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Vascular tortuosity of supra-aortic vessels is widely considered one of the main reasons for failure and delays in endovascular treatment of large vessel occlusion in patients with acute ischemic stroke. Characterization of tortuosity is a challenging task due to the lack of objective, robust and effective analysis tools. We present a fully automatic method for arterial segmentation, vessel labelling and tortuosity feature extraction applied to the supra-aortic region. A sample of 566 computed tomography angiography scans from acute ischemic stroke patients (aged 74.8 ± 12.9, 51.0% females) were used for training, validation and testing of a segmentation module based on a U-Net architecture (162 cases) and a vessel labelling module powered by a graph U-Net (566 cases). Successively, 30 cases were processed for testing of a tortuosity feature extraction module. Measurements obtained through automatic processing were compared to manual annotations from two observers for a thorough validation of the method. The proposed feature extraction method presented similar performance to the inter-rater variability observed in the measurement of 33 geometrical and morphological features of the arterial anatomy in the supra-aortic region. This system will contribute to the development of more complex models to advance the treatment of stroke by adding immediate automation, objectivity, repeatability and robustness to the vascular tortuosity characterization of patients.

Resumen Introduccion Determinar si la administracion de farmacos antiepilepticos (FAE) puede alterar la probabilidad de encontrar anomalias epileptiformes en EEG realizados de forma precoz tras una primera crisis epileptica (CE). Metodo Estudio observacional retrospectivo en el que se incluyo a los pacientes atendidos en urgencias de nuestro centro por una primera CE entre julio del 2014 y noviembre del 2019. Se recogieron los datos clinicos, las caracteristicas tecnicas de adquisicion e interpretacion de los EEG efectuados durante las primeras 72 h tras la CE y los factores relacionados con la recurrencia. Resultados Se recogieron 155 pacientes; edad media 48,6 ±22,5 anos; 61,3% hombres. El 51% presento crisis tonico-clonicas de inicio desconocido y el 12% focales con progresion a tonico-clonica bilateral. El 25,2% (39/155) recibio tratamiento con FAE antes de la realizacion del EEG; en 33 pacientes se administro un FAE no benzodiacepinico y en 6 una benzodiacepina. Se observaron anomalias epileptiformes en 29,7% de los pacientes. La administracion previa de FAE no se asocio de forma significativa ni con la probabilidad de detectar anomalias epileptiformes (p = 0,25) ni con el riesgo de recurrencia a los 6 meses (p = 0,63). Conclusiones La administracion de un FAE previo a la realizacion del EEG precoz tras una primera CE no disminuye la probabilidad de detectar anomalias epileptiformes. Estos hallazgos sugieren que iniciar un FAE de forma inmediata en aquellos pacientes con alto riesgo de recurrencia precoz no implica un menor rendimiento diagnostico de dicha prueba.

Background An increased rate of thrombotic events has been associated to Coronavirus Disease 19 (COVID-19) with a variable rate of acute stroke. Our aim is to uncover the rate of acute stroke in COVID-19 patients and identify those cases in which a possible causative relationship could exist. Methods We performed a single-center analysis of a prospective mandatory database. We studied all patients with confirmed COVID-19 and stroke diagnoses from March 2nd to April 30th. Demographic, clinical, and imaging data were prospectively collected. Final diagnosis was determined after full diagnostic work-up unless impossible due to death. Results Of 2050 patients with confirmed SARS-CoV-2 infection, 21 (1.02%) presented an acute ischemic stroke 21 and 4 (0.2%) suffered an intracranial hemorrhage. After the diagnostic work-up, in 60.0% ischemic and all hemorrhagic strokes patients an etiology non-related with COVID-19 was identified. Only in 6 patients the stroke cause was considered possibly related to COVID-19, all of them required mechanical ventilation before stroke onset. Ten patients underwent endovascular treatment; compared with patients who underwent EVT in the same period, COVID-19 was an independent predictor of in-hospital mortality (50% versus 15%; Odds Ratio, 6.67; 95% CI, 1.1-40.4; p 0.04). Conclusions The presence of acute stroke in patients with COVID-19 was below 2% and most of them previously presented established stroke risk factors. Without other potential cause, stroke was an uncommon complication and exclusive of patients with a severe pulmonary injury. The presence of COVID-19 in patients who underwent EVT was an independent predictor of in-hospital mortality.

Purpose A number of antiepileptic drugs (AEDs) are currently available for treating acute seizures. It is recommended to select the initial treatment option according to the type of epileptic syndrome and the patient's clinical characteristics, but little is known about the long-term retention rates of AEDs started in the emergency department. Methods We recruited patients admitted with seizures over a two-year period. All patients underwent early neurological assessment, EEG testing, and neuroimaging. The treatments received at baseline and at one year of follow-up were compared. Results In total, 225 patients were included. Overall, monotherapy with levetiracetam was the regimen most often used in patients with new-onset seizures, whereas other AEDs were mainly used in patients previously treated with other drugs. Lacosamide use was most likely associated with the presence of lesion related seizures in elderly patients, and carboxamides with focal onset seizures of unknown cause. The mean retention rate of the total of AED treatments was nearly 70%. The main cause leading to discontinuation was the development of intolerable adverse events. Levetiracetam use decreased as lacosamide use increased in the overall group of patients. Conclusion Our study shows that there is a trend to use newer AEDs, particularly levetiracetam, as the first option in new-onset seizures in the emergency room. However, levetiracetam use significantly decreased over follow-up, mainly because of the development of adverse events. The use of other, better-tolerated AEDs, such lacosamide predominated in elderly patients and patients with lesion related seizures, or carboxamides in epilepsies of unknown etiology.

Psychiatric comorbidity is common in epilepsy and has a considerable impact on patient quality of life (QoL). This study aimed to analyze the relationship between seizure frequency, irritability, and depression and describe how they mediate each other's effect on QoL in epilepsy.This is a cross-sectional study of consecutive adults seen at an outpatient epilepsy clinic of a tertiary hospital in Barcelona, Spain. All the patients were evaluated for psychiatric comorbidity and administered the State-Trait Anger Expression Inventory-2 (STAXI-2), the Hospital Anxiety and Depression Scale (HADS), and the Quality Of Life in Epilepsy Inventory-10 (QOLIE-10). Mediation analysis with multiple linear regression followed by the Sobel test was performed.We studied 157 patients. Seizure frequency (R = -0.193, P = .053), irritability (R = 0.216, P = .039), and depression (R = -0.598, P .001) had all a negative effect on QoL. In the adjusted linear regression model, depression was the only independent predictor of impaired QoL (B = -2.453 [95% confidence interval (CI): -3.161, -1.744], P .001). The Sobel test showed that depression exerted a significant mediating effect on seizure frequency (Z = -1.984; P = .047) and irritability (Z = -3.669; P .001) in their influence on QoL.Depression is an independent predictor of worse QoL and significantly mediated the effects of irritability and poor seizure control on QoL impairment in patients with epilepsy.

Patients with a first unprovoked epileptic seizure are often seen in emergency services. Electroencephalography (EEG) is indicated for diagnosing epilepsy, but the optimal time to perform this test has not been defined. This study aimed to determine the time interval following a seizure within which EEG has the greatest diagnostic yield.We conducted a retrospective study of all adult patients with a first unprovoked seizure who had undergone emergency EEG (July 2014-December 2019). Data collection included demographics, seizure type, time interval to EEG study, EEG pattern identified, and the prescription after emergency assessment. An optimal cut-off point for time to EEG was obtained, and an adjusted regression model was performed to establish associations with the presence of epileptiform abnormalities.A total of 170 patients were included (mean age: 50.7 years, 40.6% women). Epileptiform discharges were identified in 34.1% of recordings, nonepileptiform abnormalities in 46.5%, and normal findings in 19.4%. A lower latency from seizure to EEG was associated with a higher probability of finding epileptiform discharges (median: 12.7 in the epileptiform EEGs vs. 20 h in the nonepileptiform EEGs, p 0.001). The time interval associated with the highest probability of detecting an epileptiform EEG pattern was within the first 16 h after seizure onset: 52.1% of recordings performed before the 16-h cut-off showed these abnormal patterns compared with 20.2% performed after (p 0.001). These findings were not related to the presence of an epileptogenic lesion in neuroimaging or to other clinical variables. The finding of epileptiform abnormalities was followed by a greater prescription of antiseizure drugs (96.4% vs. 66% in nonepileptiform patterns, p 0.001).The diagnostic yield of EEG following a first unprovoked epileptic seizure is highest when this test is performed within the first 16 h after onset of the event.