In-hospital costs in patients with seizures and epilepsy after stroke

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.

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.

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.

External validation and comparison of clinical scores for predicting late seizures after intracerebral hemorrhage in Chinese patients

PURPOSE

Clinical scores have been established to predict the probability of late seizures following intracerebral hemorrhage (ICH) for individual patients, including the CAVE, CAVS and LANE scores. The purpose of this study was to compare these prediction scores in the Chinese population and undertake an independent external validation on them.

METHODS

At one tertiary hospital in China, we retrospectively recruited consecutive inpatients who had been diagnosed with ICH. Medical records and tele interviews with a modified standardized questionnaire were used to identify late seizures. All the predictors of the prediction scores were collected from patient charts and databases by a standardized data collection protocol. The external validation of the prediction scores was quantified by the area under the curve (AUC), sensitivity, specificity, Youden index (YI), positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

69 (5.4%) of 1276 patients experienced late seizures after ICH. There was no significant difference in the CAVE, CAVS, and LANE scores, which had AUCs of 0.75 (95% CI = 0.70-0.81), 0.74 (95% CI = 0.68-0.80), and 0.76 (95% CI = 0.70-0.82), respectively. At the optimal cutoff score, the LANE score had a lower sensitivity but a higher specificity than the CAVE and CAVS scores. Among the three prediction scores, the LANE score had a higher PPV than the others (0.145 vs. 0.088, 0.083), while the NPV was similar among the three prediction scores (0.989, 0.989, and 0.972).

CONCLUSION

Our study showed that the CAVE, CAVS and LANE scores had similar AUCs for the occurrence of late seizures, but the LANE score had a relatively high PPV at the optimal cutoff score. Due to low evidence for using prophylactic antiseizure medications (ASM) in patients with ICH and poor availability of specialist stroke care in China, the LANE score with a cutoff score of 3 could be an applicable prediction tool in Chinese patients with ICH.

Determinants of quality of life in Nigerian female patients with epilepsy on carbamazepine and levetiracetam monotherapy

Background

The study is aimed to identify the predictors of Quality of Life (QOL) in women with epilepsy (WWE) on carbamazepine (CBM) and levetiracetam (LTM) monotherapy. 100 WWE were recruited (50 each on CBM and LTM), after clinical diagnosis of epilepsy supported by Electroencephalography (EEG) features and seizures classification by 2017 International League Against Epilepsy (ILAE) criteria, the Quality of Life Inventory Scale 31(QOLIE-31) and Zung Self-Rating Depression Scale (ZSRDS) were used to assess QOL and depression, respectively.

Result

Higher QOLIE-31 scores was seen in the LTM group across all domains except seizure worry (p = 0.051) compared to CBM group. Logistic regression showed that the use of CBM (p = 0.000), fast frequency on EEG (p = 0.005), longer duration of epilepsy (p = 0.017), presence of depression (p = 0.008) and lower level of education (p = 0.003) were predictors of QOL. Progesterone (p = 0.040), oestradiol (p = 0.011) and prolactin (p = 0.002) in follicular phase showed significant association with QOLIE-total score. In the luteal phase, luteinizing hormone–follicle stimulating hormone (LH–FSH) ratio (p = 0.009) and testosterone (p = 0.015), FSH (p = 0.015), prolactin (p = 0.000), showed significant association with QOL. None of the hormones independently predicts QOL.

Conclusion

LTM group appears to have better QOL than CBM group. Healthcare providers should focus on addressing these identified predictors which include medication effect, depression, Level of education, EEG background and duration of epilepsy with aim of improving QOL.

Specificity and sensitivity of the SeLECT score in predicting late seizures in patients undergoing intravenous thrombolytic treatment and the effect of diabetes mellitus and leukoaraiosis

BACKGROUND

 Seizures after stroke can negatively affect the prognosis of ischemic stroke and cause a decrease in quality of life. The efficacy of intravenous (IV) recombinant tissue plasminogen activator (rt-PA) treatment in acute ischemic stroke has been demonstrated in many studies, and IV rt-PA treatment has been increasingly used around the world. The SeLECT score is a useful score for the prediction of late seizures after stroke and includes the severity of stroke (Se), large artery atherosclerosis (L), early seizure (E), cortical involvement (C), and the territory of the middle cerebral artery (T). However, the specificity and sensitivity of the SeLECT score have not been studied in acute ischemic stroke patients that received IV rt-PA treatment.

OBJECTIVE

 In the present study, we aimed to validate and develop the SeLECT score in acute ischemic stroke patients receiving IV rt-PA treatment.

METHODS

 The present study included 157 patients who received IV thrombolytic treatment in our third-stage hospital. The 1-year seizure rates of the patients were detected. SeLECT scores were calculated.

RESULTS

 In our study, we found that the SeLECT score had low sensitivity but high specificity for predicting the likelihood of late seizure after stroke in patients administered IV rt-PA therapy. In addition to the SeLECT score, we found that the specificity and sensitivity were higher when we evaluated diabetes mellitus (DM) and leukoaraiosis.

CONCLUSION

 We found that DM was an independent risk factor for late seizures after stroke in a patient group receiving thrombolytic therapy, and late seizures after stroke were less frequent in patients with leukoaraiosis.

Development and validation of a novel radiomics-clinical model for predicting post-stroke epilepsy after first-ever intracerebral haemorrhage

OBJECTIVES

Post-stroke epilepsy (PSE) is associated with increased morbidity and mortality. This study aimed to develop and validate a novel prediction model combining clinical factors and radiomics features to accurately identify patients at high risk of developing PSE after intracerebral haemorrhage (ICH).

METHODS

Researchers performed a retrospective medical chart review to extract derivation and validation cohorts of patients with first-ever ICH that attended two tertiary hospitals in China between 2010 and 2020. Clinical data were extracted from electronic medical records and supplemented by tele-interview. Predictive clinical variables were selected by multivariable logistic regression to build the clinical model. Predictive radiomics features were identified, and a Rad-score was calculated according to the coefficient of the selected feature. Both clinical variables and radiomic features were combined to build the radiomics-clinical model. Performances of the clinical, Rad-score, and combined models were compared.

RESULTS

A total of 1571 patients were included in the analysis. Cortical involvement, early seizures within 7 days of ICH, NIHSS score, and ICH volume were included in the clinical model. Rad-score, instead of ICH volume, was included in the combined model. The combined model exhibited better discrimination ability and achieved an overall better benefit against threshold probability than the clinical model in the decision curve analysis (DCA).

CONCLUSIONS

The combined radiomics-clinical model was better able to predict ICH-associated PSE compared to the clinical model. This can help clinicians better predict an individual patient's risk of PSE following a first-ever ICH and facilitate earlier PSE diagnosis and treatment.

KEY POINTS

• Radiomics has not been used in predicting the risk of developing PSE. • Higher Rad-scores were associated with higher risk of developing PSE. • The combined model showed better performance of PSE prediction ability.

Not always that EASI: Validating the Russian version of the epilepsy anxiety survey instrument and its brief counterpart

OBJECTIVE

To develop a Russian version of The Epilepsy Anxiety Survey Instrument (EASI) and assess its psychometric properties in a Russian sample of patients with epilepsy (PWE). To compare the brief version of EASI with the General Anxiety Disorder-7 (GAD-7) - the most common tool for a rapid anxiety screening.

METHODS

The study sample consisted of 181 consecutive Russian-speaking PWE. The Mini-International Neuropsychiatric Interview was used as a gold standard for diagnosing anxiety disorders. All patients completed the set of questionnaires - the Russian version of the GAD-7, The Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), and the EASI. Internal reliability of the EASI and brEASI, convergent and divergent validity of the brEASI with the GAD-7 and the NDDI-E, and factor structure assessment were performed.

RESULTS

Among 33.7% of patients with epilepsy diagnosed with any anxiety disorder, 16% had panic disorder, 10.5% had agoraphobia, 8.3% had social anxiety disorder, 21.0% had generalized anxiety disorder, and 13.3% had several comorbid anxiety disorders. The EASI factor structure differed from the original, revealing an additional factor with two items. Nevertheless, the brief version (brEASI) showed excellent screening properties - the AUC to detect any anxiety disorder was 0.916 with the optimal cutoff point > 7 points.

CONCLUSION

The brEASI performed better than the GAD-7 in our sample and, therefore, may be considered a first-line screening tool for anxiety disorders in PWE.

Non-convulsive seizures in the encephalopathic critically ill cancer patient does not necessarily portend a poor prognosis

Background

Non-convulsive status epilepticus (NCSE) is present in 10–30% of ICU patients with altered mental status (AMS) and is associated to poor outcomes. To our knowledge, there is no data describing the prevalence and outcomes of critically ill cancer patients with AMS associated to non-convulsive seizures (NCS) or NCSE. We aim to describe the outcomes and risk factors of critically ill cancer patients with encephalopathy associated with non-convulsive seizures (NCS).

Methods

This is a 3-year prospective observational study in a mixed oncological ICU at MD Anderson Cancer Center. Data of ICU patients with moderate to severe encephalopathy (Glasgow Coma Score < 13) that underwent EEG monitoring to rule out NCS were collected. Multivariate logistic regression was performed to identify risk factors and outcomes.

Results

Of the 317 patients with encephalopathy who underwent EEG monitoring, 14.5% had NCS. Known risk factors such as sepsis, CNS infection, antibiotics, and cardiac arrest were not associated with increased risk of NCS. Patients with NCS were more likely to have received recent chemotherapy (41.3% vs 21.4%; p = 0.0036), have a CNS disease (39% vs 24.4%; p = 0.035), and abnormal brain imaging (60.9% vs 44.6%; p = 0.041). Patients with lower SOFA scores, normal renal function, and absence of shock were likely to have NCS as the cause of their encephalopathy (p < 0.03). After multivariate analysis, only abnormal brain imaging and absence of renal failure were associated with NCS. Mortality was significantly lower in patients with non-convulsive seizures when compared to those without seizures (45.7% vs 64%; p = 0.022); however, there was no significant association of seizures and mortality on a multivariable logistic regression analysis.

Conclusions

NCS in critically ill cancer patients is associated with abnormalities on brain imaging and lower prevalence of organ failure. Diagnosis and treatment of NCS should be a priority in encephalopathic cancer patients, as they can have lower mortality than non-seizing patients. Opposite to other populations, NCS should not be considered a poor prognostic factor in critically ill encephalopathic cancer patients as they reflect a reversible cause for altered mentation.

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

BACKGROUND

Stroke is one of the leading causes of acquired epilepsy in adults. An instrument to predict whether people are at high risk of developing post-stroke seizures is not available. We aimed to develop and validate a prognostic model of late (>7 days) seizures after ischaemic stroke.

METHODS

In this multivariable prediction model development and validation study, we developed the SeLECT score based on five clinical predictors in 1200 participants who had an ischaemic stroke in Switzerland using backward elimination of a multivariable Cox proportional hazards model. We externally validated this score in 1169 participants from three independent international cohorts in Austria, Germany, and Italy, and assessed its performance with the concordance statistic and calibration plots.

FINDINGS

Data were complete for 99·2% of the predictors (99·2% for Switzerland, 100% for Austria, 97% for Germany, and 99·7% for Italy) and 100% of the outcome parameters. Overall, the risk of late seizures was 4% (95% CI 4-5) 1 year after stroke and 8% (6-9) 5 years after stroke. The final model included five variables and was named SeLECT on the basis of the first letters of the included parameters (severity of stroke, large-artery atherosclerotic aetiology, early seizures, cortical involvement, and territory of middle cerebral artery involvement). The lowest SeLECT value (0 points) was associated with a 0·7% (95% CI 0·4-1·0) risk of late seizures within 1 year after stroke (1·3% [95% CI 0·7-1·8] within 5 years), whereas the highest value (9 points) predicted a 63% (42-77) risk of late seizures within 1 year (83% [62-93] within 5 years). The model had an overall concordance statistic of 0·77 (95% CI 0·71-0·82) in the validation cohorts. Calibration plots indicated high agreement of predicted and observed outcomes.

INTERPRETATION

This easily applied instrument was shown to be a good predictor of the risk of late seizures after stroke in three external validation cohorts and is freely available as a smartphone app. The SeLECT score has the potential to identify individuals at high risk of seizures and is a step towards more personalised medicine. It can inform the selection of an enriched population for antiepileptogenic treatment trials and will guide the recruitment for biomarker studies of epileptogenesis.

FUNDING

None.