Development and validation of risk score to estimate 1-year late poststroke epilepsy risk in ischemic stroke patients

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.

Post-stroke epilepsy: From clinical predictors to possible mechanisms

BACKGROUND

Stroke is the most common cause of newly diagnosed epilepsy in the elderly, ahead of degenerative disorders, brain tumors, and head trauma. Stroke accounts for 30-50% of unprovoked seizures in patients aged ≥ 60 years. This review discusses the current understanding of epidemiology, risk factors, mechanisms, prevention, and treatment opportunities for post-stroke epilepsy (PSE).

METHODS

We performed a literature search in the PubMed and Cochrane Library databases. The keywords "stroke, epilepsy", "stroke, seizure", "post-stroke seizure", "post-stroke epilepsy" were used to identify the clinical and experimental articles on PSE. All resulting titles and abstracts were evaluated, and any relevant article was considered. The reference lists of all selected papers and reference lists of selected review papers were manually analyzed to find other potentially eligible articles.

RESULTS

PSE occurs in about 6% of stroke patients within several years after the event. The main risk factors are cortical lesion, initial stroke severity, young age and seizures in acute stroke period (early seizures, ES). Other risk factors, such as a cardioembolic mechanism or circulation territory involvement, remain debated. The role of ES as a risk factor of PSE could be underestimated especially in young age. Mechanism of epileptogenesis may involve gliosis scarring, alteration in synaptic plasticity, etc.; and ES may enhance these processes. Statins especially in the acute period of stroke are possible agents for PSE prevention presumably due to their anticonvulsant and neuroprotection effects. Antiepileptic drugs (AED) monotherapy is enough for seizure prevention in most cases of PSE; but no evidence was found for its efficiency against epileptic foci formation. The growing interest in PSE has led to a notable increase in the number of published articles each year. To aid in navigating this expanding body of literature, several tables are included in the manuscript.

CONCLUSION

Further studies are needed for better understanding of the pathophysiology of PSE and searching the prevention strategies.

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.

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.

The Primary Prevention of Poststroke Epilepsy in Patients With Middle Cerebral Artery Infarct: Protocol for a Randomized Controlled Trial

BACKGROUND

Poststroke epilepsy poses a significant clinical challenge for individuals recovering from strokes, leading to a less favorable long-term outlook and increased mortality rates. Existing studies have primarily concentrated on administering antiseizure or anticonvulsant treatments only after the onset of late-onset seizures, without intervening during the epileptogenesis phase following a stroke.

OBJECTIVE

This research protocol is designed to conduct a randomized controlled trial to assess whether the early, preventive introduction of low-dose antiepileptic drug therapy (levetiracetam [LEV] or perampanel [PER]) in patients who have experienced middle cerebral artery (MCA) infarction can reduce the risk of developing poststroke epilepsy (primary prevention).

METHODS

Participants with MCA infarction, either with or without reperfusion treatments, will be recruited and promptly receive preventive intervention within 72 hours of the stroke occurrence. These participants will be randomly assigned to receive either PER (4 mg per day), LEV (1000 mg per day), or a placebo that matches the active drugs. This treatment will continue for 12 weeks after allocation. Brain magnetic resonance imaging will be used to confirm the presence of MCA territory infarction, and an electroencephalography will be used to ensure the absence of epileptiform discharges or electrographic seizures at the time of the stroke. All participants will undergo follow-up assessments for 72 weeks after allocation.

RESULTS

The primary outcome under evaluation will be the incidence of poststroke epilepsy in the 3 groups following the 18-month study period. Secondary outcomes will encompass the time to the occurrence of the first seizure, the severity of seizures, any treatment-related adverse events, and the modified Rankin scale score at 3 and 18 months. Exploratory outcomes will involve comparing the effectiveness and safety of PER and LEV.

CONCLUSIONS

We anticipate that the intervention groups will experience a lower incidence and reduced severity of poststroke epilepsy compared to the control group after 18 months. We aim to establish evidence supporting the potential preventive effects of LEV and PER on poststroke seizures and epilepsy in patients with MCA infarction, as well as to explore the antiepileptogenic potential of both LEV and PER in patients with major ischemic strokes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04858841; https://clinicaltrials.gov/study/NCT04858841.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/49412.

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.

Application of Machine Learning Methods for Epilepsy Risk Ranking in Patients with Hematopoietic Malignancies Using

Machine learning methods to predict the risk of epilepsy, including vascular epilepsy, in oncohematological patients are currently considered promising. These methods are used in research to predict pharmacoresistant epilepsy and surgical treatment outcomes in order to determine the epileptogenic zone and functional neural systems in patients with epilepsy, as well as to develop new approaches to classification and perform other tasks. This paper presents the results of applying machine learning to analyzing data and developing diagnostic models of epilepsy in oncohematological and cardiovascular patients. This study contributes to solving the problem of often unjustified diagnosis of primary epilepsy in patients with oncohematological or cardiovascular pathology, prescribing antiseizure drugs to patients with single seizure syndromes without finding a disease associated with these cases. We analyzed the hospital database of the V.A. Almazov Scientific Research Center of the Ministry of Health of Russia. The study included 66,723 treatment episodes of patients with vascular diseases (I10–I15, I61–I69, I20–I25) and 16,383 episodes with malignant neoplasms of lymphoid, hematopoietic, and related tissues (C81–C96 according to ICD-10) for the period from 2010 to 2020. Data analysis and model calculations indicate that the best result was shown by gradient boosting with mean accuracy cross-validation score = 0.96. f1-score = 98, weighted avg precision = 93, recall = 96, f1-score = 94. The highest correlation coefficient for G40 and different clinical conditions was achieved with fibrillation, hypertension, stenosis or occlusion of the precerebral arteries (0.16), cerebral sinus thrombosis (0.089), arterial hypertension (0.17), age (0.03), non-traumatic intracranial hemorrhage (0.07), atrial fibrillation (0.05), delta absolute neutrophil count (0.05), platelet count at discharge (0.04), transfusion volume for stem cell transplantation (0.023). From the clinical point of view, the identified differences in the importance of predictors in a broader patient model are consistent with a practical algorithm for organic brain damage. Atrial fibrillation is one of the leading factors in the development of both ischemic and hemorrhagic strokes. At the same time, brain infarction can be accompanied both by the development of epileptic seizures in the acute period and by unprovoked epileptic seizures and development of epilepsy in the early recovery and in a longer period. In addition, a microembolism of the left heart chambers can lead to multiple microfocal lesions of the brain, which is one of the pathogenetic aspects of epilepsy in elderly patients. The presence of precordial fibrillation requires anticoagulant therapy, the use of which increases the risk of both spontaneous and traumatic intracranial hemorrhage.

Strategic infarct location for post-stroke seizure

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The hot spots of PSS were distributed around the central region of cerebral cortex.

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We observed differences between the distribution of hot spots among patients with early-PSS and those with late-PSS.

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The specific regions of the brain are significantly associated with the development of PSS after cerebral infarction.

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The location of infarction could help clinicians assess the risk of PSS in specific post-stroke stages.

Post-stroke seizure (PSS) can have a strong negative impact on functional recovery after stroke. Researchers have identified numerous risk factors of PSS; however, the relationship between infarction location and PSS remains unclear. We recruited patients who presented with an acute cerebral infarction between 2012 and 2017 and suffered from seizures within 1 year after stroke (PSS group). PSS group was subgrouped into early-PSS and late-PSS groups based on the interval between seizure and stroke. We also recruited an equal number of acute cerebral infarction patients without post-stroke seizures during the follow-up period (Non-PSS group). All brain MRIs from the two groups were processed, whereupon normalized infarct maps from the PSS and Non-PSS groups were compared via voxel- and volumetric-based analyses. A total of 132 subjects were enrolled in the study, including PSS (n = 66, consisting of 31 early-PSS and 35 late-PSS) and Non-PSS (n = 66) patients. No significant differences were observed between the two groups in terms of stroke lateralization or severity. Image analysis revealed that the volume of infarction was larger in the PSS group than in the Non-PSS group; however, the difference did not reach the level of significance. Unlike the Non-PSS group, the PSS group presented hot spots over the left central region, left superior parietal lobule, and right frontal operculum. We observed differences between the distribution of hot spots among patients with early-PSS and those with late-PSS. We found that some brain regions were significantly associated with the development of PSS after ischemic stroke, and these regions differed between cases of early and late PSS. It appears that the location of infarction could help clinicians assess the risk of PSS in specific post-stroke stages.

Risk of Incident Epilepsy After a Middle Cerebral Artery Territory Infarction

Background

Among poststroke morbidities, poststroke epilepsy (PSE) has been identified as a significant clinical issue. Although middle cerebral artery (MCA) infarct is the most common type of stroke among all vascular territories, very few studies specifically focused on the risk factors leading to PSE in patients with MCA infarct.

Methods

A population study in Taiwan has been conducted, linking the National Health Insurance Research Database and Hospital Stroke Registry, from 2001 to 2015 and 2006 to 2010, respectively. Patients were divided into MCA and non-MCA groups, and the diagnosis of incident epilepsy between the groups has been compared. The multivariable Cox proportional hazard model was used to identify the risk factors for developing PSE. The distribution of time to PSE was estimated using the Kaplan–Meier method.

Results

In total, 1,838 patients were recruited, with 774 and 1,064 in the MCA and non-MCA groups, respectively. PSE incidence in the MCA group was 15.5% vs. 6.2% in the non-MCA group, with a hazard ratio of (95% CI) 2.06 (1.33–3.19). Factors significantly associated with PSE included atrial fibrillation, depression, National Institutes of Health Stroke Scale (NIHSS) scores of ≥ 16, and alert on arrival. For patients with MCA infarct, higher NIHSS and Glasgow coma scale scores, the presence of visual field defects and weakness, urination control impairment, and complications during hospitalization were associated with a higher risk for PSE development.

Conclusions

This study established the conditions leading to a higher risk of PSE and identified the important clinical risk factors in patients experiencing MCA infarct. Efforts to manage these risk factors may be important in preventing PSE in patients with MCA infarct.

Asymmetric distribution of enlarged perivascular spaces in centrum semiovale may be associated with epilepsy after acute ischemic stroke

Objective

To investigate the factors influencing enlarged perivascular space (EPVS) characteristics at the onset of acute ischemic stroke (AIS), and whether the PVS characteristics can predict later post‐stroke epilepsy (PSE).

Methods

A total of 312 patients with AIS were identified, of whom 58/312 (18.6%) developed PSE. Twenty healthy participants were included as the control group. The number of PVS in the basal ganglia (BG), centrum semiovale (CS), and midbrain (MB) was manually calculated on T₂‐weighted MRI. The scores and asymmetry index (AI) of EPVS in each region were compared among the enrolled participants. Other potential risk factors for PSE were also analyzed, including NIHSS at admission and stroke etiologies.

Results

The EPVS scores were significantly higher in the bilateral BG and CS of AIS patients compared to those of the control group (both p < 0.01). No statistical differences in EPVS scores in BG, CS, and MB were obtained between the PSE group and the nonepilepsy AIS group (all p > 0.01). However, markedly different AI scores in CS were found between the PSE group and the nonepilepsy AIS group (p = 0.004). Multivariable analysis showed that high asymmetry index of EPVS (AI≥0.2) in CS was an independent predictor for PSE (OR = 3.7, 95% confidence interval 1.5–9.1, p = 0.004).

Conclusions

Asymmetric distribution of EPVS in CS may be an independent risk factor and a novel imaging biomarker for the development of PSE. Further studies to understand the mechanisms of this association and confirmation with larger patient populations are warranted.

Hospital Revisits for Post-Ischemic Stroke Epilepsy after Acute Stroke Interventions

OBJECTIVES

Improvements in acute stroke care have led to an increase in ischemic stroke survivors, who are at risk for development of post-ischemic stroke epilepsy (PISE). The impact of therapies such as thrombectomy and thrombolysis on risk of hospital revisits for PISE is unclear. We utilized administrative data to investigate the association between stroke treatment and PISE-related visits.

MATERIALS AND METHODS

Using claims data from California, New York, and Florida, we performed a retrospective analysis of adult survivors of acute ischemic strokes. Patients with history of epilepsy, trauma, infections, or tumors were excluded. Included patients were followed for a primary outcome of revisits for seizures or epilepsy. Cox proportional hazards regression was used to identify covariates associated with PISE.

RESULTS

In 595,545 included patients (median age 74 [IQR 21], 52% female), the 6-year cumulative rate of PISE-related revisit was 2.20% (95% CI 2.16-2.24). In multivariable models adjusting for demographics, comorbidities, and indicators of stroke severity, IV-tPA (HR 1.42, 95% CI 1.31-1.54, p<0.001) but not MT (HR 1.62, 95% CI 0.90-1.50, p=0.2) was associated with PISE-related revisit. Patients who underwent decompressive craniectomy experienced a 2-fold increase in odds for returning with PISE (HR 2.35, 95% CI 1.69-3.26, p<0.001). In-hospital seizures (HR 4.06, 95% CI 3.76-4.39, p<0.001) also elevated risk for PISE.

SIGNIFICANCE

We demonstrate that ischemic stroke survivors who received IV-tPA, underwent decompressive craniectomy, or experienced acute seizures were at increased risk PISE-related revisit. Close attention should be paid to these patients with increased potential for long-term development of and re-hospitalization for PISE.

Development and validation of a claims-based model to identify patients at risk of chronic thromboembolic pulmonary hypertension following acute pulmonary embolism

OBJECTIVE

Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare disease that often follows pulmonary embolism (PE). Screening for CTEPH is challenging, often delaying diagnosis and worsening prognosis. Predictive risk models for CTEPH could help identify at-risk patients, but existing models require multiple clinical inputs. We developed and validated a predictive risk model for CTEPH using health insurance claims that can be used by payers/quality-of-care organizations to screen patients post-PE.

METHODS

Adult patients newly diagnosed with acute PE (index date) were identified from the Optum De-identified Clinformatics Extended DataMart (January 2007-March 2018; development set) and IBM MarketScan (January 2008-June 2019; validation set) databases. Predictors were identified 12 months before or on the index PE. Risk of "likely CTEPH" was assessed post-PE based on CTEPH-related diagnoses and procedures since the CTEPH diagnosis code (ICD-10-CM: I27.24) was not available until 1 October 2017. Stepwise variable selection was used to build the model using the development set; model validation was subsequently conducted using the validation set.

RESULTS

The development set included 93,428 patients, of whom 11,878 (12.7%) developed likely CTEPH. Older age (odds ratios [OR] = 1.16-1.49), female (OR = 1.09), unprovoked PE (i.e. without thrombotic factors; OR = 1.14), hypertension (OR = 1.07), osteoarthritis (OR = 1.08), diabetes (OR = 1.07), chronic obstructive pulmonary disease (OR = 1.11), obesity (OR = 1.21) were associated with higher odds of likely CTEPH, and oral anticoagulants with lower odds (OR= 0.50, all p < .01). C-statistic was 0.77 in the development and validation sets.

CONCLUSION

A claims-based risk model reliably predicted the risk of CTEPH post-PE and could be used to identify high-risk patients who may benefit from focused monitoring.

Risk models to predict late-onset seizures after stroke: A systematic review

BACKGROUND AND PURPOSE

We performed a systematic review to evaluate available risk models to predict late seizure onset among stroke survivors.

METHODS

We searched major databases (PubMed, SCOPUS, and Cochrane Library) from inception to October 2020 for articles on the development and/or validation of risk models to predict late seizures after a stroke. The impact of models to predict late-onset seizures was also assessed. We included seven articles in the final analysis. For each of these studies, we evaluated the study design and scope of predictors analyzed to derive each model. We assessed the performance of the models during internal and external validation in terms of discrimination and calibration.

RESULTS

Three studies focused on ischemic stroke alone, with c-statistic values ranging from 0.73 to 0.77. The SeLECT model from Switzerland was externally validated in Italian, German, and Austrian cohorts where c-statistics ranged from 0.69 to 0.81. This model along with the PSEiCARe model, were internally validated and calibration performance was provided for both models. The CAVS and CAVE models reported on the risk of late-onset seizures in patients with hemorrhagic stroke. The CAVS model derivation cohort was racially diverse. The CAVS model's c-statistic was 0.76, while the CAVE model had a c-statistic of 0.81. Calibration and internal validation were not performed for either study. The CAVS model, created from a Finnish population, was externally validated in American and French cohorts, with c-statistics of 0.73 and 0.69, respectively. Finally, the two studies focusing on both types of stroke came from the PoSERS and INPOSE models. Neither model provided c-statistics, calibration metrics, internal or external validation information. We found no evidence of the presence of impact studies to assess the effect of adopting late-onset seizure risk models after stroke on clinical outcomes.

CONCLUSION

The SeLECT model was the only model developed in line with proposed guidelines for appropriate model development. The model, which was externally validated in a very similar and homogeneous population, may need to be tested in a more racially/ethnic diverse and younger population; testing the SeLECT model, accounting for overall brain health is likely to improve the identification of high-risk patients for late post stroke seizures.

Development and validation of a clinical score to predict late seizures after intracerebral hemorrhage in Chinese

BACKGROUND

Seizures are a frequent complication after intracerebral hemorrhage (ICH). The CAVE score was developed in Europeans to predict late seizures after ICH. Given the higher incidence of ICH in Asians, we aimed to develop and validate a clinical scoring tool for predicting post-ICH late seizures in Chinese.

METHODS

We retrospectively included patients admitted with ICH to a major stroke center in Shandong province, China, in the derivation cohort, who were followed up for occurrence of late seizures (more than seven days after ICH). We applied Cox regression model to identify significant clinical factors which were used to derive a predictive scoring model. The performance of this model was compared with CAVE, and validated in a separate cohort of patients with ICH admitted to another stroke center.

RESULTS

In the derivation cohort (n = 602; median age 65 years; 57 % male；median follow up 24 months), 47 (7.8 %) patients had late seizures during follow up. Four significant risk factors were identified and selected to derive the LANE score (Lobar hemorrhage, Age <65 years, NIHSS score ≥15, Early seizures). The total possible points ranged from 0 to 6, corresponding to positive predictive values of 10.1%-100%, and negative predictive values of 96.8%-92.2%, respectively. The c-statistics of the LANE score in the derivation cohort and validation cohort (n = 521) were 0.83 and 0.78, respectively, while those of the CAVE score were 0.81 and 0.74, respectively.

CONCLUSION

We have developed and validated a clinical scoring tool for predicting late seizures after ICH in Chinese. This tool may be used to identify high risk patients for closer monitoring and clinical trials of therapies to prevent post-ICH epilepsy in the future.

Subsequent Development of Epithelial Ovarian Cancer After Ovarian Surgery for Benign Ovarian Tumor: A Population-Based Cohort Study

Purpose

The goal of the current study is to determine the risk of subsequent development of epithelial ovarian cancer (EOC) in women after ovarian surgery for benign ovarian tumors.

Patients and Methods

We conducted the nationwide population-based historic cohort study using the National Health Insurance Research Database (NHIRD) of Taiwan. Eleven thousand six hundred twenty women who underwent ovarian surgery for ovarian benign diseases were analyzed. The collected data included age, types of ovarian surgery, medical history by Charlson comorbidity index (CCI), infertility (yes/no), pelvic inflammatory disease (PID) (yes/no), tubal ligation (yes/no), total/subtotal hysterectomy (TH/STH) (yes/no), and endometrioma (yes/no). We used the Kaplan-Meier method and the Log-rank test to evaluate the risk factors. Cox proportional hazard methods were used to evaluate risk factors for the subsequent development of EOC. Multivariate analysis using Cox stepwise forward regression was conducted for the covariate selected in univariate analysis. Hazard ratio (HR) and 95% confidence interval (CI) were calculated using the Wald test.

Results

Subsequent EOC incidence rate (IR, incidence per 10,000 person-years) of women after ovarian surgery for benign ovarian tumors was 2.98. Separating into four groups based on different age, IR of EOC was 1.57 (<30 years), 4.71 (30-39 years), 3.59 (40-49 years) and 0.94 (≥50 years), respectively. Univariate and multivariate analyses identified only high level of CCI (≥2 or more) as an independent risk factor for subsequent development of EOC in women after ovarian surgery for benign ovarian tumors (HR 59.17, 95% CI 7.50-466.80 in women with CCI level of 2 and HR 190.68, 95% CI 24.33-2494.19, in women with CCI level ≥3, respectively).

Conclusion

Our results, if confirmed, suggest that women with other comorbidities (CCI) should be well informed that they may have a higher risk of subsequent development of EOC when ovarian surgery is planned even though the final pathology showed a benign ovarian tumor.

Development and validation of prediction scores for nosocomial infections, reoperations, and adverse events in the daily clinical setting of neurosurgical patients with cerebral and spinal tumors

OBJECTIVE

Various quality indicators are currently under investigation, aiming at measuring the quality of care in neurosurgery; however, the discipline currently lacks practical scoring systems for accurately assessing risk. The aim of this study was to develop three accurate, easy-to-use risk scoring systems for nosocomial infections, reoperations, and adverse events for patients with cerebral and spinal tumors.

METHODS

The authors developed a semiautomatic registry with administrative and clinical data and included all patients with spinal or cerebral tumors treated between September 2017 and May 2019. Patients were further divided into development and validation cohorts. Multivariable logistic regression models were used to develop risk scores by assigning points based on β coefficients, and internal validation of the scores was performed.

RESULTS

In total, 1000 patients were included. An unplanned 30-day reoperation was observed in 6.8% of patients. Nosocomial infections were documented in 7.4% of cases and any adverse event in 14.5%. The risk scores comprise variables such as emergency admission, nursing care level, ECOG performance status, and inflammatory markers on admission. Three scoring systems, NoInfECT for predicting the incidence of nosocomial infections (low risk, 1.8%; intermediate risk, 8.1%; and high risk, 26.0% [p < 0.001]), LEUCut for 30-day unplanned reoperations (low risk, 2.2%; intermediate risk, 6.8%; and high risk, 13.5% [p < 0.001]), and LINC for any adverse events (low risk, 7.6%; intermediate risk, 15.7%; and high risk, 49.5% [p < 0.001]), showed satisfactory discrimination between the different outcome groups in receiver operating characteristic curve analysis (AUC ≥ 0.7).

CONCLUSIONS

The proposed risk scores allow efficient prediction of the likelihood of adverse events, to compare quality of care between different providers, and further provide guidance to surgeons on how to allocate preoperative care.

Risk factors for seizures after intracerebral hemorrhage: Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) Study

OBJECTIVE

We aimed to identify risk factors for seizures after intracerebral hemorrhage, and to validate the prognostic value of the previously reported CAVE score (0-4 points: cortical involvement, age <65, volume >10 mL, and early seizures within 7 days of hemorrhage).

PATIENTS AND METHODS

Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) was a prospective study of spontaneous intracerebral hemorrhage. We included patients who did not have a prior history of seizure and survived to discharge. Univariate analysis and multiple logistic regression modeling were used to identify risk factors for seizure.

RESULTS

From 2010-2015, 3000 cases were recruited, and 2507 patients were included in this study. Seizures after hospital discharge developed in 77 patients 3.1 %). Patients with lobar (cortical) hemorrhage (OR 3.0, 95 % CI 1.8-5.0), larger hematoma volume (OR 1.5 per cm³, 95 % CI 1.2-2.0), and surgical evacuation of hematoma (OR 2.6, 95 % CI 1.4-4.8) had a higher risk of late seizure, and older patients had a lower risk (OR 0.88 per 5-year interval increase, 95 % CI 0.81-0.95). The CAVE score was highly associated with seizure development (OR 2.5 per unit score increase, 95 % CI 2.0-3.2, p < 0.0001). The CAVS score, substituting surgical evacuation for early seizure, increased the OR per unit score to 2.8 (95 % CI 2.2-3.5).

CONCLUSIONS

Lobar hemorrhage, larger hematoma volume, younger age, and surgical evacuation are strongly associated with the development of seizures. We validated the CAVE score in a multi-ethnic population, and found the CAVS score to have similar predictive value while representing the current practice of AED use.