unknown etiology. At 6 months, 79.1% of patients were classified as responders and 17.6% as having drug-resistant epilepsy. The mean direct cost in the first year of epilepsy diagnosis was €3816.06, 49.7% of which was due to hospital admissions. The mean annual cost per patient was €2584.17, 51.4% of which was due to anti-seizure medications (ASMs). Focal epilepsy and poor response in the first 6 months of treatment predicted higher annual costs, while focal epilepsy and pre-existing comorbidities predicted higher costs in the first year. CONCLUSIONS: The direct cost of newly diagnosed epilepsy in adults in our area is €2584 per patient/year. Anti-seizure medication use is the main cost driver. Focal epilepsy, comorbidities, and poor response to ASMs are independent predictors of higher costs.

Seizures after Ischemic Stroke: A Matched Multicenter Study.

OBJECTIVE: The purpose of this study was to identify risk factors for acute symptomatic seizures and post-stroke epilepsy after acute ischemic stroke and evaluate the effects of reperfusion treatment. METHODS: We assessed the risk factors for post-stroke seizures using logistic or Cox regression in a multicenter study, including adults from 8 European referral centers with neuroimaging-confirmed ischemic stroke. We compared the risk of post-stroke seizures between participants with or without reperfusion treatment following propensity score matching to reduce confounding due to treatment selection. RESULTS: In the overall cohort of 4,229 participants (mean age 71 years, 57% men), a higher risk of acute symptomatic seizures was observed in those with more severe strokes, infarcts located in the posterior cerebral artery territory, and strokes caused by large-artery atherosclerosis. Strokes caused by small-vessel occlusion carried a small risk of acute symptomatic seizures. 6% developed post-stroke epilepsy. Risk factors for post-stroke epilepsy were acute symptomatic seizures, more severe strokes, infarcts involving the cerebral cortex, and strokes caused by large-artery atherosclerosis. Electroencephalography findings within 7 days of stroke onset were not independently associated with the risk of post-stroke epilepsy. There was no association between reperfusion treatments in general or only intravenous thrombolysis or mechanical thrombectomy with the time to post-stroke epilepsy or the risk of acute symptomatic seizures. INTERPRETATION: Post-stroke seizures are related to stroke severity, etiology, and location, whereas an early electroencephalogram was not predictive of epilepsy. We did not find an association of reperfusion treatment with risks of acute symptomatic seizures or post-stroke epilepsy. ANN NEUROL 2021;90:808-820.

Effect of late-onset epilepsy on cognitive functioning in patients with small vessel disease.

RATIONALE: Late-onset epilepsy (LOE) often has underlying cerebrovascular cause and has been associated with neurocognitive deficits and dementia. Nevertheless, the interplay between these factors has not been studied thus far. Hence, we conducted a retrospective cross-sectional study aimed to explore how unprovoked epileptic seizures along with vascular-related factors contribute to neurocognitive impairments in patients with cerebral small vessel disease. METHODS: Twenty-seven patients with LOE aged > 60 years with concomitant cerebral small vessel disease (cSVD) and a matched group of cSVD without epilepsy were cognitively assessed. Demographic, clinical, and vascular information were obtained and vascular burden score was calculated for each patient. Multiple linear regression models were used to explore the relationship between epilepsy and cognitive measures adjusting for demographic and vascular risk factors. RESULTS: Compared with cSVD, cSVD-LOE group showed a poorer performance on verbal memory measures, visuomotor tracking and speed processing and phonetic fluency. In the multiple regression analysis, the presence of epilepsy was found to be the major predictor for verbal memory dysfunction, specifically in verbal short recall (p = 0.008) and verbal learning (p < 0.001). No interactions between vascular burden and epilepsy were found. CONCLUSION: Patients who had cSVD with concurrent LOE showed poorer performance on memory function compared with patients with cSVD without epilepsy, and they showed a different cognitive profile from that typically manifested by patients with cSVD. The presence of epilepsy, but not seizure localization nor vascular burden, was the major contributor to the decrease in verbal memory.

Relationship between sleep quality and cognitive performance in patients with epilepsy.

PURPOSE: To investigate the relationship between self-reported sleep quality and cognitive function in patients with epilepsy (PWE), as well as anxiety and depressive symptoms and patient quality of life (QoL). METHODS: This multicenter cross-sectional study included PWE aged ≥12 years who were receiving ≥1 anti-seizure medication (ASM) and had not been diagnosed with a sleep disorder. Patients completed the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), the Montreal Cognitive Assessment test (MoCA), the Hospital Anxiety and Depression Scale (HADS), and the Quality of Life in Epilepsy Inventory-10 (QOLIE-10). RESULTS: The study enrolled 150 patients aged 16-83 years, mean age (standard deviation [SD]) 40.6 (15.2) years; 58.7% were female and 75.3% had focal epilepsy. Mean (SD) PSQI score was 4.71 (3.08), 44.4% of patients had impaired sleep quality (PSQI score ≥5), 19.9% had pathologic excessive daytime sleepiness (ESS score >12), and 32.7% had mild cognitive impairment (MoCA score <26). Within the PSQI, sleep disturbance (P = 0.036) and use of sleep medication (P = 0.006) scores were significantly higher in patients with mild cognitive impairment. Multiple regression analysis showed older age (regression coefficient [B], -0.086; 95% confidence interval [CI], -0.127, -0.045; P < 0.001) and the use of sleep medication component of the PSQI [B, -1.157; 95% CI, -2.064, -0.220; P = 0.013) were independently associated with lower MoCA score. Poor sleep quality was associated with probable anxiety and depression symptoms, and directly correlated with reduced QoL. CONCLUSIONS: In PWE, sleep quality was not significantly independently associated with mild cognitive impairment, although poor sleep quality had a negative effect on mood and QoL.

Medium-term effects of COVID-19 pandemic on epilepsy: A follow-up study.

OBJECTIVE: To analyze the medium-term impact of the COVID-19 pandemic on epilepsy patients, focusing on psychological effects and seizure control. METHODS: Prospective follow-up study to evaluate the medium-term effects of the COVID-19 pandemic on a cohort of epilepsy patients from a tertiary hospital previously surveyed during the first peak of the pandemic. Between July 1, 2020, and August 30, 2020, the patients answered an online 19-item questionnaire, HADS, and PSIQ scales. Short- and medium-term effects of the pandemic confinement and the perception of telemedicine were compared. RESULTS: 153 patients completed the questionnaire, mean ± SD age, 47.6 ± 19.3 years; 49.7% women. Depression was reported by 43 patients, significantly more prevalent than in the short-term analysis (29.2% vs. 19.7%; p = .038). Anxiety (38.1% vs. 36.1%; p = 0.749) and insomnia (28.9% vs. 30.9%, p = .761) remained highly prevalent. Seventeen patients reported an increase in seizure frequency (11.1% vs. 9.1%, p = .515). The three factors independently associated with an increase in seizure frequency in the medium term were drug-resistant epilepsy (odds ratio [OR] = 8.2, 95% CI 2.06-32.52), depression (OR = 6.46, 95% CI 1.80-23.11), and a reduction in income (OR = 5.47, 95% CI 1.51-19.88). A higher proportion of patients found telemedicine unsatisfactory (11.2% vs. 2.4%), and a lower percentage (44.8% vs. 56.8%) found it very satisfactory (p = .005). CONCLUSIONS: Depression rates increased significantly after the first wave. Depression, drug-resistant epilepsy, and a reduction in family income were independent risk factors for an increased seizure frequency. Perception of telemedicine worsened, indicating need for re-adaptation.

Factors associated with resistance to benzodiazepines in status epilepticus.

OBJECTIVE: To investigate factors related to benzodiazepine (BZD) resistance in status epilepticus (SE) with a focus on their relationship with the etiology of the episode. METHODS: All SE cases in patients aged >16 years treated with BZDs were prospectively collected in our center from February 2011 to April 2019. The registry included demographics, SE type and etiology, the timing and duration of BZD administration, and the outcome. In total, 371 episodes were analyzed. RESULTS: Median age at SE onset was 61.3 years; the most frequent etiology was acute symptomatic (55.8%). SE with prominent motor symptoms occurred in 63.3%. Median time to BZD administration was 2 h. We studied the correlation between two-time variables: time from SE onset to BZD administration and time from BZD administration to resolution of SE (response); we observed that timely administration correlated with a faster response in patients with prominent motor symptoms (p = 0.017), SE due to a chronic structural cerebral lesion (p = 0.004), and patients with a history of seizures (p = 0.013). In these subgroups (prominent motor symptoms or chronic structural lesion) BZD administration within the first 4.5 h was highly associated with shorter post-BZD SE duration (p < 0.001). SIGNIFICANCE: The relationship between prompt BZD administration and subsequent duration of SE was found to depend to some extent on the etiology of the episode: patients with chronic structural lesions and those with previous epilepsy responded faster to BZDs. Semiology may have also its impact, as the presence of prominent motor symptoms showed also a faster response.

Seizures and Epilepsy After Stroke: Epidemiology, Biomarkers and Management.

Stroke is the leading cause of seizures and epilepsy in older adults. Patients who have larger and more severe strokes involving the cortex, are younger, and have acute symptomatic seizures and intracerebral haemorrhage are at highest risk of developing post-stroke epilepsy. Prognostic models, including the SeLECT and CAVE scores, help gauge the risk of epileptogenesis. Early electroencephalogram and blood-based biomarkers can provide information additional to the clinical risk factors of post-stroke epilepsy. The management of acute versus remote symptomatic seizures after stroke is markedly different. The choice of an ideal antiseizure medication should not only rely on efficacy but also consider adverse effects, altered pharmacodynamics in older adults, and the influence on the underlying vascular co-morbidity. Drug-drug interactions, particularly those between antiseizure medications and anticoagulants or antiplatelets, also influence treatment decisions. In this review, we describe the epidemiology, risk factors, biomarkers, and management of seizures after an ischaemic or haemorrhagic stroke. We discuss the special considerations required for the treatment of post-stroke epilepsy due to the age, co-morbidities, co-medication, and vulnerability of stroke survivors.