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

Development of a nomogram model for early prediction of refractory convulsive status epilepticus

INTRODUCTION

We aim to identify risk factors that predict refractory convulsive status epilepticus (RCSE) and to develop a model for early recognition of patients at high risk for RCSE.

METHODS

This study involved 200 patients diagnosed with convulsive status epilepticus (CSE), of whom 73 were RCSE and 127 were non-RCSE. Variables included demographic information, lifestyle factors, medical history, comorbidities, clinical symptoms, neuroimaging characteristics, laboratory tests, and nutritional scores. A predictive model was developed through multivariable logistic regression analysis. The model's predictive performance and clinical utility were evaluated using various metrics, including the area under the receiver operating characteristic (AUROC) curve, GiViTI calibration belt, and decision curve analysis (DCA). Additionally, we performed internal five-fold cross-validation for this model.

RESULTS

We developed a nomogram model with six predictors: age ≤ 40 years, prior history of epilepsy, presence of epileptic foci, duration of CSE > 30 min, c-reactive protein > 6 mg/L, and nutritional risk screening ≥ 3 points. Our model has a high AUROC (0.838) and good consistency (P = 0.999). In DCA, the curve of our model exhibits a positive net benefit across the entire range of threshold probabilities. Moreover, our model achieved an accuracy of 0.778 and a Kappa value of 0.519 in the five-fold cross-validation.

CONCLUSION

We developed an objective, simple and accessible model to assess the risk of RCSE. This model shows promise as a valuable tool for evaluating the individual risk of RCSE.

Acute symptomatic seizures in patients with recurrent ischemic stroke: A multicentric study

OBJECTIVE

Epileptic seizures occur frequently after stroke due to changes in brain function and structure, and up to around 10% of stroke patients experience stroke recurrence in the first year. We aimed to establish the risk of acute symptomatic seizures in patients with recurrent stroke.

METHODS

Retrospective cohort study including consecutive admissions to a Stroke Unit due to acute ischemic stroke, during a 5-year period. Additional inclusion of patients admitted to two centers in different countries to corroborate findings (confirmatory cohort). We aimed to compare acute symptomatic seizure incidence in patients with and without previous stroke. Patients with history of epilepsy were excluded. Logistic regression modeling was performed to identify predictors in middle cerebral artery (MCA) stroke.

RESULTS

We included 1473 patients (1085 with MCA stroke), of which 117 had a recurrent ischemic stroke (84 with MCA stroke). Patients with recurrent stroke had a seizure risk during hospital stay similar to that of patients with a first-ever stroke (5.1% vs. 4.5%, OR 1.15, 95% CI .48-2.71, p = .75). Risk of acute symptomatic seizures was also similar (5.0% vs. 4.1, OR 1.22, 95% CI .29-5.27, p = .78). Older age, female sex, and hemorrhagic transformation were predictors of seizures in patients with a first MCA ischemic stroke, but not in recurrent stroke patients. Electrographic characteristics were similar between the two groups in patients who had an electroencephalogram (46 with first stroke, 5 with recurrent stroke). The low rate of seizures (1.5%) in the confirmatory cohort (n = 198) precluded full comparison with the initial cohort. Nevertheless, the rate of seizures was not higher in stroke recurrence.

SIGNIFICANCE

History of previous stroke was not associated with an increased risk of acute symptomatic seizures during hospital stay. Larger, prospective studies, with prospective electrophysiological evaluation, are needed to explore the impact of stroke recurrence on seizure risk.

Causal associations of ischemic stroke, metabolic factors, and related medications with epilepsy: a Mendelian randomization study

Background

Earlier researches have demonstrated that ischemic stroke, metabolic factors, and associated medications may influence the risk of epilepsy. Nevertheless, the causality between these elements and epilepsy remains inconclusive. This study aims to examine whether ischemic stroke, metabolic factors, and related medications affect the overall risk of epilepsy.

Methods

We used single nucleotide polymorphisms associated with ischemic stroke, hypothyroidism, hypertension, blood glucose levels, high cholesterol, serum 25-Hydroxyvitamin D levels, testosterone, HMG CoA reductase inhibitors, and beta-blocking agents as instrumental variables in a Mendelian randomization technique to investigate causality with epilepsy. Multiple sensitivity methods were performed to evaluate pleiotropy and heterogeneity.

Results

The IVW analysis revealed positive associations between ischemic stroke (OR = 1.29; p = 0.020), hypothyroidism (OR = 1.05; p = 0.048), high blood pressure (OR = 1.10; p = 0.028), high cholesterol (OR = 1.10; p = 0.024), HMG CoA reductase inhibitors (OR = 1.19; p = 0.003), beta-blocking agents (OR = 1.20; p = 0.006), and the risk of epilepsy. Conversely, blood glucose levels (OR = 0.79; p = 0.009), serum 25-Hydroxyvitamin D levels (OR = 0.75; p = 0.020), and testosterone (OR = 0.62; p = 0.019) exhibited negative associations with the risk of epilepsy. Sensitivity analyses confirmed the robustness of these findings (p > 0.05).

Conclusion

Our research suggests that ischemic stroke, hypothyroidism, high blood pressure, high cholesterol, HMG CoA reductase inhibitors, and beta-blockers may increase the risk of epilepsy, whereas serum 25-Hydroxyvitamin D levels and blood glucose levels may reduce the risk.

Prediction of epilepsy after stroke: Proposal of a modified SeLECT 2.0 score based on posttreatment stroke outcome

OBJECTIVE

The SeLECT 2.0 score is a prognostic model of epilepsy after ischemic stroke. We explored whether replacing the severity of stroke at admission with the severity of stroke after treatment at 72 h from onset could improve the predictive accuracy of the score.

METHODS

We retrospectively identified consecutive adults with acute first-ever neuroimaging-confirmed ischemic stroke who were admitted to the Stroke Unit of the Ospedale Civile Baggiovara (Modena, Italy) and treated with intravenous thrombolysis and/or endovascular treatment. Study outcome was the occurrence of at least one unprovoked seizure presenting >7 days after stroke.

RESULTS

Participants included in the analysis numbered 1094. The median age of the subjects was 74 (interquartile range [IQR] = 64-81) years, and 595 (54.4%) were males. Sixty-five (5.9%) subjects developed unprovoked seizures a median of 10 (IQR = 6-27) months after stroke. The median values of the original and modified SeLECT2.0 scores were 3 (IQR = 2-4) and 2 (IQR = 1-3). The modified SeLECT 2.0 score showed better discrimination for the prediction of poststroke epilepsy at 36, 48, and 60 months after stroke compared to the original score according to the area under time-dependent receiver operating characteristic curves. The modified SeLECT 2.0 score had higher values of Harrell C and Somers D parameters and lower values of Akaike and Bayesian information criteria than the original score. The modified SeLECT 2.0 score produced more accurate risk predictions compared to the SeLECT 2.0 score at all evaluated time points from 12 to 60 months after stroke according to the Net Reclassification Index.

SIGNIFICANCE

Replacing baseline with posttreatment stroke severity may improve the ability of the SeLECT 2.0 score to predict poststroke epilepsy.

Evolution of EEG Findings in Patients with Acute Brain Injury

Introduction

Increasing use of continuous EEG monitoring (cEEG) provides the opportunity to observe temporal trends in EEG patterns during the acute phase of brain injury. These trends have not been extensively documented.

Methods

We conducted a retrospective chart review of patients undergoing cEEG between January 1st and June 30th, 2019, at two academic medical centers. Only patients with acute brain injury having electrographic or electroclinical seizures or epileptic EEG findings on day one of monitoring and ≥ two calendar days of cEEG were included. The temporal evolution of EEG patterns was depicted as a heatmap.

Results

Of 1356 screened patients, 101 met the study criteria. Clinical acute symptomatic seizures occurred in 30 patients (29.7%) prior to EEG. The median number of days of cEEG was four (IQR 3-6). Amongst patients with electrographic seizures, status epilepticus, generalized periodic discharges, or sporadic epileptiform discharges, 24.6% had improvement and 54.1% had resolution of epileptic EEG findings by the final day of monitoring. In contrast, 65% with lateralized periodic discharges or lateralized rhythmic delta activity persisted or worsened. Overall, 61.4% (62/101) showed either improvement (19.8%) or resolution (41.6%) of their EEG findings prior to hospital discharge. Of the 36 patients with follow-up EEGs at a median of 4.5 (IQR 3-8) months after admission for acute brain injury, 83% (30/36) showed either improvement (1/36; 2.7%) or resolution (29/36; 80.6%).

Conclusions

We observed a trend towards normalization of most epileptiform patterns except LPDs and LRDA, over time in patients with acute brain injury. The clinical significance of this trend as it relates to antiseizure medication treatment and neurologic outcomes warrants further investigation in an independent cohort.

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy

BACKGROUND

Epilepsy is a serious complication after an ischemic stroke. Although two studies have developed prediction model for post-stroke epilepsy (PSE), their accuracy remains insufficient, and their applicability to different populations is uncertain. With the rapid advancement of computer technology, machine learning (ML) offers new opportunities for creating more accurate prediction models. However, the potential of ML in predicting PSE is still not well understood. The purpose of this study was to develop prediction models for PSE among ischemic stroke patients.

METHODS

Patients with ischemic stroke from two stroke centers were included in this retrospective cohort study. At the baseline level, 33 input variables were considered candidate features. The 2-year PSE prediction models in the derivation cohort were built using six ML algorithms. The predictive performance of these machine learning models required further appraisal and comparison with the reference model using the conventional triage classification information. The Shapley additive explanation (SHAP), based on fair profit allocation among many stakeholders according to their contributions, is used to interpret the predicted outcomes of the naive Bayes (NB) model.

RESULTS

A total of 1977 patients were included to build the predictive model for PSE. The Boruta method identified NIHSS score, hospital length of stay, D-dimer level, and cortical involvement as the optimal features, with the receiver operating characteristic curves ranging from 0.709 to 0.849. An additional 870 patients were used to validate the ML and reference models. The NB model achieved the best performance among the PSE prediction models with an area under the receiver operating curve of 0.757. At the 20 % absolute risk threshold, the NB model also provided a sensitivity of 0.739 and a specificity of 0.720. The reference model had poor sensitivities of only 0.15 despite achieving a helpful AUC of 0.732. Furthermore, the SHAP method analysis demonstrated that a higher NIHSS score, longer hospital length of stay, higher D-dimer level, and cortical involvement were positive predictors of epilepsy after ischemic stroke.

CONCLUSIONS

Our study confirmed the feasibility of applying the ML method to use easy-to-obtain variables for accurate prediction of PSE and provided improved strategies and effective resource allocation for high-risk patients. In addition, the SHAP method could improve model transparency and make it easier for clinicians to grasp the prediction model's reliability.

Early seizures and risk of epilepsy and death after intracerebral haemorrhage: The MUCH Italy

INTRODUCTION

It is unclear which patients with non-traumatic (spontaneous) intracerebral haemorrhage (ICH) are at risk of developing acute symptomatic seizures (provoked seizures occurring within the first week after stroke onset; early seizures, ES) and whether ES predispose to the occurrence of remote symptomatic seizures (unprovoked seizures occurring more than 1 week after stroke; post-stroke epilepsy, PSE) and long-term mortality.

PATIENTS AND METHODS

In the setting of the Multicenter Study on Cerebral Haemorrhage in Italy (MUCH-Italy) we examined the risk of ES and whether they predict the occurrence of PSE and all-cause mortality in a cohort of patients with first-ever spontaneous ICH and no previous history of epilepsy, consecutively hospitalized in 12 Italian neurological centers from 2002 to 2014.

RESULTS

Among 2570 patients (mean age, 73.4 ± 12.5 years; males, 55.4%) 228 (8.9%) had acute ES (183 (7.1%) short seizures and 45 (1.8%) status epilepticus (SE)). Lobar location of the hematoma (OR, 1.49; 95% CI, 1.06-2.08) was independently associated with the occurrence of ES. Of the 2,037 patients who were followed-up (median follow-up time, 68.0 months (25th-75th percentile, 77.0)), 155 (7.6%) developed PSE. ES (aHR, 2.34; 95% CI, 1.42-3.85), especially when presenting as short seizures (aHR, 2.35; 95% CI, 1.38-4.00) were associated to PSE occurrence. Unlike short seizures, SE was an independent predictor of all-cause mortality (aHR, 1.50; 95% CI, 1.005-2.26).

DISCUSSION AND CONCLUSION

The long-term risk of PSE and death after an ICH vary according to ES subtype. This might have implications for the design of future clinical trials targeting post-ICH epileptic seizures.

Double, Double Toil and Trouble: Recurrent Episodes of Status Epilepticus Are Associated With Increasingly Worse Outcomes

Clinical Characteristics and Outcomes of Patients With Recurrent Status Epilepticus Episodes Bauer K, Rosenow F, Knake S, Willems LM, Kämppi L, Strzelczyk A. Neurol Res Pract . 2023;5(1):34. doi:10.1186/s42466-023-00261-9 Background: Multiple studies have focused on medical and pharmacological treatments and outcome predictors of patients with status epilepticus (SE). However, a sufficient understanding of recurrent episodes of SE is lacking. Therefore, we reviewed recurrent SE episodes to investigate their clinical characteristics and outcomes in patients with relapses. Methods: In this retrospective, multicenter study, we reviewed recurrent SE patient data covering 2011 to 2017 from the university hospitals of Frankfurt and Marburg, Germany. Clinical characteristics and outcome variables were compared among the first and subsequent SE episodes using a standardized form for data collection. Results: We identified 120 recurrent SE episodes in 80 patients (10.2% of all 1177 episodes). The mean age at the first SE episode was 62.2 years (median 66.5; SD 19.3; range 21–91), and 42 of these patients were male (52.5%). A mean of 262.4 days passed between the first and the second episode. Tonic–clonic seizure semiology and a cerebrovascular disease etiology were predominant in initial and recurrent episodes. After subsequent episodes, patients showed increased disability as indicated by the modified Rankin Scale (mRS), and 9 out of 80 patients died during the second episode (11.3%). Increases in refractory and super-refractory SE (RSE and SRSE, respectively) were noted during the second episode, and the occurrence of a non-refractory SE (NRSE) during the first SE episode did not necessarily provide a protective marker for subsequent non-refractory episodes. An increase in the use of intravenous-available anti-seizure medication (ASM) was observed in the treatment of SE patients. Patients were discharged from hospital with a mean of 2.8 ± 1.0 ASMs after the second SE episode and 2.1 ± 1.2 ASMs after the first episode. Levetiracetam was the most common ASM used before admission and on discharge for SE patients. Conclusions: This retrospective, multicenter study used the mRS to demonstrate worsened outcomes of patients at consecutive SE episodes. ASM accumulations after subsequent SE episodes were registered over the study period. The study results underline the necessity for improved clinical follow-ups and outpatient care to reduce the health care burden from recurrent SE episodes.

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.

Futile recanalization is associated with increased risk of post-stroke epilepsy

BACKGROUND

Endovascular treatment (EVT) is the standard of care of ischaemic stroke due to occlusion of large vessels. Although EVT can significantly improve short- and long-term outcomes, functional dependence can persist despite the achievement of a successful recanalization. The evidence about the predictors of post-stroke epilepsy (PSE) in patients with stroke treated by EVT is limited. We aimed to evaluate the relationship between futile recanalization and the risk of PSE.

METHODS

We retrospectively identified consecutive adults with first-ever ischaemic stroke of anterior circulation who were treated with EVT. Futile recanalization was defined as poor 3-month functional status (modified Rankin scale score ≥ 3) despite complete or near-complete recanalization. Study outcome was the occurrence of PSE during the follow-up.

RESULTS

The study included 327 patients with anterior circulation ischaemic stroke treated with EVT. Futile recanalization occurred in 116 (35.5%) patients and 26 (8.0%) developed PSE during a median follow-up of 35 [interquartile range, 22.7-55.2] months. Futile recanalization was more common among patients who developed PSE compared to those who did not (76.9% versus 31.9%; p < 0.001). Futile recanalization [hazard ratio (HR) = 5.63, 95% confidence interval (CI): 1.88-16.84; p = 0.002], large artery atherosclerosis (HR = 3.48, 95% CI: 1.44-8.40; p = 0.006), cortical involvement (HR = 15.51, 95% CI: 2.06-116.98; p = 0.008), and acute symptomatic status epilepticus (HR = 14.40, 95% CI: 2.80-73.98; p = 0.001) increased the risk of PSE.

CONCLUSIONS

Futile recanalization after EVT is associated with increased risk of PSE in patients with ischaemic stroke due to occlusion of large vessel of the anterior circulation.

Late onset epilepsy and stroke: Diagnosis, pathogenesis and prevention

The association of stroke and late-onset epilepsy (LOE) is discussed with special regard to its diagnosis, pathogenesis, and prevention. In addition to epidemiological data, including those from different age groups, the mechanisms for the development of acute symptomatic and remote symptomatic seizures are reviewed. The risk factors associated with seizures and post-stroke epilepsy (PSE) are considered, along with the methodological limitations of the study. For future research, the distinction between acute and remote symptomatic seizure before or after seven days from stroke onset should be reviewed because different acute symptomatic seizures (ASSs) themselves can entail a variable PSE risk. The definition of LOE by age is hitherto inconsistent. Comparing adult lifespan epochs, it is evident that stroke and seizures exhibit similar prevalence profiles. Young adulthood, old adulthood, and elderly epochs may be relevant for the differentiation of LOE subtype by age, vascular comorbidity, and other characteristics. A step-scheme strategy as a possible contribution to cerebrovascular prevention approaches is proposed.

Pathophysiology, Diagnosis, Prognosis, and Prevention of Poststroke Epilepsy: Clinical and Research Implications

Poststroke epilepsy (PSE) is associated with higher mortality and poor functional and cognitive outcomes in patients with stroke. With the remarkable development of acute stroke treatment, there is a growing number of survivors with PSE. Although approximately 10% of patients with stroke develop PSE, given the significant burden of stroke worldwide, PSE is a significant problem in stroke survivors. Therefore, the attention of health policymakers and significant funding are required to promote PSE prevention research. The current PSE definition includes unprovoked seizures occurring more than 7 days after stroke onset, given the high recurrence risks of seizures. However, the pathologic cascade of stroke is not uniform, indicating the need for a tissue-based approach rather than a time-based one to distinguish early seizures from late seizures. EEG is a commonly used tool in the diagnostic work-up of PSE. EEG findings during the acute phase of stroke can potentially stratify the risk of subsequent seizures and predict the development of poststroke epileptogenesis. Recent reports suggest that cortical superficial siderosis, which may be involved in epileptogenesis, is a promising marker for PSE. By incorporating such markers, future risk-scoring models could guide treatment strategies, particularly for the primary prophylaxis of PSE. To date, drugs that prevent poststroke epileptogenesis are lacking. The primary challenge involves the substantial cost burden due to the difficulty of reliably enrolling patients who develop PSE. There is, therefore, a critical need to determine reliable biomarkers for PSE. The goal is to be able to use them for trial enrichment and as a surrogate outcome measure for epileptogenesis. Moreover, seizure prophylaxis is essential to prevent functional and cognitive decline in stroke survivors. Further elucidation of factors that contribute to poststroke epileptogenesis is eagerly awaited. Meanwhile, the regimen of antiseizure medications should be based on individual cardiovascular risk, psychosomatic comorbidities, and concomitant medications. This review summarizes the current understanding of poststroke epileptogenesis, its risks, prognostic models, prophylaxis, and strategies for secondary prevention of seizures and suggests strategies to advance research on PSE.

The Association of Epileptic Seizures after Acute Ischemic Stroke with Cerebral Cortical Involvement and Electroencephalographic Changes

Background and objectives: while acute ischemic stroke is the leading cause of epilepsy in the elderly population, data about its risk factors have been conflicting. Therefore, the aim of our study is to determine the association of early and late epileptic seizures after acute ischemic stroke with cerebral cortical involvement and electroencephalographic changes. Materials and methods: a prospective cohort study in the Hospital of the Lithuanian University of Health Sciences Kaunas Clinics Department of Neurology was conducted and enrolled 376 acute ischemic stroke patients. Data about the demographical, clinical, radiological, and encephalographic changes was gathered. Patients were followed for 1 year after stroke and assessed for late ES. Results: the incidence of ES was 4.5%, the incidence of early ES was 2.7% and the incidence of late ES was 2.4%. The occurrence of early ES increased the probability of developing late ES. There was no association between acute cerebral cortical damage and the occurrence of ES, including both early and late ES. However, interictal epileptiform discharges were associated with the occurrence of ES, including both early and late ES.

Status Epilepticus after mechanical thrombectomy: The role of early EEG assessment in Stroke Unit, clinical and radiological prognostication

BACKGROUND

Convulsive (CSE) and non-convulsive (NCSE) Status Epilepticus are a complication in 0.2-0.3% ischemic strokes. Large stroke and cortical involvement are the main risk factors for developing SE. This study evaluates the prevalence of SE in patients treated with endovascular thrombectomy (EVT) through EEG recording within 72- h from admission. Moreover, we compared clinical, radiological, and outcome measures in SE and no-SE patients.

MATERIALS AND METHODS

We collected retrospectively demographical and clinical characteristics of acute ischemic stroke patients who underwent EVT, admitted in the Stroke Unit (SU) of the University Hospital of Trieste between January 2018 and March 2020 who underwent EEG recording within 72- h from the symptoms' onset.

RESULTS

Out of 247 EVT patients, 138 met the inclusion criteria, of whom 9 (6.5%) showed SE with median onset time of 1 day (IQR 1-2). No difference was found between the two groups as for age, sex, risk factors, grade of recanalization, etiology of stroke, and closed vessel. The no-SE group presented higher NIHSS improvement rate (p=0.025) compared to the SE group. The sum of the lobes involved in the ischemic lesion was significantly higher in SE group (p=0.048).

CONCLUSION

SE after EVT in large strokes is a non-rare complication, with most being NCSE. Performing a rapid EEG assessment in a Stroke Unit setting may allow for a prompt recognition and treatment of SE in the acute/hyper-acute phase. SE may be correlated with worse clinical outcomes in patients with large vessel occlusion.

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.

Risk Factors and Temporal Patterns of Poststroke Epilepsy across Stroke Subtypes: Insights from a Nationwide Cohort Study in Korea

INTRODUCTION

We aimed to investigate the risk factors associated with poststroke epilepsy (PSE) among patients with different subtypes of stroke, focusing on age-related risk and time-varying effects of stroke subtypes on PSE development.

METHODS

A retrospective, nationwide, population-based cohort study was conducted using Korean National Health Insurance Service-National Sample Cohort data. Patients hospitalized with newly diagnosed stroke from 2005 to 2015 were included and followed up for up to 10 years. The primary outcome was the development of PSE, defined as having a diagnostic code and a prescription for anti-seizure medication. Multivariable Cox proportional hazard models were used to estimate PSE hazard ratios (HRs), and time-varying effects were also assessed.

RESULTS

A total of 8,305 patients with ischemic stroke, 1,563 with intracerebral hemorrhage (ICH), and 931 with subarachnoid hemorrhage (SAH) were included. During 10 years of follow-up, 4.6% of patients developed PSE. Among patients with ischemic stroke, significant risk factors for PSE were younger age (HR = 1.47), living in rural areas (HR = 1.35), admission through the emergency room (HR = 1.33), and longer duration of hospital stay (HR = 1.45). Time-varying analysis revealed elevated HRs for ICH and SAH, particularly in the first 2 years following the stroke. The age-specific HRs also showed an increased risk for those under the age of 65, with a noticeable decrease in risk beyond that age.

CONCLUSION

The risk of developing PSE varies according to stroke subtype, age, and other demographic factors. These findings underscore the importance of tailored poststroke monitoring and management strategies to mitigate the risk of PSE.

Neutrophil to lymphocyte ratio and early seizures after ischemic stroke: A case-control study

BACKGROUND

Early post-stroke seizures (EPSS) are associated with an increased risk of mortality and post-stroke epilepsy. This study aimed to identify potential risk factors for EPSS, focusing on blood parameters, such as the neutrophil-to-lymphocyte ratio (NLR), which is a biomarker for inflammation.

METHODS

Patients treated for ischemic stroke between 2017 and 2019 were retrospectively identified. 44 of them had a first epileptic seizure within 7 days after the stroke. They were matched 1:2 for age and sex with controls who had a stroke but no EPSS. Information on demographics, stroke characteristics, and blood parameters were collected on admission. Logistic regression was used to identify variables associated with EPSS and the area under the receiver operating characteristic curve (AUROC) to estimate their predictive accuracy.

RESULTS

The NLR value (p = 0.035), National Institutes of Health Stroke Scale (NIHSS) (p = 0.016) and cortical localization of stroke (p = 0.03) were significantly correlated with the occurrence of EPSS in univariate logistic regression. In multivariable logistic regression, after adjusting for age, sex, baseline NIHSS, and stroke localization, the NLR values [adjusted odds ratio 1.097, 95% confidence interval (CI): 1.005-1.197; p = 0.038] were independently associated with the occurrence of EPSS. The AUROC for NLR was 0.639 (95% CI: 0.517-0.761) with 2.98 as the best predictive cut-off value. There was a significant positive relationship between NLR and NIHSS, rS(87) = 0.383, p = <0.001.

CONCLUSION

Higher NLR values were associated with increased risk of EPSS. This biomarker appears useful to assess the risk of developing EPSS.

Clinical data mining: challenges, opportunities, and recommendations for translational applications

Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

The added value of risk assessment and subsequent targeted treatment for epileptic seizures after stroke: An early-HTA analysis

INTRODUCTION

The development of post-stroke epilepsy (PSE) is related to a worse clinical outcome in stroke patients. Adding a biomarker to the clinical diagnostic process for the prediction of PSE may help to establish targeted and personalized treatment for high-risk patients, which could lead to improved patient outcomes. We assessed the added value of a risk assessment and subsequent targeted treatment by conducting an early Health Technology Assessment.

METHODS

Interviews were conducted with four relevant stakeholders in the field of PSE to obtain a realistic view of the current healthcare and their opinions on the potential value of a PSE risk assessment and subsequent targeted treatment. The consequences on quality of life and costs of current care of a hypothetical care pathway with perfect risk assessment were modeled based on information from a literature review and the input from the stakeholders. Subsequently, the maximum added value (the headroom) was calculated. Sensitivity analyses were performed to test the robustness of this result to variation in assumed input parameters, i.e. the accuracy of the risk assessment, the efficacy of anti-seizure medication (ASM), and the probability of patients expected to develop PSE.

RESULTS

All stakeholders considered the addition of a predictive biomarker for the risk assessment of PSE to be of value. The headroom amounted to €12,983. The sensitivity analyses demonstrated that the headroom remained beneficial when varying the accuracy of the risk assessment, the ASM efficacy, and the number of patients expected to develop PSE.

DISCUSSION

We showed that a risk assessment for PSE development is potentially valuable. This work demonstrates that it is worthwhile to undertake clinical studies to evaluate biomarkers for the prediction of patients at high risk for PSE and to assess the value of targeted prophylactic treatment.

Prognostic value of early electrographic biomarkers of epileptogenesis in high-risk ischaemic stroke patients

BACKGROUND AND PURPOSE

Post-stroke epilepsy (PSE) is frequent. Better prediction of PSE would enable individualized management and improve trial design for epilepsy prevention. The aim was to assess the complementary value of continuous electroencephalography (EEG) data during the acute phase compared with clinical risk factors currently used to predict PSE.

METHODS

A prospective cohort of 81 patients with ischaemic stroke who received early continuous EEG monitoring was studied to assess the association of early EEG seizures, other highly epileptogenic rhythmic and periodic patterns, and regional attenuation without delta (RAWOD, an EEG pattern of stroke severity) with PSE. Clinical risk factors were investigated using the SeLECT (stroke severity; large-artery atherosclerosis; early clinical seizures; cortical involvement; territory of middle cerebral artery) scores.

RESULTS

Twelve (15%) patients developed PSE. The presence of any of the investigated patterns was associated with a risk of epilepsy of 46%, with a sensitivity and specificity of 83% and 78%. The association remained significant after adjusting for the SeLECT score (odds ratio 18.8, interquartile range 3.8-72.7).

CONCLUSIONS

It was found that highly epileptogenic rhythmic and periodic patterns and RAWOD were associated with the development of PSE and complemented clinical risk factors. These findings indicate that continuous EEG provides useful information to determine patients at higher risk of developing PSE and could help individualize care.

Acute symptomatic seizures after stroke: A scoping review on primary prevention, treatment with antiseizure medications and drug discontinuation

AIM

To evaluate and synthesize the evidence and knowledge gaps on primary prevention and treatment of post-stroke acute symptomatic seizures (ASSs) using antiseizure medications (ASMs).

METHODS

We systematically searched of EMBASE, MEDLINE (accessed from PubMed), and the Cochrane Central Register of Controlled Trials (CENTRAL) to include randomized, double- or single-blinded trials (RCTs) on primary prophylaxis and treatment of post-stroke ASSs with ASMs. The risk of bias in the included studies was assessed according to the recommendations of the Cochrane Handbook for Systematic Reviews of Interventions.

RESULTS

Two placebo-controlled RCTs (totaling 114 participants) evaluating valproate or levetiracetam as primary prophylaxis of ASSs due to hemorrhagic stroke were included. In one RCT, post-stroke ASS occurred in 1/36 patients (2.7%) on valproate and in 4/36 patients (7%) on placebo (p = 0.4). In the other RCT, ASSs were only electrographic and occurred in 3/19 (16%) with levetiracetam and in 10/23 (43%) with placebo (p = 0.043). We found no RCTs on the treatment of post-stroke ASSs or discontinuation of ASMs administered for the treatment of post-stroke ASSs.

CONCLUSION

Evidence to support primary prophylaxis of ASSs is sparse and of very low quality and is insufficient to recommend it routinely. Secondary prevention of post-stroke ASSs is usually not recommended except in selected cases (the most relevant being acute symptomatic status epilepticus, which carries a high risk of subsequent poststroke seizures (PSE)). The choice of which ASM to administer and for how long is not based on solid RCT evidence. Management of post-stroke PSE should be done according to an evidence-based framework, considering the individuality of the patient and the pharmacological properties of the drugs.

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.

Acute Symptomatic Seizures After Ischemic Strokes: Time Is Brain, Squared!

Association of Mortality and Risk of Epilepsy With Type of Acute Symptomatic Seizure After Ischemic Stroke and an Updated Prognostic Model Sinka L, Abraira L, Imbach LL, Zieglgänsberger D, Santamarina E, Álvarez-Sabín J, Ferreira-Atuesta C, Katan M, Scherrer N, Bicciato G, Terziev R, Simmen C, Schubert KM, Elshahabi A, Baumann CR, Döhler N, Erdélyi-Canavese B, Felbecker A, Siebel P, Winklehner M, von Oertzen TJ, Wagner JN, Gigli GL, Serafini A, Nilo A, Janes F, Merlino G, Valente M, Zafra-Sierra MP, Bayona-Ortiz H, Conrad J, Evers S, Lochner P, Roell F, Brigo F, Bentes C, Peralta AR, Pinho E Melo T, Keezer MR, Duncan JS, Sander JW, Tettenborn B, Koepp MJ, Galovic M. JAMA Neurol . 2023;80(6):605-613. doi:10.1001/jamaneurol.2023.0611 . PMID: 37036702 ; PMCID: PMC10087089 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 anti-seizure medication treatment and the methods and frequency of follow-up.

Association of comorbid-socioeconomic clusters with mortality in late onset epilepsy derived through unsupervised machine learning

BACKGROUND AND OBJECTIVES

Late-onset epilepsy is a heterogenous entity associated with specific aetiologies and an elevated risk of premature mortality. Specific multimorbid-socioeconomic profiles and their unique prognostic trajectories have not been described. We sought to determine if specific clusters of late onset epilepsy exist, and whether they have unique hazards of premature mortality.

METHODS

We performed a retrospective observational cohort study linking primary and hospital-based UK electronic health records with vital statistics data (covering years 1998-2019) to identify all cases of incident late onset epilepsy (from people aged ≥65) and 1:10 age, sex, and GP practice-matched controls. We applied hierarchical agglomerative clustering using common aetiologies identified at baseline to define multimorbid-socioeconomic profiles, compare hazards of early mortality, and tabulating causes of death stratified by cluster.

RESULTS

From 1,032,129 people aged ≥65, we identified 1048 cases of late onset epilepsy who were matched to 10,259 controls. Median age at epilepsy diagnosis was 68 (interquartile range: 66-72) and 474 (45%) were female. The hazard of premature mortality related to late-onset epilepsy was higher than matched controls (hazard ratio [HR] 1.73; 95% confidence interval [95%CI] 1.51-1.99). Ten unique phenotypic clusters were identified, defined by 'healthy' males and females, ischaemic stroke, intracerebral haemorrhage (ICH), ICH and alcohol misuse, dementia and anxiety, anxiety, depression in males and females, and brain tumours. Cluster-specific hazards were often similar to that derived for late-onset epilepsy as a whole. Clusters that differed significantly from the base late-onset epilepsy hazard were 'dementia and anxiety' (HR 5.36; 95%CI 3.31-8.68), 'brain tumour' (HR 4.97; 95%CI 2.89-8.56), 'ICH and alcohol misuse' (HR 2.91; 95%CI 1.76-4.81), and 'ischaemic stroke' (HR 2.83; 95%CI 1.83-4.04). These cluster-specific risks were also elevated compared to those derived for tumours, dementia, ischaemic stroke, and ICH in the whole population. Seizure-related cause of death was uncommon and restricted to the ICH, ICH and alcohol misuse, and healthy female clusters.

SIGNIFICANCE

Late-onset epilepsy is an amalgam of unique phenotypic clusters that can be quantitatively defined. Late-onset epilepsy and cluster-specific comorbid profiles have complex effects on premature mortality above and beyond the base rates attributed to epilepsy and cluster-defining comorbidities alone.

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

BACKGROUND

Acute symptomatic epileptic seizures are frequently seen in neurocritical care. To prevent subsequent unprovoked seizures, long-term treatments with antiseizure medications are often initiated although supporting evidence is lacking. This study aimed at prospectively assessing the risk of unprovoked seizure relapse with respect to the use of antiseizure medications. It was hypothesized that after a first acute symptomatic seizure of structural etiology, the cumulative 12-month risk of unprovoked seizure relapse is ≤ 25%.

METHODS

Inclusion criteria were age ≥ 18 and acute symptomatic first-ever epileptic seizure; patients with status epilepticus were excluded. Using telephone and mail interviews, participants were followed for 12 months after the acute symptomatic first seizure. Primary endpoint was the occurrence and timing of a first unprovoked seizure relapse. In addition, neuro-intensivists in Germany were interviewed about their antiseizure treatment strategies through an anonymous online survey.

RESULTS

Eleven of 122 participants with structural etiology had an unprovoked seizure relapse, resulting in a cumulative 12-month risk of 10.7% (95%CI, 4.7%-16.7%). None of 19 participants with a non-structural etiology had a subsequent unprovoked seizure. Compared to structural etiology alone, combined infectious and structural etiology was independently associated with unprovoked seizure relapse (OR 11.1; 95%CI, 1.8-69.7). Median duration of antiseizure treatment was 3.4 months (IQR 0-9.3). Seven out of 11 participants had their unprovoked seizure relapse while taking antiseizure medication; longer treatment durations were not associated with decreased risk of unprovoked seizure relapse. Following the non-representative online survey, most neuro-intensivists consider 3 months or less of antiseizure medication to be adequate.

CONCLUSIONS

Even in case of structural etiology, acute symptomatic seizures bear a low risk of subsequent unprovoked seizures. There is still no evidence favoring long-term treatments with antiseizure medications. Hence, individual constellations with an increased risk of unprovoked seizure relapse should be identified, such as central nervous system infections causing structural brain damage. However, in the absence of high-risk features, antiseizure medications should be discontinued early to avoid overtreatment.