Prediction of late seizures after ischaemic stroke with a novel prognostic model (the SeLECT score): a multivariable prediction model development and validation study

Antiseizure Medication Withdrawal, Risk of Epilepsy, and Longterm EEG Trends in Acute Symptomatic Seizures or Epileptic EEG Patterns

Background and Objectives

Patients with acute symptomatic seizures (ASyS) and acute epileptiform findings on EEG are common. They are often prescribed long-term antiseizure medications (ASMs); it is unknown whether or when this is necessary. Primary outcome was late unprovoked seizure occurrence and association with ASM taper. The secondary outcome was EEG pattern evolution over time.

Methods

This is a retrospective cohort study of patients from 2015 to 2021 with ASyS (clinical or electrographic) and/or epileptiform findings on index hospitalization EEGs who were discharged on ASMs and had subsequent follow-up including an outpatient EEG at Yale New Haven Hospital. All patients were seen in our postacute symptomatic seizure (PASS) clinic after hospital discharge. We also developed a simple predictive score, Epilepsy-PASS (EPI-PASS), using variables independently associated with seizure recurrence based on stepwise regression; each of the 3 identified variables was assigned a score of 0 (absent) or 1 (present), for a total score of 0-3.

Results

Of 190 patients screened, 58 were excluded, leaving a final cohort of 112 patients. Twenty-four percent (27/112) patients developed a late unprovoked seizure (i.e., epilepsy). Independent predictors of epilepsy were persistence of epileptiform abnormalities on follow-up EEGs [56% developed epilepsy vs 19% without, 0.002, OR 7.18 (1.36-37.88)], clinical ASyS [32% vs 13%, p = 0.002, OR 7.45 (2.31-54.36)], and cortical involvement on imaging [40% vs 11%, p = 0.003, OR 7.63 (1.96-29.58)]. None of the 23 patients with none of these predictors (0 points on EPI-PASS) developed epilepsy, vs 13% with 1 predictor (EPI-PASS = 1) and 46% with 2 or 3 predictors (EPI-PASS = 2-3) at 1-year follow-up. ASM taper was not associated with seizure recurrence. Abnormal EEG findings in the index hospitalization usually resolved [54/69 (78%) patients] on subsequent EEGs.

Discussion

Most patients with clinical ASyS or acute epileptiform EEG findings do not require long-term ASMs. Index hospitalization EEG findings usually resolve, but if they do not, there is a >50% chance of developing epilepsy. Other predictors of epilepsy are cortical involvement on imaging and clinical ASyS. A simple 4-point scale using these 3 predictors (EPI-PASS) may help predict the risk of developing epilepsy but requires independent validation.

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.

Use of Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers Is Associated With a Reduced Risk of Poststroke Epilepsy in Patients With Ischemic Stroke

BACKGROUND

Poststroke epilepsy (PSE) is a common complication after ischemic stroke. This study investigates the association between the use of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) and the risk of PSE in patients with ischemic stroke.

METHODS AND RESULTS

A population-based retrospective cohort study was conducted using Taiwan's National Health Insurance Research Database between 2000 and 2015. Patients with hypertension with a history of ischemic stroke were classified into prevalent, new, and nonusers according to their use of ACEIs/ARBs. Prevalent ACEI/ARB users were further classified into continuing or discontinued users, based on their poststroke medication adherence. We used multivariate Cox regression models, adjusted for demographics and comorbidities, to assess the risk of PSE among different ACEI/ARB user groups. There were 182 983 ACEI/ARB users and 38 365 nonusers included. There were 7387 patients diagnosed with PSE, whereas 213 961 were not. Nonusers exhibited a higher risk of PSE (adjusted hazard ratio [aHR], 1.72 [95% CI, 1.63-1.82]). Both prevalent and nonusers had higher risks compared with new ACEI/ARB users, with respective aHRs of 1.33 (95% CI, 1.25-1.41) and 2.00 (95% CI, 1.87-2.14). Discontinued ACEI/ARB users showed the highest risk of PSE (aHR, 2.34 [95% CI, 2.15-2.54]), suggesting the importance of continuing ACEI/ARB use after stroke. Treatment-by-age interaction was significant among patients with or without ACEI/ARB use before stroke (P value for interaction 0.004 and <0.001, respectively), suggesting a stronger beneficial association in younger patients.

CONCLUSIONS

The use of ACEIs/ARBs after ischemic stroke in patients with hypertension is associated with a reduced risk of PSE, especially among younger patients.

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.

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.

New epilepsy therapies in development

Epilepsy is a common brain disorder, characterized by spontaneous recurrent seizures, with associated neuropsychiatric and cognitive comorbidities and increased mortality. Although people at risk can often be identified, interventions to prevent the development of the disorder are not available. Moreover, in at least 30% of patients, epilepsy cannot be controlled by current antiseizure medications (ASMs). As a result of considerable progress in epilepsy genetics and the development of novel disease models, drug screening technologies and innovative therapeutic modalities over the past 10 years, more than 200 novel epilepsy therapies are currently in the preclinical or clinical pipeline, including many treatments that act by new mechanisms. Assisted by diagnostic and predictive biomarkers, the treatment of epilepsy is undergoing paradigm shifts from symptom-only ASMs to disease prevention, and from broad trial-and-error treatments for seizures in general to mechanism-based treatments for specific epilepsy syndromes. In this Review, we assess recent progress in ASM development and outline future directions for the development of new therapies for the treatment and prevention of epilepsy.

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.

Revascularization Therapies for Ischemic Stroke and Association With Risk of Epilepsy: A Danish Nationwide Register-Based Study

BACKGROUND

The association between stroke revascularization therapies and poststroke epilepsy is only sparsely investigated, and results are conflicting. The aim of this study is to investigate whether stroke revascularization therapies are associated with different risks of poststroke epilepsy.

METHODS AND RESULTS

We conducted a nationwide, register-based, propensity score-matched cohort study. We identified 40 816 patients admitted with a first ischemic stroke and no prior history of epilepsy in Denmark between January 1, 2011, and December 16, 2018. Of these, 6541 were treated with thrombolysis, 379 with thrombectomy, and 1005 with both thrombolysis and thrombectomy. The 3 treatment groups were each matched 1:1 to patients with stroke not treated with revascularization. Exact matching was done for sex, while propensity scores included information on stroke severity, cortical involvement, age, comorbidities, and socioeconomic parameters. Outcome was any diagnosis of epilepsy. We used Cox regressions to estimate adjusted hazard ratios (HRs) of epilepsy after ischemic stroke. Compared with matched patients with ischemic stroke not receiving revascularization treatment, patients who received thrombolysis alone had 32% lower risk of epilepsy (adjusted HR, 0.68 [95% CI, 0.57-0.81]) and patients who received thrombolysis and thrombectomy had 45% lower risk of epilepsy (adjusted HR, 0.55 [95% CI, 0.41-0.73]). Thrombectomy alone was not associated with significantly lower risk of epilepsy compared with matched patients with ischemic stroke not receiving revascularization therapy (adjusted HR, 0.78 [95% CI, 0.57-1.29]).

CONCLUSIONS

Thrombolysis alone and in combination with thrombectomy in ischemic stroke was associated with lower risk of epilepsy, whereas thrombectomy alone was not associated with lower risk of epilepsy.

Safety and efficacy of concomitant treatment with non-vitamin K antagonist oral anticoagulants and antiseizure medications: A propensity score matching cohort study

Research on cerebrovascular events in atrial fibrillation (AF) patients taking non-vitamin K antagonist oral anticoagulants (NOACs) with antiseizure medications (ASMs) is limited, highlighting a significant gap in literature. We assessed thrombotic and hemorrhagic risks in patients on NOACs and ASMs versus those on NOACs or ASMs alone. We analyzed a retrospective cohort from five centers, including AF and epilepsy patients on both medications (n = 188), AF patients on NOACs (n = 298), and epilepsy patients on ASMs (n = 50), with a 3-year follow-up. Propensity score matching adjusted for cardiovascular risk differences. The primary outcomes were ischemic stroke, transient ischemic attack, and major bleeding. Results showed the ASM+NOAC group had a higher risk of primary outcomes compared to the NOAC-only group (5.68% vs. 1.18%, hazard ratio = 5.72, 95% confidence interval = 2.22-14.73), with no events in the ASM-only group. This suggests an increased risk for patients on combined NOAC and ASM therapy, underlining the need for careful drug interaction consideration.

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.

EEG biomarkers for the prediction of post-traumatic epilepsy - a systematic review of an emerging field

Traumatic brain injury (TBI) is often followed by post-traumatic epilepsy (PTE), a condition often difficult to treat and leading to a substantial decline in quality of life as well as increased long-term mortality. The latent period between TBI and the emergence of spontaneous recurrent seizures provides an opportunity for pharmacological intervention to prevent epileptogenesis. Biomarkers capable of predicting PTE development are urgently needed to facilitate clinical trials of putative anti-epileptogenic drugs. EEG is a widely available and flexible diagnostic modality that plays a fundamental role in epileptology. We systematically review the advances in the field of the discovery of EEG biomarkers for the prediction of PTE in humans. Despite recent progress, the field faces several challenges including short observation periods, a focus on early post-injury monitoring, difficulties in translating findings from animal models to scalp EEG, and emerging evidence indicating the importance of assessing altered background scalp EEG activity alongside epileptiform activity using quantitative EEG methods while also considering sleep abnormalities in future studies.

Early focal electroencephalogram and neuroimaging findings predict epilepsy development after aneurysmal subarachnoid hemorrhage

INTRODUCTION

Seizures are a common complication of subarachnoid hemorrhage (SAH) in both acute and late stages: 10-20 % acute symptomatic seizures, 12-25 % epilepsy rate at five years. Our aim was to identify early electroencephalogram (EEG) and computed tomography (CT) findings that could predict long-term epilepsy after SAH.

MATERIAL AND METHODS

This is a multicenter, retrospective, longitudinal study of adult patients with aneurysmal SAH admitted to two tertiary care hospitals between January 2011 to December 2022. Routine 30-minute EEG recording was performed in all subjects during admission period. Exclusion criteria were the presence of prior structural brain lesions and/or known epilepsy. We documented the presence of SAH-related cortical involvement in brain CT and focal electrographic abnormalities (epileptiform and non-epileptiform). Post-SAH epilepsy was defined as the occurrence of remote unprovoked seizures ≥ 7 days from the bleeding.

RESULTS

We included 278 patients with a median follow-up of 2.4 years. The mean age was 57 (+/-12) years, 188 (68 %) were female and 49 (17.6 %) developed epilepsy with a median latency of 174 days (IQR 49-479). Cortical brain lesions were present in 189 (68 %) and focal EEG abnormalities were detected in 158 patients (39 epileptiform discharges, 119 non-epileptiform abnormalities). The median delay to the first EEG recording was 6 days (IQR 2-12). Multiple Cox regression analysis showed higher risk of long-term epilepsy in those patients with CT cortical involvement (HR 2.6 [1.3-5.2], p 0.009), EEG focal non-epileptiform abnormalities (HR 3.7 [1.6-8.2], p 0.002) and epileptiform discharges (HR 6.7 [2.8-15.8], p < 0.001). Concomitant use of anesthetics and/or antiseizure medication during EEG recording had no influence over its predictive capacity. ROC-curve analysis of the model showed good predictive capability at 5 years (AUC 0.80, 95 %CI 0.74-0.87).

CONCLUSIONS

Focal electrographic abnormalities (both epileptiform and non-epileptiform abnormalities) and cortical involvement in neuroimaging predict the development of long-term epilepsy. In-patient EEG and CT findings could allow an early risk stratification and facilitate a personalized follow-up and management of SAH patients.

Direct Oral Anticoagulants and Concomitant Anti-seizure Medications: A Retrospective, Case-Control Study in a Real-World Setting

PURPOSE

Although prescription of direct oral anticoagulants (DOACs) for epileptic patients on anti-seizure medications (ASMs) is on the increase, international guidelines pose strict restrictions because this may lead to pharmacologic interactions. However, current evidence on their clinical relevance remains scanty. This retrospective, case-control study assessed the frequency of ischemic/hemorrhagic events and epileptic seizures involving DOAC-ASM cotherapy in the real world, compared with DOAC and ASM monotherapy, in age- and gender-matched controls.

METHODS

Data on patients who had been prescribed a concomitant DOAC and ASM therapy for at least 6 months were extracted from the database of the Pharmaceutical Service of the Alessandria Province (Italy). After exclusions, the case group included 124 patients, 44 on valproic acid (VPA) and 80 on levetiracetam (LEV) concomitant with a DOAC, and it was compared with the DOAC-control and ASM-control groups. The clinical and laboratory data were extracted from the electronic archives of the hospitals in the same province.

FINDINGS

Two (1.6%) ischemic and 2 (1.6%) major hemorrhagic events were observed in the case group. Four (3.2%) ischemic and no hemorrhagic events occurred in the DOAC-control group. There were no statistically significant differences in the ischemic and hemorrhagic events between the case group (patients on concomitant LEV or VPA who were prescribed a DOAC) and the DOAC-control group, and there was no difference in the recurrence rate of epileptic seizures between the case group and the ASM-control group.

IMPLICATIONS

Although this study has some limits, mainly the small sample size, our findings indicate that neither LEV nor VPA concomitant treatment significantly affects the effects of DOACs in a real-world setting.

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.

Effect of Intravenous Thrombolysis and Mechanical Thrombectomy on the Incidence of Acute Symptomatic Seizure and Post-Stroke Epilepsy in Patients with Acute Large-Vessel Occlusion

Objective

Reperfusion therapy, such as intravenous tissue-plasminogen activator (IV-tPA) and mechanical thrombectomy (MT) for acute ischemic stroke, may increase the incidence of acute symptomatic seizure (ASS) and post-stroke epilepsy (PSE). This study aimed to analyze the effect and predictors of reperfusion therapy for ASS and PSE limited to large-vessel occlusions (LVOs).

Methods

This retrospective study classified 237 subjects with LVO into four groups: (1) IV-tPA + MT+ (n = 74 cases, (2) MT only (n = 82), (3) tissue-plasminogen activator (tPA) only (n = 28), and (4) IV-tPA - MT- (n = 53). The incidences of ASS and PSE were assessed. Potential predictors, such as etiology, functional disability, neuroimaging findings, and the SeLECT score, were statistically analyzed.

Results

There were 12 (5.1%) subjects with ASS and 10 subjects (4.2%) with PSE. The IV-tPA and MT groups had significantly high reperfusion rates, with a Thrombolysis in Cerebral Infarction score ≥2c (p = 0.01) but there were no significant differences in the increases of hemorrhagic transformation, ASS, and PSE. An Alberta Stroke Program Early Computed Tomography Score <6 was a significant predictor of ASS (p = 0.01), and an infarct volume >60 ml was a significant predictor of PSE (p = 0.01).

Conclusion

Reperfusion therapy for acute LVO was not found to increase the risk of ASS and PSE. Large-sized infarctions should be treated with care in PSE.

Prognostic Implications of Early Prediction in Posttraumatic Epilepsy

Posttraumatic epilepsy (PTE) is a complication of traumatic brain injury that can increase morbidity, but predicting which patients may develop PTE remains a challenge. Much work has been done to identify a variety of risk factors and biomarkers, or a combination thereof, for patients at highest risk of PTE. However, several issues have hampered progress toward fully adapted PTE models. Such issues include the need for models that are well-validated, cost-effective, and account for competing outcomes like death. Additionally, while an accurate PTE prediction model can provide quantitative prognostic information, how such information is communicated to inform shared decision-making and treatment strategies requires consideration of an individual patient's clinical trajectory and unique values, especially given the current absence of direct anti-epileptogenic treatments. Future work exploring approaches integrating individualized communication of prediction model results are needed.

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.

Outpatient EEG in Routine Clinical Care of Patients With Stroke-Related Acute Symptomatic Seizure Concerns

PURPOSE

Acute symptomatic seizures (ASyS) after stroke contribute the highest risk to poststroke epilepsy (PSE) development. We investigated the use of outpatient EEG (oEEG) among stroke patients with ASyS concerns.

METHODS

Adults with acute stroke, ASyS concerns (underwent cEEG), and outpatient clinical follow-up were included (study population). Patients with oEEG (oEEG cohort) were analyzed for electrographic findings. Univariable and multivariable analyses helped identify predictors of oEEG use in routine clinical care.

RESULTS

Among 507 patients, 83 (16.4%) underwent oEEG. The independent predictors of oEEG utilization included age (OR = 1.03 [1.01 to 1.05, P = 0.01]), electrographic ASyS on cEEG (OR 3.9 [1.77 to 8.9], P < 0.001), ASMs at discharge (OR 3.6 [1.9 to 6.6], P < 0.001), PSE development (OR 6.6 [3.5 to 12.6], P < 0.001), and follow-up duration (OR = 1.01 [1.002 to 1.02], P = 0.016). Almost 40% of oEEG cohort developed PSE, but only 12% had epileptiform abnormalities. Close to a quarter (23%) of oEEGs were within normal limits.

CONCLUSIONS

One in six patients with ASyS concern after stroke undergoes oEEG. Electrographic ASyS, PSE development, and ASM at discharge are primary drivers of oEEG use. While PSE drives oEEG use, we need systematic, prospective investigation of outpatient EEG's role as prognostic tool for PSE development.

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.

Development and validation of a nomogram for predicting 28-day mortality in patients with ischemic stroke

BACKGROUND/AIM

We aimed to construct a validated nomogram model for predicting short-term (28-day) ischemic stroke mortality among critically ill populations.

MATERIALS AND METHODS

We collected raw data from the Medical Information Mart for Intensive Care IV database, a comprehensive repository renowned for its depth and breadth in critical care information. Subsequently, a rigorous analytical framework was employed, incorporating a 10-fold cross-validation procedure to ensure robustness and reliability. Leveraging advanced statistical methodologies, specifically the least absolute shrinkage and selection operator regression, variables pertinent to 28-day mortality in ischemic stroke were meticulously screened. Next, binary logistic regression was utilized to establish nomogram, then applied concordance index to evaluate discrimination of the prediction models. Predictive performance of the nomogram was assessed by integrated discrimination improvement (IDI) and net reclassification index (NRI). Additionally, we generated calibration curves to assess calibrating ability. Finally, we evaluated the nomogram's net clinical benefit using decision curve analysis (DCA), in comparison with scoring systems clinically applied under common conditions.

RESULTS

A total of 2089 individuals were identified and assigned into training (n = 1443) or validation (n = 646) cohorts. Various identified risk factors, including age, ethnicity, marital status, underlying metastatic solid tumor, Charlson comorbidity index, heart rate, Glasgow coma scale, glucose concentrations, white blood cells, sodium concentrations, potassium concentrations, mechanical ventilation, use of heparin and mannitol, were associated with short-term (28-day) mortality in ischemic stroke individuals. A concordance index of 0.834 was obtained in the training dataset, indicating that our nomogram had good discriminating ability. Results of IDI and NRI in both cohorts proved that our nomogram had positive improvement of predictive performance, compared to other scoring systems. The actual and predicted incidence of mortality showed favorable concordance on calibration curves (P > 0.05). DCA curves revealed that, compared with scoring systems clinically used under common conditions, the constructed nomogram yielded a greater net clinical benefit.

CONCLUSIONS

Utilizing a comprehensive array of fourteen readily accessible variables, a prognostic nomogram was meticulously formulated and rigorously validated to provide precise prognostication of short-term mortality within the ischemic stroke cohort.

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 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.

The Progress of Poststroke Seizures

A stroke is one of the most common fatal diseases of the nervous system, and the number of strokes per year has increased substantially in recent years. Epilepsy is a poststroke complication that greatly affects the prognosis of patients and reduces their quality of survival. Effective avoidance of causative factors can reduce the risk of a poststroke seizure. However, while many studies have been devoted to elucidating the pathogenesis of poststroke seizures, the literature lacks a comprehensive understanding of the pathogenic mechanism. This article briefly presents the current definition, risk factors, pathogenesis, and prognosis of poststroke seizures based on reported studies and literature reviews, aiming to enrich the available knowledge of this disease.

Epileptiform electroencephalogram discharges increase seizure recurrence risk in patients with acute symptomatic seizure due to a structural brain lesion

OBJECTIVE

The risk factors for seizure recurrence after acute symptomatic seizure due to a structural brain lesion are not well established. The aim of this study was to analyze possible associations between demographic, clinical, and electroencephalographic variables and epilepsy development in patients with acute symptomatic seizure due to an acute structural brain lesion.

METHODS

We designed an observational prospective study of patients with acute symptomatic seizure due to an acute structural brain lesion (hemorrhagic stroke, ischemic stroke, traumatic brain injury, or meningoencephalitis) who underwent EEG during their initial admission between January 2015 and January 2020. We analyzed prospectively recorded demographic, clinical, electroencephalographic (EEG), and treatment-related variables. All variables were compared between patients with and without seizure recurrence during 2 years of follow up.

RESULTS

We included 194 patients (41.2 % women; mean [SD] age, 57.3 [15.8] years) with acute symptomatic seizure due to an acute structural brain lesion. They all underwent EEG during admission and were followed for at least 2 years. The identifiable causes were hemorrhagic stroke (44.8 %), ischemic stroke (19.5 %), traumatic brain injury (18.5 %), and meningoencephalitis (17 %). Fifty-six patients (29 %) experienced a second seizure during follow-up. Seizure recurrence was associated with epileptiform discharges on EEG (52% vs 32 %; OR 2.3 [95 % CI, 1.2-4.3], p = 0.008) and onset with status epilepticus (17% vs 0.05 %, OR 4.03 [95 % CI 1.45-11.2], p = 0.009).

CONCLUSIONS

Epileptiform discharges on EEG and status epilepticus in patients with acute symptomatic seizure due to an acute structural brain lesion are associated with a higher risk of epilepsy development.

Factors Associated with Early and Late Seizure Related to Aneurysmal Subarachnoid Hemorrhage

Post-stroke epilepsy may occur after aneurysmal subarachnoid hemorrhage (aSAH). Both early and late seizures could cause severe neurocognitive deficits if administration of appropriate antiseizure medication is delayed. Therefore, it is important to elucidate the risk factors for early and late seizures, which could be shared with medical teams to promptly manage seizures. There are aspects of both hemorrhage and ischemia in aSAH, and thus, numerous risk factors are considered for early and late seizures. We examined factors associated with aSAH-related early and late seizures. Among 297 patients who had aSAH and underwent direct or endovascular surgery, 25 had early seizures and 20 had late seizures. Patients who did not experience any seizures in at least 2-years of follow-up (n = 81) were used as the control group. Early seizures were associated with older age and acute severe nonneurological infection, whereas late seizures were associated with intraparenchymal lesion volume >10 mL and shunt placement. In patients with late seizures, consistency was frequently observed between electroencephalogram and the presence of intraparenchymal lesions. The frontopolar electrode on electroencephalogram was highly sensitive to abnormality in early seizures. Early seizures were induced by the patient's systemic factors, which may lower the threshold for cortical excitability. Patients with intraparenchymal lesions who undergo shunt placement should be carefully followed up for late seizures.

Analyzing the causal relationship between lipid-lowering drug target genes and epilepsy: a Mendelian randomization study

Background

Previous research has yielded conflicting results on the link between epilepsy risk and lipid-lowering medications. The aim of this study is to determine whether the risk of epilepsy outcomes is causally related to lipid-lowering medications predicted by genetics.

Methods

We used genetic instruments as proxies to the exposure of lipid-lowering drugs, employing variants within or near genes targeted by these drugs and associated with low-density lipoprotein cholesterol (LDL cholesterol) from a genome-wide association study. These variants served as controlling factors. Through drug target Mendelian randomization, we systematically assessed the impact of lipid-lowering medications, including HMG-CoA reductase (HMGCR) inhibitors, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, and Niemann-Pick C1-like 1 (NPC1L1) inhibitors, on epilepsy.

Results

The analysis demonstrated that a higher expression of HMGCR was associated with an elevated risk of various types of epilepsy, including all types (OR = 1.17, 95% CI:1.03 to 1.32, p = 0.01), focal epilepsy (OR = 1.24, 95% CI:1.08 to 1.43, p = 0.003), and focal epilepsy documented with lesions other than hippocampal sclerosis (OR = 1.05, 95% CI: 1.01 to 1.10, p = 0.02). The risk of juvenile absence epilepsy (JAE) was also associated with higher expression of PCSK9 (OR = 1.06, 95% CI: 1.02 to 1.09, p = 0.002). For other relationships, there was no reliable supporting data available.

Conclusion

The drug target MR investigation suggests a possible link between reduced epilepsy vulnerability and HMGCR and PCSK9 inhibition.

Epilepsy and epileptiform activity in late-onset Alzheimer disease: clinical and pathophysiological advances, gaps and conundrums

A growing body of evidence has demonstrated a link between Alzheimer disease (AD) and epilepsy. Late-onset epilepsy and epileptiform activity can precede cognitive deterioration in AD by years, and its presence has been shown to predict a faster disease course. In animal models of AD, amyloid and tau pathology are linked to cortical network hyperexcitability that precedes the first signs of memory decline. Thus, detection of epileptiform activity in AD has substantial clinical importance as a potential novel modifiable risk factor for dementia. In this Review, we summarize the epidemiological evidence for the complex bidirectional relationship between AD and epilepsy, examine the effect of epileptiform activity and seizures on cognition in people with AD, and discuss the precision medicine treatment strategies based on the latest research in human and animal models. Finally, we outline some of the unresolved questions of the field that should be addressed by rigorous research, including whether particular clinicopathological subtypes of AD have a stronger association with epilepsy, and the sequence of events between epileptiform activity and amyloid and tau pathology.

Role of the glymphatic system and perivascular spaces as a potential biomarker for post-stroke epilepsy

Stroke is one of the most common causes of acquired epilepsy, which can also result in disability and increased mortality rates particularly in elderly patients. No preventive treatment for post-stroke epilepsy is currently available. Development of such treatments has been greatly limited by the lack of biomarkers to reliably identify high-risk patients. The glymphatic system, including perivascular spaces (PVS), is the brain's waste clearance system, and enlargement or asymmetry of PVS (ePVS) is hypothesized to play a significant role in the pathogenesis of several neurological conditions. In this article, we discuss potential mechanisms for the role of perivascular spaces in the development of post-stroke epilepsy. Using advanced MR-imaging techniques, it has been shown that there is asymmetry and impairment of glymphatic function in the setting of ischemic stroke. Furthermore, studies have described a dysfunction of PVS in patients with different focal and generalized epilepsy syndromes. It is thought that inflammatory processes involving PVS and the blood-brain barrier, impairment of waste clearance, and sustained hypertension affecting the glymphatic system during a seizure may play a crucial role in epileptogenesis post-stroke. We hypothesize that impairment of the glymphatic system and asymmetry and dynamics of ePVS in the course of a stroke contribute to the development of PSE. Automated ePVS detection in stroke patients might thus assist in the identification of high-risk patients for post-stroke epilepsy trials. PLAIN LANGUAGE SUMMARY: Stroke often leads to epilepsy and is one of the main causes of epilepsy in elderly patients, with no preventative treatment available. The brain's waste removal system, called the glymphatic system which consists of perivascular spaces, may be involved. Enlargement or asymmetry of perivascular spaces could play a role in this and can be visualised with advanced brain imaging after a stroke. Detecting enlarged perivascular spaces in stroke patients could help identify those at risk for post-stroke epilepsy.

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.

Large datasets from Electronic Health Records predict seizures after ischemic strokes: A Machine Learning approach

Objective

To develop an artificial intelligence, machine learning prediction model for estimating the risk of seizures 1 year and 5 years after ischemic stroke (IS) using a large dataset from Electronic Health Records.

Background

Seizures are frequent after ischemic strokes and are associated with increased mortality, poor functional outcomes, and lower quality of life. Separating patients at high risk of seizures from those at low risk of seizures is needed for treatment and clinical trial planning, but remains challenging. Machine learning (ML) is a potential approach to solve this paradigm.

Design/Methods

We identified patients (aged ≥18 years) with IS without a prior diagnosis of seizures from 2015 until inception (08/09/22) in the TriNetX Research Network, using the International Classification of Diseases, Tenth Revision (ICD-10) I63, excluding I63.6 (venous infarction). The outcome of interest was any ICD-10 diagnosis of seizures (G40/G41) at 1 year and 5 years following the index IS. We applied a conventional logistic regression and a Light Gradient Boosted Machine algorithm to predict the risk of seizures at 1 year and 5 years. The performance of the model was assessed using the area under the receiver operating characteristics (AUROC), the area under the precision-recall curve (AUPRC), F1 statistic, model accuracy, balanced accuracy, precision, and recall, with and without anti-seizure medication use in the models.

Results

Our study cohort included 430,254 IS patients. Seizures were present in 18,502 (4.3%) and (5.3%) patients within 1 and 5 years after IS, respectively. At 1-year, the AUROC, AUPRC, F1 statistic, accuracy, balanced-accuracy, precision, and recall were respectively 0.7854 (standard error: 0.0038), 0.2426 (0.0048), 0.2299 (0.0034), 0.8236 (0.001), 0.7226 (0.0049), 0.1415 (0.0021), and 0.6122, (0.0095). Corresponding metrics at 5 years were 0.7607 (0.0031), 0.247 (0.0064), 0.2441 (0.0032), 0.8125 (0.0013), 0.7001 (0.0045), 0.155 (0.002) and 0.5745 (0.0095).

Conclusion

Our findings suggest that ML models show good model performance for predicting seizures after IS.

Seizing the Brain Networks in Lesional Focal Epilepsies

Mapping Lesion-Related Epilepsy to a Human Brain Network Frederic L.W. V. J. Schaper, Janne Nordberg, Alexander L. Cohen, Christopher Lin, Joey Hsu, Andreas Horn, Michael A. Ferguson, Shan H. Siddiqi,William Drew, Louis Soussand, Anderson M. Winkler, Marta Simó, Jordi Bruna, Sylvain Rheims, Marc Guenot, Marco Bucci, Lauri Nummenmaa, Julie Staals, Albert J. Colon, Linda Ackermans, Ellen J. Bubrick, Jurriaan M. Peters, OnaWu, Natalia S. Rost, Jordan Grafman, Hal Blumenfeld, Yasin Temel, Rob P. W. Rouhl, Juho Joutsa, Michael D. Fox. JAMA Neurol . 2023;80(9):891-902. doi:10.1001/jamaneurol.2023.1988 . PMID: 37399040. PMCID: PMC10318550 Importance: It remains unclear why lesions in some locations cause epilepsy while others do not. Identifying the brain regions or networks associated with epilepsy by mapping these lesions could inform prognosis and guide interventions. Objective: To assess whether lesion locations associated with epilepsy map to specific brain regions and networks. Design, Setting, and Participants: This case-control study used lesion location and lesion network mapping to identify the brain regions and networks associated with epilepsy in a discovery data set of patients with poststroke epilepsy and control patients with stroke. Patients with stroke lesions and epilepsy (n = 76) or no epilepsy (n = 625) were included. Generalizability to other lesion types was assessed using 4 independent cohorts as validation data sets. The total number of patients across all datasets (both discovery and validation datasets) were 347 with epilepsy and 1126 without. Therapeutic relevance was assessed using deep brain stimulation sites that improve seizure control. Data were analyzed from September 2018 through December 2022. All shared patient data were analyzed and included; no patients were excluded. Main Outcomes and Measures: Epilepsy or no epilepsy. Results: Lesion locations from 76 patients with poststroke epilepsy (39 [51%] male; mean [SD] age, 61.0 [14.6] years; mean [SD] follow-up, 6.7 [2.0] years) and 625 control patients with stroke (366 [59%] male; mean [SD] age, 62.0 [14.1] years; follow-up range, 3-12 months) were included in the discovery data set. Lesions associated with epilepsy occurred in multiple heterogenous locations spanning different lobes and vascular territories. However, these same lesion locations were part of a specific brain network defined by functional connectivity to the basal ganglia and cerebellum. Findings were validated in 4 independent cohorts including 772 patients with brain lesions (271 [35%] with epilepsy; 515 [67%] male; median [IQR] age, 60 [50-70] years; follow-up range, 3-35 years). Lesion connectivity to this brain network was associated with increased risk of epilepsy after stroke (odds ratio [OR], 2.82; 95%CI, 2.02-4.10; P < .001) and across different lesion types (OR, 2.85; 95%CI, 2.23-3.69; P < .001). Deep brain stimulation site connectivity to this same network was associated with improved seizure control (r , 0.63; P < .001) in 30 patients with drug-resistant epilepsy (21 [70%] male; median [IQR] age, 39 [32-46] years; median [IQR] follow-up, 24 [16-30] months). Conclusions and Relevance: The findings in this study indicate that lesion-related epilepsy mapped to a human brain network, which could help identify patients at risk of epilepsy after a brain lesion and guide brain stimulation therapies.

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.

Risk Factors Associated with Epilepsy Related to Cerebrovascular Disease: A Systematic Review and Meta-Analysis

Background and Objective

Stroke is one of the most frequent neurological syndromes in the adult population and the cause of 10% of all diagnosed epilepsies. It is attributed to the origin of up to 50% of them in adults >60 years of age. Although a few risk factors have been described and considered when modeling predictive tools, this aspect is still clinically complex. The objective of this study is to describe and compare predictor scales of post stroke epilepsy (PSE) in adult patients with better performance.

Methods

A systematic review and meta-analysis were performed of studies published between 2010 and 2020 and found in PubMed, Scopus, EMBASE, LILACS, BVS, Google Scholar, and CENTRAL databases. Sixteen studies were included with a total of 298,694 patients with a diagnosis of stroke, 5590 presented late seizures (LS).

Results

Hemorrhage, cortical involvement, and early seizure were the elements most associated with the risk of presenting late seizures. The SeLECT score demonstrated a low risk of bias with a high predictive ability in patients with ischemic stroke (AUC: 0.77 [95% CI: 0.71-0.82]). In patients with hemorrhagic stroke, the CAVE score demonstrated adequate predictive ability (AUC: 0.81 [95% CI: 0.76-0.86]), but an uncertain risk of bias. Research has established risk factors for post ictal epilepsy; however, the numerous ways of assessing data in studies and the difference in their designs make the task of producing a predictive scale that covers the most important risk factors and is reliable for application in the clinical setting, regardless of stroke etiology, very arduous.

Conclusion

Hemorrhage, cortical involvement, and early seizure are associated with an increased risk of post ictal epilepsy. Also, elements such as age, traditional vascular risk factors, and functional assessment failed to reflect statistical significance. Finally, further research is required to refine the available predictive tools.

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.

Post-stroke seizures, epilepsy, and mortality in a prospective hospital-based study

Background and objectives

Post-stroke epilepsy (PSE) is a significant concern in the elderly population, with stroke being a leading cause of epilepsy in this demographic. Several factors have shown consistent associations with the risk of developing PSE, including cortical lesions, initial stroke severity, younger age, and the occurrence of early seizures. The primary objectives of this study were two-fold: (1) to determine the incidence of PSE and (2) to identify the risk factors associated with PSE in a prospective cohort of post-stroke patients.

Methods

A prospective single-hospital study was conducted, involving patients diagnosed with acute ischemic and hemorrhagic stroke. The patients were followed up for 2 years (or until death) from the time of admission. Data about seizure occurrence and recurrent stroke were collected. Kaplan-Meyer curves were used for the assessment of PSE incidence and mortality. Possible predictors of PSE and mortality were selected from between-group analysis and tested in multivariable regressions.

Results

Our study enrolled a total of 424 patients diagnosed with acute stroke. Among them, 97 cases (23%) experienced early post-stroke seizures, and 28 patients (6.6%) developed PSE. The cumulative risks of developing PSE were found to be 15.4% after hemorrhagic stroke and 8.7% after ischemic stroke. In multivariable fine and gray regression with competitive risk of death, significant predictors for developing PSE in the ischemic cohort were watershed infarction (HR 6.01, 95% CI 2.29-15.77, p < 0.001) and low Barthel index at discharge (HR 0.98, CI 0.96-0.99, p = 0.04). Furthermore, patients who eventually developed PSE showed slower recovery and presented a worse neurologic status at the time of discharge. The in-hospital dynamics of the National Institutes of Health Stroke Scale (NIHSS) were significantly worse in the PSE group compared to the non-PSE group (p = 0.01).

Discussion

A higher proportion of cases experienced early seizures compared to what has been commonly reported in similar studies. Watershed stroke and low Barthel index at discharge were both identified as independent risk factors of PSE in ischemic strokes, which sheds light on the underlying mechanisms that may predispose individuals to post-stroke epilepsy after experiencing an ischemic stroke.

Frequency and predictors of poststroke epilepsy after mechanical thrombectomy for large vessel occlusion stroke: results from a multicenter cohort study

BACKGROUND

Poststroke epilepsy (PSE) represents an important complication of stroke. Data regarding the frequency and predictors of PSE in patients with large-vessel occlusion stroke receiving mechanical thrombectomy (MT) are scarce. Furthermore, information on acute and preexisting lesion characteristics on brain MRI has not yet been systematically considered in risk prediction of PSE. This study thus aims to assess PSE risk after acute ischemic stroke treated with MT, based on clinical and MRI features.

METHODS

In this multicenter study from two tertiary stroke centers, we included consecutive acute ischemic stroke patients who had received MT for acute intracranial large vessel occlusion (LVO) between 2011 and 2017, in whom post-interventional brain MRI and long term-follow-up data were available. Infarct size, affected cerebrovascular territory, hemorrhagic complications and chronic cerebrovascular disease features were assessed on MRI (blinded to clinical information). The primary outcome was the occurrence of PSE (> 7 days after stroke onset) assessed by systematic follow-up via phone interview or electronic records.

RESULTS

Our final study cohort comprised 348 thrombectomy patients (median age: 67 years, 45% women) with a median long-term follow-up of 78 months (range 0-125). 32 patients (9%) developed PSE after a median of 477 days (range 9-2577 days). In univariable analyses, larger postinterventional infarct size, infarct location in the parietal, frontal or temporal lobes and cerebral microbleeds were associated with PSE. Multivariable Cox regression analysis confirmed larger infarct size (HR 3.49; 95% CI 1.67-7.30) and presence of cerebral microbleeds (HR 2.56; 95% CI 1.18-5.56) as independent predictors of PSE.

CONCLUSION

In our study, patients with large vessel occlusion stroke receiving MT had a 9% prevalence of PSE over a median follow-up period of 6.5 years. Besides larger infarct size, presence of cerebral microbleeds on brain MRI predicted PSE occurrence.

Predictors of unprovoked seizures in intracerebral hemorrhages

BACKGROUND

Seizures are a common complication of intracerebral hemorrhage (ICH). We aimed to identify predictors of unprovoked seizures (US) after ICH in a Chinese cohort.

METHODS

We retrospectively included patients with ICH admitted in the Second Hospital of Hebei Medical University between November 2018 and December 2020. Incidence and risk factors of US were identified with univariate and then multiple Cox regression analysis. We used χ2 test to compare incidence of US between groups with or without prophylactic anti-seizure medications (ASM) in patients with craniotomy.

RESULTS

A total of 488 patients were included in the cohort, 58 (11.9%) patients developed US within 3 years after ICH. Analysis on the 362 patients without prophylactic ASM showed that craniotomy (HR 8.35, 95% CI 3.80-18.31) and acute symptomatic seizures (ASS) (HR 13.76, 95% CI 3.56-53.17) are independent predictors of US. No significant effect of prophylactic ASM use was found on incidence of US in ICH patients with craniotomy (P = 0.369).

CONCLUSIONS

Craniotomy and acute symptomatic seizures were independent predictors for unprovoked seizures after ICH, suggesting that more attention should be paid for such patients during follow-up. Whether prophylactic ASM treatment benefits ICH patients underwent craniotomy remains uncertain.

Clinical characteristics and outcomes of patients with post-stroke epilepsy: protocol for an individual patient data meta-analysis from the International Post-stroke Epilepsy Research Repository (IPSERR)

INTRODUCTION

Despite significant advances in managing acute stroke and reducing stroke mortality, preventing complications like post-stroke epilepsy (PSE) has seen limited progress. PSE research has been scattered worldwide with varying methodologies and data reporting. To address this, we established the International Post-stroke Epilepsy Research Consortium (IPSERC) to integrate global PSE research efforts. This protocol outlines an individual patient data meta-analysis (IPD-MA) to determine outcomes in patients with post-stroke seizures (PSS) and develop/validate PSE prediction models, comparing them with existing models. This protocol informs about creating the International Post-stroke Epilepsy Research Repository (IPSERR) to support future collaborative research.

METHODS AND ANALYSIS

We utilised a comprehensive search strategy and searched MEDLINE, Embase, PsycInfo, Cochrane, and Web of Science databases until 30 January 2023. We extracted observational studies of stroke patients aged ≥18 years, presenting early or late PSS with data on patient outcome measures, and conducted the risk of bias assessment. We did not apply any restriction based on the date or language of publication. We will invite these study authors and the IPSERC collaborators to contribute IPD to IPSERR. We will review the IPD lodged within IPSERR to identify patients who developed epileptic seizures and those who did not. We will merge the IPD files of individual data and standardise the variables where possible for consistency. We will conduct an IPD-MA to estimate the prognostic value of clinical characteristics in predicting PSE.

ETHICS AND DISSEMINATION

Ethics approval is not required for this study. The results will be published in peer-reviewed journals. This study will contribute to IPSERR, which will be available to researchers for future PSE research projects. It will also serve as a platform to anchor future clinical trials.

TRIAL REGISTRATION NUMBER

NCT06108102.

Incidence and risk factors of post-stroke seizures and epilepsy: systematic review and meta-analysis

OBJECTIVE

Due to variability in reports, the aim of this meta-analysis was to evaluate the incidence and risk factors of post-stroke early seizures (ES) and post-stroke epilepsy (PSE).

METHODS

The MEDLINE, EMBASE and Web of Science databases were searched for post-stroke ES/PSE articles published on any date up to November 2020. Post-stroke ES included seizures occurring within 7 days of stroke, and PSE included at least one unprovoked seizure. Using random effects models, the incidence and risk factors of post-stroke ES and PSE were evaluated. The study was retrospectively registered with INPLASY (INPLASY2023100008).

RESULTS

Of 128 included studies in total, the incidence of post-stroke ES was 0.07 (95% confidence interval [CI] 0.05, 0.10) and PSE was 0.10 (95% CI 0.08, 0.13). The rates were higher in children than adults. Risk factors for post-stroke ES included hemorrhagic stroke (odds ratio [OR] 2.14, 95% CI 1.44, 3.18), severe strokes (OR 2.68, 95% CI 1.73, 4.14), cortical involvement (OR 3.09, 95% CI 2.11, 4.51) and hemorrhagic transformation (OR 2.70, 95% CI 1.58, 4.60). Risk factors for PSE included severe strokes (OR 4.92, 95% CI 3.43, 7.06), cortical involvement (OR 3.20, 95% CI 2.13, 4.81), anterior circulation infarcts (OR 3.28, 95% CI 1.34, 8.03), hemorrhagic transformation (OR 2.81, 95% CI 1.25, 6.30) and post-stroke ES (OR 7.24, 95% CI 3.73, 14.06).

CONCLUSION

Understanding the risk factors of post-stroke ES/PSE may identify high-risk individuals who might benefit from prophylactic treatment.

Post-stroke Everything

PURPOSE OF REVIEW

This review aims at providing updates on selected post-stroke complications. We examined recent advances in diagnosing and treating the following post-stroke complications: cognitive impairment, epilepsy, depression, fatigue, tremors, dysphagia, and pain.

RECENT FINDINGS

Advances in understanding the mechanisms of post-stroke complications, in general, are needed despite advances made in understanding, treating, and preventing these complications. There are growing progresses in integrating new tools to diagnose post-stroke cognitive impairment. The potential role of acute stroke reperfusion treatment in post-stroke epilepsy and its impact on other stroke complications is getting more transparent. Post-stroke depression remains underestimated and new tools to diagnose depression after stroke are being developed. New promising pharmacological approaches to treating post-stroke pain are emerging. Tremors related to stroke are poorly understood and under-evaluated, while treatment towards post-stroke dysphagia has benefited from new non-pharmacological to pharmacological approaches.

CONCLUSIONS

An integrative approach to stroke complications and collaborations between providers across specialties are more likely to improve stroke outcomes.

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.

Outcomes in Patients With Poststroke Seizures: A Systematic Review and Meta-Analysis

Importance

Published data about the impact of poststroke seizures (PSSs) on the outcomes of patients with stroke are inconsistent and have not been systematically evaluated, to the authors' knowledge.

Objective

To investigate outcomes in people with PSS compared with people without PSS.

Data Sources

MEDLINE, Embase, PsycInfo, Cochrane, LILACS, LIPECS, and Web of Science, with years searched from 1951 to January 30, 2023.

Study Selection

Observational studies that reported PSS outcomes.

Data Extraction and Synthesis

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was used for abstracting data, and the Joanna Briggs Institute tool was used for risk-of-bias assessment. Data were reported as odds ratio (OR) and standardized mean difference (SMD) with a 95% CI using a random-effects meta-analysis. Publication bias was assessed using funnel plots and the Egger test. Outlier and meta-regression analyses were performed to explore the source of heterogeneity. Data were analyzed from November 2022 to January 2023.

Main Outcomes and Measures

Measured outcomes were mortality, poor functional outcome (modified Rankin scale [mRS] score 3-6), disability (mean mRS score), recurrent stroke, and dementia at patient follow-up.

Results

The search yielded 71 eligible articles, including 20 110 patients with PSS and 1 166 085 patients without PSS. Of the participants with PSS, 1967 (9.8%) had early seizures, and 10 605 (52.7%) had late seizures. The risk of bias was high in 5 studies (7.0%), moderate in 35 (49.3%), and low in 31 (43.7%). PSSs were associated with mortality risk (OR, 2.1; 95% CI, 1.8-2.4), poor functional outcome (OR, 2.2; 95% CI, 1.8-2.8), greater disability (SMD, 0.6; 95% CI, 0.4-0.7), and increased dementia risk (OR, 3.1; 95% CI, 1.3-7.7) compared with patients without PSS. In subgroup analyses, early seizures but not late seizures were associated with mortality (OR, 2.4; 95% CI, 1.9-2.9 vs OR, 1.2; 95% CI, 0.8-2.0) and both ischemic and hemorrhagic stroke subtypes were associated with mortality (OR, 2.2; 95% CI, 1.8-2.7 vs OR, 1.4; 95% CI, 1.0-1.8). In addition, early and late seizures (OR, 2.4; 95% CI, 1.6-3.4 vs OR, 2.7; 95% CI, 1.8-4.1) and stroke subtypes were associated with poor outcomes (OR, 2.6; 95% CI, 1.9-3.7 vs OR, 1.9; 95% CI, 1.0-3.6).

Conclusions and Relevance

Results of this systematic review and meta-analysis suggest that PSSs were associated with significantly increased mortality and severe disability in patients with history of stroke. Unraveling these associations is a high clinical and research priority. Trials of interventions to prevent seizures may be warranted.

Development and validation of a nomogram for predicting deep venous thrombosis in patients with pelvic and acetabular fractures: a retrospective cohort study : Predictive model for pelvic/acetabular fractures

PURPOSE

To construct a novel nomogram model that can predict DVT and avoid unnecessary examination.

METHODS

Patients admitted to the hospital with pelvis/acetabular fractures were included between July 2014 and July 2018. The potential predictors associated with DVT were analyzed using Univariate and multivariable logistic regression analysis. The predictive nomogram was constructed and internally validated.

RESULTS

230 patients were finally enrolled. There were 149 individuals in the non-DVT group and 81 in the DVT group. Following analysis, we obtained the final nomogram model. The risk factors included age (OR, 1.037; 95% CI, 1.013-1.062; P = 0.002), body mass index (BMI) (OR, 1.253; 95% CI, 1.120-1.403; P < 0.001); instant application of anticoagulant after admission (IAA) (OR, 2.734; 95% CI, 0.847-8.829; P = 0.093), hemoglobin (HGB) (OR, 0.970; 95% CI, 0.954-0.986; P < 0.001), D-Dimer(OR, 1.154; 95% CI, 1.016-1.310; P = 0.027) and fibrinogen (FIB) (OR, 1.286; 95% CI, 1.024-1.616; P = 0.002). The apparent C-statistic was 0.811, and the adjusted C-statistic was 0.777 after internal validations, demonstrating good discrimination. Hosmer and Lemeshow's goodness of fit (GOF) test of the predictive model showed a good calibration for the probability of prediction and observation (χ2 = 3.285, P = 0.915; P > 0.05). The decision curve analysis (DCA) and Clinical impact plot (CIC) demonstrated superior clinical use of the nomogram.

CONCLUSIONS

An easy-to-calculate nomogram model for predicting DVT in patients with pelvic-acetabular fractures were developed. It could help clinicians to reduce DVT and avoid unnecessary examinations.