Prognosis and management of acute symptomatic seizures: a prospective, multicenter, observational study

The impact of white matter lesions on seizure recurrence after first epileptic seizures in the elderly: a prospective study

BACKGROUND

Despite considerable previous research, to what degree white matter lesions (WML) may be epileptogenic remains unclear. Therefore, the decision of initiating treatment with antiseizure medication (ASM) can be challenging in patients with only WML on neuroimaging. In this prospective study we assessed whether the prevalence, localization or severity of WML impact the risk of seizure recurrence in patients aged 60 years or older after first-time seizures.

METHODS

Data was analyzed from 168 patients, aged ≥ 60 years-old who had experienced a previous unprovoked seizure and had either a potentially epileptogenic lesion or WML on neuroimaging. The frequency of seizure recurrence was documented after 6, 12, and 24 months. Pearson´s chi-square test of independence (categorical variables) and the independent Student´s t-test (continuous variables) were used to analyze intergroup differences. Binary logistic regressions were calculated to examine the influence of WML locations as a predictor of seizure recurrence. Kaplan-Meier survival analyses and log-rank statistics were performed to determine the cumulative recurrence rates between the groups.

RESULTS

Fifteen patients had only potentially epileptogenic lesions on neuroimaging (EPI) and 93 showed WML only (OWML). Sixty patients showed both of them on neuroimaging (EWML). Frontal and parieto-occipital were the predominant WML locations. Neither severity nor location of WML had a significant impact on recurrence rates. The two-year cumulative probability of becoming seizure-free was significantly lower in the EPI group compared to the EWML (χ2 [1] = 4.425, p = 0.035) and the OWML group (χ2 [1] = 13.094, p < 0.001). A significant association between interictal epileptiform discharges in EEG and seizure recurrence was found in OWML patients (p = 0.004).

CONCLUSION

We could not find any association between prevalence, severity or location of WML and seizure recurrence after first seizures in the elderly. Therefore, treatment with ASM should be started with caution in those patients. Our results show a trend of WML not having epileptogenic potential, but further studies are needed to get better evidence.

TRIAL REGISTRATION

ClinicalTrials.gov Protocol Registration and Results, NCT06836687, AZ 199/17, release: 03/19/2024 retrospectively registered. https://register.

CLINICALTRIALS

gov/prs/beta/studies/S000EBC700000025/recordSummary.

Risk of unprovoked seizures after discontinuation of antiseizure medication at discharge following acute symptomatic seizures

OBJECTIVE

We aimed to investigate whether the risk of unprovoked seizures differs between patients receiving a brief antiseizure medication (ASM) course during hospitalization and those treated beyond hospital discharge following acute symptomatic seizures (ASyS).

METHODS

We performed a single-center, retrospective cohort study of all consecutive adults without epilepsy who received maintenance ASM (≥48 h) after ASyS. All patients underwent continuous electroencephalographic (EEG) monitoring and were divided into those receiving ASMs only during hospitalization and those discharged on ASMs. We used propensity score matching to balance covariates between groups. Cause-specific Cox proportional hazards models analyzed the time to the first unprovoked seizure; death was treated as a competing risk.

RESULTS

A total of 144 adults (mean age = 57.4 ± 18.6 years, 48% females) included 118 (82%) patients discharged on ASMs and 26 (18%) who received ASM during hospitalization. During a median follow-up of 24.6 months, 15% experienced an unprovoked seizure. The cumulative incidence of unprovoked seizures at 3, 12, and 36 months was 7.2%, 11.5%, and 17.9%, respectively. ASM status at discharge was significantly associated with electrographic seizures on EEG, etiology, mental status at the time of ASyS, and functional outcome at discharge. After a well-balanced propensity score matching, there was no significant difference in time to unprovoked seizure between patients discharged on ASMs and those who received ASMs only during hospitalization.

SIGNIFICANCE

We found that unprovoked seizure risk may not differ significantly between ASyS patients receiving a brief ASM course during hospitalization and those treated for a longer duration after discharge. Although our findings need confirmation in larger studies, they underscore the need for investigating optimal ASM duration in this patient population.

Association of the Timing and Type of Acute Symptomatic Seizures With Poststroke Epilepsy and Mortality

BACKGROUND

Acute symptomatic seizures (ASyS) increase the risk of epilepsy and mortality after a stroke. The impact of the timing and type of ASyS remains unclear.

METHODS

This multicenter cohort study included data from 9 centers between 2002 and 2018, with a final analysis in February 2024. The study included 4552 adults (2005 female; median age, 73 years) with ischemic stroke and no seizure history. Seizures were classified using International League Against Epilepsy definitions. We examined ASyS occurring within seven days after stroke. The main outcomes were all-cause mortality and epilepsy. Validation of the updated SeLECT score (SeLECT-ASyS) was performed in 3 independent cohorts (Switzerland, Argentina, and Japan) collected between 2012 and 2024, including 74 adults with ASyS.

RESULTS

The 10-year risk of poststroke epilepsy ranged from 41% to 94%, and mortality from 36% to 100%, depending on ASyS type and timing. ASyS on stroke onset day had a higher epilepsy risk (adjusted hazard ratio [aHR], 2.3 [95% CI, 1.3-4.0]; P=0.003) compared with later ASyS. Status epilepticus had the highest epilepsy risk (aHR, 9.6 [95% CI, 3.5-26.7]; P<0.001), followed by focal to bilateral tonic-clonic seizures (aHR, 3.4 [95% CI, 1.9-6.3]; P<0.001). Mortality was higher in those with ASyS presenting as focal to bilateral tonic-clonic seizures on day 0 (aHR, 2.8 [95% CI, 1.4-5.6]; P=0.004) and status epilepticus (aHR, 14.2 [95% CI, 3.5-58.8]; P<0.001). The updated SeLECT-ASyS model, available as an application, outperformed a previous model in the derivation cohort (concordance statistics, 0.68 versus 0.58; P=0.02) and in the validation cohort (0.70 versus 0.50; P=0.18).

CONCLUSIONS

ASyS timing and type significantly affect epilepsy and mortality risk after stroke, improving epilepsy prediction and guiding patient counseling.

Antiseizure medication use in acute symptomatic seizures: A narrative review

Acute symptomatic seizures, occurring shortly after a central nervous system insult, constitute nearly half of all seizure cases. However, there is a conspicuous absence of clear, comprehensive, and cohesive guidelines for the management of these seizures with antiseizure medications, especially their duration of use. This lack of consensus on the optimal duration of therapy leads to prolonged treatments that may carry adverse consequences. The primary objective of this narrative review is to present the existing evidence-based literature on the management of acute symptomatic seizures within the context of the underlying pathologies that trigger them. We explore the risk of developing epilepsy for each specific etiology and identify the factors that influence this risk. Finally, to facilitate decision-making regarding treatment duration, we categorize acute seizures based on the temporal characteristics of hyperexcitability as acute, subacute, and prolonged. Such a rubric may offer clarity in an area where consensus and guidelines are lacking.

The impact of the new definition of epilepsy on diagnosis, treatment, and short-term outcomes-A prospective study

Background

In 2014, the ILAE introduced a new definition of epilepsy that allows some patients to be diagnosed earlier than under the previously used definition. According to the old classification, the diagnosis was made after a second unprovoked seizure. The risk of this was 36% after the first seizure. The aim of this study is to investigate the clinical impact of the new definition on diagnosis, treatment, and short-term outcome.

Methods

From 2018 to 2021, adult patients admitted with a first epileptic seizure were prospectively included. Demographic and clinical data were collected at baseline, at 6 and 12 months follow-up (FU). Factors affecting seizure recurrence, especially age, use of anti-seizure medication (ASM), interictal epileptiform discharges (IED) in the EEG, and the presence of structural lesions on imaging were investigated.

Results

Data from 235 patients were collected (41.7% female). Of these, 146 patients (62.1%) were diagnosed with epilepsy (PWE), following the new ILAE-criteria. Potential epileptogenic lesions on imaging were found in 49.3% of PWE. At the first FU (6.08 months ± 1.35), 143 patients (77.3%) were seizure-free, including 89 of the 146 patients diagnosed as PWE were seizure-free (70.6%). At the second FU (12.45 months ± 1.83), 129 patients (80.6%) were seizure-free. Seventy-seven of the PWE were seizure-free (72%). The use of ASM decreased (odds ratio = 0.46, p = 0.004) the recurrence rate significantly.

Conclusion

Our results suggest that the new definition of epilepsy results in a higher frequency of epilepsy diagnosis and treatment. Short-term outcomes improved (1-year-recurrence rate of 19.4%).

Predictive models for secondary epilepsy in patients with acute ischemic stroke within one year

Background

Post-stroke epilepsy (PSE) is a critical complication that worsens both prognosis and quality of life in patients with ischemic stroke. An interpretable machine learning model was developed to predict PSE using medical records from four hospitals in Chongqing.

Methods

Medical records, imaging reports, and laboratory test results from 21,459 ischemic stroke patients were collected and analyzed. Univariable and multivariable statistical analyses identified key predictive factors. The dataset was split into a 70% training set and a 30% testing set. To address the class imbalance, the Synthetic Minority Oversampling Technique combined with Edited Nearest Neighbors was employed. Nine widely used machine learning algorithms were evaluated using relevant prediction metrics, with SHAP (SHapley Additive exPlanations) used to interpret the model and assess the contributions of different features.

Results

Regression analyses revealed that complications such as hydrocephalus, cerebral hernia, and deep vein thrombosis, as well as specific brain regions (frontal, parietal, and temporal lobes), significantly contributed to PSE. Factors such as age, gender, NIH Stroke Scale (NIHSS) scores, and laboratory results like WBC count and D-dimer levels were associated with increased PSE risk. Tree-based methods like Random Forest, XGBoost, and LightGBM showed strong predictive performance, achieving an AUC of 0.99.

Conclusions

The model accurately predicts PSE risk, with tree-based models demonstrating superior performance. NIHSS score, WBC count, and D-dimer were identified as the most crucial predictors.

Funding

The research is funded by Central University basic research young teachers and students research ability promotion sub-projec t(2023CDJYGRH-ZD06), and by Emergency Medicine Chongqing Key Laboratory Talent Innovation and development joint fund project (2024RCCX10).

Late-Onset Idiopathic Generalized Epilepsy Manifesting With De Novo Late-Onset Absence Status Epilepticus After COVID-19 Infection: A Case Report

Herein, we present a case of idiopathic generalized epilepsy (IGE) manifesting as de novo late-onset absence status epilepticus (ASE) following mild coronavirus disease 2019 (COVID-19). A woman in her 40s presented with persistent 3-5.5 Hz generalized spike-wave complexes (SWCs) on electroencephalography (EEG). She experienced a generalized tonic-clonic seizure (GTCS) 10 days after the COVID-19 infection. She was diagnosed with epilepsy at 40 years of age, after which she was started on levetiracetam (LEV) 1,000 mg/day. After the medication was started, she experienced three other GTCSs. We performed a long-term video EEG of the patient, leading to a diagnosis of late-onset IGE with de novo late-onset ASE. She achieved seizure freedom for over a year with a combination of valproic acid (VPA) and lamotrigine (LTG), although her EEG continued to demonstrate persistent generalized SWCs. This case suggests that late-onset IGE accompanied by de novo late-onset status epilepticus may have been triggered by COVID-19. Persistent neuroinflammation may be reflected in persistent EEG abnormalities, even after epileptic seizures are well controlled with medications. LTG and VPA are believed to be effective for clinical management, and EEG is an essential modality for recording epileptic activity in outpatient settings.

Antiseizure Medication Use and Outcomes After Suspected or Confirmed Acute Symptomatic Seizures

Importance

Antiseizure medications (ASMs) are frequently prescribed for acute symptomatic seizures and epileptiform abnormalities (EAs; eg, periodic or rhythmic patterns). There are limited data on factors associated with ASM use and their association with outcomes.

Objectives

To determine factors associated with ASM use in patients with confirmed or suspected acute symptomatic seizures undergoing continuous electroencephalography, and to explore the association of ASMs with outcomes.

Design, Setting, and Participants

This multicenter cohort study was performed between July 1 and September 30, 2021, at 5 US centers of the Post Acute Symptomatic Seizure Investigation and Outcomes Network. After screening 1717 patients, the study included 1172 hospitalized adults without epilepsy who underwent continuous electroencephalography after witnessed or suspected acute symptomatic seizures. Data analysis was performed from November 14, 2023, to February 2, 2024.

Exposure

ASM treatment (inpatient ASM continuation ≥48 hours).

Main Outcomes and Measures

Factors associated with (1) ASM treatment, (2) discharge ASM prescription, and (3) discharge and 3-month Glasgow Outcome Scale score of 4 or 5 were ascertained.

Results

A total of 1172 patients (median [IQR] age, 64 [52-75] years; 528 [45%] female) were included. Among them, 285 (24%) had clinical acute symptomatic seizures, 107 (9%) had electrographic seizures, and 364 (31%) had EAs; 532 (45%) received ASM treatment. Among 922 patients alive at discharge, 288 (31%) were prescribed ASMs. The respective frequencies of inpatient ASM treatment and discharge prescription were 82% (233 of 285) and 69% (169 of 246) for patients with clinical acute symptomatic seizures, 96% (103 of 107) and 95% (61 of 64) for electrographic seizures, and 64% (233 of 364) and 48% (128 of 267) for EAs. On multivariable analysis, acute and progressive brain injuries were independently associated with increased odds of inpatient ASM treatment (odds ratio [OR], 3.86 [95% CI, 2.06-7.32] and 8.37 [95% CI, 3.48-20.80], respectively) and discharge prescription (OR, 2.26 [95% CI, 1.04-4.98] and 10.10 [95% CI, 3.94-27.00], respectively). Admission to the neurology or neurosurgery service (OR, 2.56 [95% CI, 1.08-6.18]) or to the neurological intensive care unit (OR, 7.98 [95% CI, 3.49-19.00]) was associated with increased odds of treatment. Acute symptomatic seizures and EAs were significantly associated with increased odds of ASM treatment (OR, 14.30 [95% CI, 8.52-24.90] and 2.30 [95% CI, 1.47-3.61], respectively) and discharge prescription (OR, 12.60 [95% CI, 7.37-22.00] and 1.72 [95% CI, 1.00-2.97], respectively). ASM treatment was not associated with outcomes at discharge (OR, 0.96 [95% CI, 0.61-1.52]) or at 3 months after initial presentation (OR, 1.26 [95% CI, 0.78-2.04]). Among 623 patients alive and with complete data at 3 months after discharge, 30 (5%) had postdischarge seizures, 187 (30%) were receiving ASMs, and 202 (32%) had all-cause readmissions.

Conclusions and Relevance

This study suggests that etiology and electrographic findings are associated with ASM treatment for acute symptomatic seizures and EAs; ASM treatment was not associated with functional outcomes. Comparative effectiveness studies are indicated to identify which patients may benefit from ASMs and to determine the optimal treatment duration.

The compelling role of allopurinol in hyperuricemia-induced epilepsy: Unrecognized like tears in rain

Epilepsy is a common neurological disease characterized by the recurrent, paroxysmal, and unprovoked seizures. It has been shown that hyperuricemia enhances and associated with the development and progression of epilepsy through induction of inflammation and oxidative stress. In addition, uric acid is released within the brain and contributes in the development of neuronal hyperexcitability and epileptic seizure. Brain uric acid acts as damage associated molecular pattern (DAMP) activates the immune response and induce the development of neuroinflammation. Therefore, inhibition of xanthine oxidase by allopurinol may reduce hyperuricemia-induced epileptic seizure and associated oxidative stress and inflammation. However, the underlying mechanism of allopurinol in the epilepsy was not fully elucidated. Therefore, this review aims to revise from published articles the link between hyperuricemia and epilepsy, and how allopurinol inhibits the development of epileptic seizure.

Efficacy and safety of phenytoin and levetiracetam for acute symptomatic seizures in children with acute encephalitis syndrome: an open label, randomised controlled trial

INTRODUCTION

Seizures represent a significant comorbidity in children with acute encephalitis syndrome (AES). Despite this, there is a notable absence of randomized controlled trials (RCTs) directly comparing antiseizure medications (ASMs) in children with AES.

MATERIALS AND METHODS

This RCT aimed to assess the efficacy and safety of phenytoin and levetiracetam in controlling seizures among children with AES. Both ASMs were administered with a loading followed by maintenance dose. After a 12-week period, children exhibiting a normal electroencephalogram and no seizure recurrence underwent tapering and discontinuation of ASM. Clinical follow-up occurred daily for the first week, and subsequently at 4, 12, and 24 weeks, evaluating seizure recurrence, incidence of status epilepticus, cognition, behavior, functional status, ASM acquisition cost, and adverse effects.

RESULTS

A total of 100 children (50 in each group) were enrolled. Within the first week, 5 and 3 children in the phenytoin and levetiracetam groups expired. Up to 1 week or death (whichever occurred earliest), 46 (92 %) and 44 (88 %) children remained seizure-free. Intention-to-treat analysis for both best and worst-case scenarios showed insignificant differences (p=0.52 and 1.0). No children experienced seizure recurrence after 1 week in either group. The number of patients with breakthrough status epilepticus, need for mechanical ventilation, duration of hospital stay, presence of epileptiform abnormalities in repeat electroencephalogram at 12 weeks, functional outcomes at 1, 12, and 24 weeks, as well as cognition and behavioral profiles at 24 weeks, were comparable in both groups (p>0.05 for all). However, the incidence of treatment-emergent adverse events (TEAEs) causally related to study medications was significantly higher in the phenytoin group (p=0.04).

CONCLUSION

Levetiracetam and phenytoin are comparable in efficacy in terms of achieving clinical seizure control in children with acute encephalitis syndrome, although levetiracetam group demonstrated fewer adverse effects.

Exit Strategy: Balancing the Risks and Rewards of Antiseizure Medication Withdrawal

The majority of people with epilepsy achieves long-term seizure-freedom and may consider withdrawal of their anti-seizure medications (ASMs). Withdrawal of ASMs can yield substantial benefits but may be associated with potential risks. This review critically examines the existing literature on ASM withdrawal, emphasizing evidence-based recommendations, where available. Our focus encompasses deprescribing strategies for individuals who have attained seizure freedom through medical treatment, those who have undergone successful epilepsy surgery, and individuals initiated on ASMs following acute symptomatic seizures. We explore state-of-the-art prognostic models in these scenarios that could guide the decision-making process. The review underscores the importance of a collaborative shared-decision approach between patients, caregivers, and physicians. We describe the subjective and objective factors influencing these decisions and illustrate how trade-offs may be effectively managed in practice.

Clinical approaches for poststroke seizure: a review

Poststroke seizure is a potential complication of stroke, which is the most frequent acute symptomatic seizure in adults. Patients with stroke may present with an abnormal or aggressive behavior accompanied by altered mental status and symptoms, such as hemiparesis, dysarthria, and sensory deficits. Although stroke manifestations that mimic seizures are rare, diagnosing poststroke seizures can be challenging when accompanied with negative postictal symptoms. Differential diagnoses of poststroke seizures include movement disorders, syncope, and functional (nonepileptic) seizures, which may present with symptoms similar to seizures. Furthermore, it is important to determine whether poststroke seizures occur early or late. Seizures occurring within and after 7 d of stroke onset were classified as early and late seizures, respectively. Early seizures have the same clinical course as acute symptomatic seizures; they rarely recur or require long-term antiseizure medication. Conversely, late seizures are associated with a risk of recurrence similar to that of unprovoked seizures in a patient with a focal lesion, thereby requiring long-term administration of antiseizure medication. After diagnosis, concerns regarding treatment strategies, treatment duration, and administration of primary and secondary prophylaxis often arise. Antiseizure medication decisions for the initiation of short-term primary and long-term secondary seizure prophylaxis should be considered for patients with stroke. Antiseizure drugs such as lamotrigine, carbamazepine, lacosamide, levetiracetam, phenytoin, and valproate may be administered. Poststroke seizures should be diagnosed systematically through history with differential diagnosis; in addition, classifying them as early or late seizures can help to determine treatment strategies.

Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape

Epilepsy, a neurological disorder characterized by recurrent seizures, has witnessed a remarkable transformation in its classification paradigm, driven by advances in clinical understanding, neuroimaging, and molecular genetics. This narrative review navigates the dynamic landscape of epilepsy classification, offering insights into recent developments, challenges, and the promising horizon. Historically, epilepsy classification relied heavily on clinical observations, categorizing seizures based on their phenomenology and presumed etiology. However, the field has profoundly shifted from a symptom-based approach to a more refined, multidimensional system. One pivotal aspect of this evolution is the integration of neuroimaging techniques, particularly magnetic resonance imaging (MRI) and functional imaging modalities. These tools have unveiled the intricate neural networks implicated in epilepsy, facilitating the identification of distinct brain abnormalities and the categorization of epilepsy subtypes based on structural and functional findings. Furthermore, the role of genetics has become increasingly prominent in epilepsy classification. Genetic discoveries have not only unraveled the molecular underpinnings of various epileptic syndromes but have also provided valuable diagnostic and prognostic insights. This narrative review delves into the expanding realm of genetic testing and its impact on tailoring treatment strategies to individual patients. As the classification landscape evolves, there are accompanying challenges. The narrative review underscores the transformative potential of artificial intelligence and machine learning in epilepsy classification. These technologies hold promise in automating the analysis of complex neuroimaging and genetic data, offering enhanced accuracy and efficiency in epilepsy diagnosis and classification. In conclusion, navigating the shifting landscape of epilepsy classification is a journey marked by progress, complexity, and the prospect of improved patient care. We are charting a course toward more precise diagnoses and tailored treatments by embracing advanced neuroimaging, genetics, and innovative technologies. As the field continues to evolve, collaborative efforts and a holistic understanding of epilepsy's diverse manifestations will be instrumental in harnessing the full potential of this dynamic landscape.