Prevalence and predictors of post-stroke epilepsy among Ghanaian stroke survivors

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.

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.

Risk Factors for Post-Stroke Seizures in a Tertiary Care Center: A Case-Control Study

Purpose

Stroke is the second leading cause of global deaths. Post-stroke seizures (PSS) can lead to lasting complications, such as prolonged hospitalizations, increased disability rates, and higher mortality. Our study investigates the associated factors that contribute to post-stroke seizures in patients at a local tertiary hospital.

Patients and Methods

We designed a case-control study where patients admitted with PSS were recruited with consent. Controls admitted for stroke without seizure were then included. Suitability based on exclusion criteria was ensured before recording their sociodemographic and clinical data. An EEG was performed and read by two certified neurologists before the data was analyzed.

Results

We recruited 180 participants, 90 cases and 90 matched controls. Gender (p=0.013), race (p=0.015), dyslipidemia (p<0.001), prior stroke (p<0.031), large artery atherosclerosis (p<0.001), small vessel occlusions (p<0.001), blood pressure on presentation (p<0.028) and thrombolysis administration (p<0.029) were significantly associated with the occurrence of PSS. An increase in odds of PSS was observed in the male gender (1.974), dyslipidemia (3.480), small vessel occlusions (4.578), and in participants with epileptiform changes on EEG (3.630). Conversely, lower odds of PSS were seen in participants with high blood pressure on presentation (0.505), large artery atherosclerosis (0.266), and those who underwent thrombolysis (0.319).

Conclusion

This study emphasized that identifying post-stroke seizures may be aided by EEGs and recognizing at-risk groups, which include males of Chinese descent in Asia, dyslipidemia, small vessel occlusions, those with low to normal blood pressure on presentation, and epileptiform changes in EEGs.

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.

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.

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.

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.

The epidemiology of epilepsy in older adults: A narrative review by the ILAE Task Force on Epilepsy in the Elderly

In an aging world, it is important to know the burden of epilepsy affecting populations of older persons. We performed a selective review of epidemiological studies that we considered to be most informative, trying to include data from all parts of the world. We emphasized primary reports rather than review articles. We reviewed studies reporting the incidence and prevalence of epilepsy that focused on an older population as well as studies that included a wider age range if older persons were tabulated as a subgroup. There is strong evidence that persons older than approximately 60 years incur an increasing risk of both acute symptomatic seizures and epilepsy. In wealthier countries, the incidence of epilepsy increases sharply after age 60 or 65 years. This phenomenon was not always observed among reports from populations with lower socioeconomic status. This discrepancy may reflect differences in etiologies, methods of ascertainment, or distribution of ages; this is an area for more research. We identified other areas for which there are inadequate data. Incidence data are scarcer than prevalence data and are missing for large areas of the world. Prevalence is lower than would be expected from cumulative incidence, possibly because of remissions, excess mortality, or misdiagnosis of acute symptomatic seizures as epilepsy. Segmentation by age, frailty, and comorbidities is desirable, because "epilepsy in the elderly" is otherwise too broad a concept. Data are needed on rates of status epilepticus and drug-resistant epilepsy using the newer definitions. Many more data are needed from low-income populations and from developing countries. Greater awareness of the high rates of seizures among older adults should lead to more focused diagnostic efforts for individuals. Accurate data on epilepsy among older adults should drive proper allocation of treatments for individuals and resources for societies.

Status of epilepsy in the tropics: An overlooked perspective

Epilepsy is one of the most common serious chronic neurological diseases affecting people of all ages globally. It is characterized by recurrent seizures. About 50 million people worldwide have epilepsy. Indubitably, people with epilepsy (PWE) may be without access to appropriate treatment. Many studies have examined the molecular mechanisms and clinical aspects of epilepsy; nonetheless, the treatment gap exists in some special areas. In the tropics, the specific geographical and ecological conditions and a lack of medical resources result in neglect or delay of diagnosis for PWE. Herein, we summarized the epidemiology of epilepsy in the tropics and discussed the disease burden and existing problems, aiming to offer a medical environment for patients in need and highlight the importance of reducing the epileptic disease burden in tropical countries.

Incidence and predictors of post stroke seizure among adult stroke patients admitted at Felege Hiwot compressive specialized hospital, Bahir Dar, North West Ethiopia, 2021: a retrospective follow up study

BACKGROUND

A post stroke seizure is a period of neurological dysfunction caused by abnormal neuronal activity. Seizures after a stroke have an impact on patients' lives and increase mortality in stroke patients. It also has a negative impact on the prognosis of stroke. However, there is a scarcity of literature in Ethiopia on the occurrence of post-stroke seizures. Therefore, this study aimed to assess the incidence and predictors of post-stroke seizure at Felege Hiwot compressive specialized hospital, North West Ethiopia.

METHODS

An institution-based retrospective follow-up study was carried out at Felege Hiwot Compressive Specialized Hospital, North West Ethiopia from July 1, 2017 to June 30, 2021. The records of 568 stroke patients were reviewed using a random sample method. To find predictors of post-stroke seizures, we applied the log-binomial regression model.

RESULT

The incidence of post-stroke seizures was 22.18%( 95% CI 18.83%-25.83%). Older age group (ARR = 2.49, 95% CI 1.33-4.69), hemorrhagic stroke (ARR = 1.99, 95% CI 1.25-3.17), surgical intervention (ARR = 1.85, 95% CI 1.22-2.81), and tramadol medication (ARR = 1.85, 95% CI 1.22-2.81) were found to be predictors of post stroke seizure.

CONCLUSION

This study revealed that the incidence of post stroke seizure was high and older age, haemorrhagic type of stroke, surgical management, and use of tramadol anti-pain medication are risk factors for post-stroke seizures. Therefore, health care professionals must pay special attention and provide clinical care to patients who have risk factors for post-stroke seizure.

Poststroke Seizure and Epilepsy: A Review of Incidence, Risk Factors, Diagnosis, Pathophysiology, and Pharmacological Therapies

Stroke is the most common cause of epilepsy and ultimately leads to a decrease in the quality of life of those affected. Ischemic and hemorrhagic strokes can both lead to poststroke epilepsy (PSE). Significant risk factors for PSE include age < 65age less than 65 years, stroke severity measured by the National Institutes of Health Stroke Scale (NIHSS), cortical involvement, and genetic factors such as TRPM6 polymorphism. The diagnosis of PSE is made by using imaging modalities, blood biomarkers, and prognostic criteria. Electroencephalography (EEG) is currently the gold standard to diagnose PSE, while new combinations of modalities are being tested to increase diagnostic specificity. This literature review uncovers a newly found mechanism for the pathology of poststroke epilepsy. The pathogenesis of early-onset and late-onset is characterized by sequelae of neuronal cellular hypoxia and disruption of the blood-brain barrier, respectively. Interleukin-6 is responsible for increasing the activity of glial cells, causing gliosis and hyperexcitability of neurons. Epinephrine, high-mobility group protein B1, downregulation of CD32, and upregulation of HLA-DR impact the pathology of poststroke epilepsy by inhibiting the normal neuronal immune response. Decreased levels of neuropeptide Y, a neurotransmitter, act through multiple unique mechanisms, such as inhibiting intracellular Ca²⁺ accumulation and acting as an anti-inflammatory, also implemented in the worsening progression of poststroke epilepsy. Additionally, CA1 hippocampal resonant neurons that increase theta oscillation are associated with poststroke epilepsy. Hypertensive small vessel disease may also have an implication in the temporal lobe epilepsy by causing occult microinfarctions. Furthermore, this review highlights the potential use of statins as primary prophylaxis against PSE, with multiple studies demonstrating a reduction in incidence using statins alone, statins in combination with antiepileptic drugs (AEDs), and statins with aspirin. The evidence strongly suggests that the second generation AEDs are a superior treatment method for PSE. Data from numerous studies demonstrate their relative lack of significant drug interactions, increased tolerability, and potential superiority in maintaining seizure-free status.

Long-term determinants of death after stroke in Ghana: Analysis by stroke types & subtypes

BACKGROUND

Determinants of long-term mortality after stroke by mechanistic type and subtype are unknown in sub-Saharan Africa (SSA). Such data are crucial for targeting specific pathophysiologic pathways to improve stroke outcomes in the region.

PURPOSE

To evaluate rates and predictors of mortality up to 8 years after stroke, by type and subtype, in Ghana.

METHODS

We prospectively collected data on stroke patients presenting at a tertiary medical facility in Ghana between 2013 and 2018 who were followed up until October 31, 2021. Stroke diagnosis was confirmed using a Computerized Tomography scan; ischemic strokes were mechanistically typed using the TOAST classification while intracerebral hemorrhages were subtyped using the SMASH-U scheme. Demographic and clinical predictors of stroke mortality were evaluated using Cox proportional hazards regression modelling.

RESULTS

Of 564 patients encountered during the study period, data on vital status were available for 556 (98.6%) subjects at discharge and 442 (78.4%) on follow-up. Mean age was 61.1 ±15.1 years, and 223 (53.1%) were male. Mortality rates at 1, 3, 12, 36, 60 and 96 months were 37.5%, 43.2%, 49.7%, 57.4%, 62.9%, and 73.7% respectively. Three (3) factors remained significantly associated with risk of death namely age, adjusted hazard ratios (aHR) of 1.12 (95%CI: 1.04-1.20), no formal education 1.36 (95% CI: 1.02-1.81) and modified Rankin score 1.67 (95%CI: 1.42 - 1.98) for each unit rise. For ischemic stroke the four (4) factors associated with long-term mortality were low formal education, low monthly income, having diabetes mellitus and higher functional score on admission. For intracerebral hemorrhage, the two factors were increasing age and high functional score.

CONCLUSION

Stroke severity is the key predictor of long-term mortality after an index stroke in Ghana, regardless of the underlying pathophysiologic mechanism. Instituting acute stroke systems of care to facilitate timely reperfusion efforts may greatly improve long term survival outcomes after stroke in SSA.

Clinical Characteristics and Gene Mutation Analysis of Poststroke Epilepsy

Epilepsy is one of the most common brain disorders worldwide. Poststroke epilepsy (PSE) affects functional retrieval after stroke and brings considerable social values. A stroke occurs when the blood circulation to the brain fails, causing speech difficulties, memory loss, and paralysis. An electroencephalogram (EEG) is a tool that may detect anomalies in brain electrical activity, including those induced by a stroke. Using EEG data to determine the electrical action in the brains of stroke patients is an effort to measure therapy. Hence in this paper, deep learning assisted gene mutation analysis (DL-GMA) was utilized for classifying poststroke epilepsy in patients. This study suggested a model categorizing poststroke patients based on EEG signals that utilized wavelet, long short-term memory (LSTM), and convolutional neural networks (CNN). Gene mutation analysis can help determine the cause of an individual's epilepsy, leading to an accurate diagnosis and the best probable medical management. The test outcomes show the viability of noninvasive approaches that quickly evaluate brain waves to monitor and detect daily stroke diseases. The simulation outcomes demonstrate that the proposed GL-GMA achieves a high accuracy ratio of 98.3%, a prediction ratio of 97.8%, a precision ratio of 96.5%, and a recall ratio of 95.6% and decreases the error rate 10.3% compared to other existing methods.

Risk Factors for Postischemic Stroke Epilepsy in Young Adults: A Nationwide Population-Based Study in Taiwan

Background

The incidence of ischemic stroke has been increasing in the young population over the past 20 years. Poststroke epilepsy (PSE) is a common complication after stroke. However, few population-based studies with sufficient follow-up have investigated factors associated with PSE, especially factors related to comorbidities and unhealthy lifestyles in the modern young population. Accordingly, this study aimed to determine the long-term incidence and these risk factors for PSE young adults.

Methods

This cohort study was conducted using data from the Taiwan National Health Insurance Research Database (NHIRD) from 2002 to 2018. All patients aged between 19 and 44 years and diagnosed with ischemic stroke from 2002 to 2015 were retrospectively enrolled with a follow-up of at least 3 years. Multivariable Cox regression models were performed to identify predictors of PSE, including patients' demographics, baseline conditions, stroke severity, etiologies, comorbidities, and unhealthy behaviors.

Results

Among 6,512 ischemic stroke patients, 402 cases (6.2%) developed PSE who were with a mean follow-up period of 8.3 years (SD = 4.3 years). During the overall follow-up, stroke severity and manifestations were associated with PSE, including National Institutes of Health Stroke Scale (NIHSS) score ≥10 (aHR, 1.98; 95% CI, 1.50–2.61), seizure at first stroke admission [adjusted hazard ratio (aHR), 57.39; 95% confidence interval (CI), 43.02–76.55], length of hospital stay ≥14 days (aHR, 1.60; 95% CI, 1.26–2.02), recurrent stroke (aHR, 2.32; 95% CI, 1.85–2.90), aphasia (aHR, 1.77; 95% CI, 1.20–2.60), and malignancy (aHR, 2.05; 95% CI, 1.30–3.24). Furthermore, stroke patients with drug abuse were 2.90 times more likely to develop PSE than those without (aHR, 2.90; 95% CI, 1.53–5.50). By contrast, statin use (aHR, 0.62; 95% CI, 0.48–0.80) was associated with a lower risk of PSE. The risk factors at 1-year and 5-year PSE were similar to that of an overall follow-up.

Conclusions

Stroke severity, aphasia, malignancy, and drug abuse were associated increased risk of PSE and statin use may protect against PSE in young adults. Reducing the severity of stroke, statin use and controlling unhealthy behaviors might be able to decrease the development of PSE. Since PSE is associated with poor outcomes, early identification or intervention of PSE based on the risk factors might reduce the harmful effects of PSE.

Prescription patterns and dosages of antiepileptic drugs in prevalent patients with epilepsy in Taiwan: A nationwide retrospective cross-sectional study

OBJECTIVE

To evaluate the prescription patterns and prescribed daily dose (PDD)/defined daily dose (DDD) ratios of antiepileptic drugs (AEDs) in prevalent patients with epilepsy in Taiwan.

MATERIALS AND METHODS

A nationwide retrospective cross-sectional study was conducted for prevalent patients with epilepsy in 2016 using the Taiwanese National Health Insurance Research Database. The prescription records of AEDs of all prevalent patients with epilepsy were retrieved. The mean PDDs and PDD/DDD ratios of AEDs in adult patients were obtained to evaluate dosing adequacy. A chi-square test and two-sample t test were used to analyze the differences in AED prescription patterns and dosages, respectively, among patients with different ages, sexes, comorbidities, and therapeutic approaches.

RESULTS

A total of 118,937 prevalent patients with epilepsy were enrolled. The predominant therapeutic approach was monotherapy, especially in the elder adults, accounting for 82.9% of elder adult patients with epilepsy. The proportion of AED monotherapy was higher in patients with dementia (78.9%) and stroke (80.6%). The top three antiepileptic monotherapies were valproic acid (28.7%), levetiracetam (19.1%), and phenytoin (16.9%); however, oxcarbazepine (22.8%) was substituted for carbamazepine (3.9%) as monotherapy for patients aged 0-17 years. Among adult patients with epilepsy, the PDD/DDD ratio of each AED in monotherapy was less than 1.00. The mean PDD of each AED was higher in polytherapy than in monotherapy (p < 0.01), except for lacosamide. The mean PDDs of all evaluated AEDs in monotherapy were lower in elder adult patients than in younger adult patients, most of which reached statistical significance (p < 0.001).

CONCLUSIONS

In Taiwan, valproic acid was the most prescribed AED for prevalent patients with epilepsy. The mean PDDs of most AEDs were lower than the DDDs developed by the World Health Organization.

Impact of drug treatment and drug interactions in post-stroke epilepsy

Stroke is a huge burden on our society and this is expected to grow in the future due to the aging population and the associated co-morbidities. The improvement of acute stroke care has increased the survival rate of stroke patients, and many patients are left with permanent disability, which makes stroke the main cause of adult disability. Unfortunately, many patients face other severe complications such as post-stroke seizures and epilepsy. Acute seizures (ASS) occur within 1 week after the stroke while later occurring unprovoked seizures are diagnosed as post-stroke epilepsy (PSE). Both are associated with a poor prognosis of a functional recovery. The underlying neurobiological mechanisms are complex and poorly understood. There are no universal guidelines on the management of PSE. There is increasing evidence for several risk factors for ASS/PSE, however, the impacts of recanalization, drugs used for secondary prevention of stroke, treatment of stroke co-morbidities and antiseizure medication are currently poorly understood. This review focuses on the common medications that stroke patients are prescribed and potential drug interactions possibly complicating the management of ASS/PSE.

Frequency and factors associated with post-stroke seizures in a large multicenter study in West Africa

BACKGROUND

Post-stroke seizures (PSS) are associated with significant morbidity and mortality across the globe. There is a paucity of data on PSS in Africa.

PURPOSE

To assess the frequency and factors associated with PSS by stroke types across 15 hospitals in Nigeria and Ghana.

METHODS

We analyzed data on all stroke cases recruited into the Stroke Investigative Research and Educational Network (SIREN). We included adults aged ≥18 years with radiologically confirmed ischemic stroke (IS) or intracerebral hemorrhage (ICH). PSS were defined as acute symptomatic seizures occurring at stroke onset and/or during acute hospitalization up until discharge. We used logistic regression to estimate adjusted odds ratios (aOR) with 95% Confidence Interval.

RESULTS

Among 3344 stroke patients, 499 (14.9%) had PSS (95% CI: 13.7-16.2%). The mean duration of admission in days for those with PSS vs no PSS was 17.4 ± 28.6 vs 15.9 ± 24.7, p = 0.72. There were 294(14.1%) PSS among 2091 ischemic strokes and 159(17.7%) among 897 with ICH, p = 0.01. The factors associated with PSS occurrence were age < 50 years, aOR of 1.59 (1.08-2.33), National Institute of Health Stroke Score (NIHSS), 1.29 (1.16-1.42) for each 5 units rise and white cell count 1.07 (1.01-1.13) for each 10^3 mm3 rise. Factors associated with PSS in ischemic were NIHSS score, aOR of 1.17 (1.04-1.31) and infarct volume of 10-30 cm3 aOR of 2.17(1.37-3.45). Among ICH, associated factors were alcohol use 5.91 (2.11-16.55) and lobar bleeds 2.22 (1.03-4.82).

CONCLUSION

The burden of PSS among this sample of west Africans is substantial and may contribute to poor outcomes of stroke in this region. Further longitudinal studies are required to understand the impact on morbidity and mortality arising from PSS in Africa.

Neurological disorders encountered at an out-patient clinic in Ghana's largest medical center: A 16-year review

Background

With a rising age of its population, sub-Saharan Africa(SSA) is currently experiencing an unprecedented rise in burden of neurological disorders. There is limited data on the demographic profile of neurological diseases in SSA.

Objective

To describe the spectrum of neurological disorders at the adult neurology clinic at Ghana's leading medical center.

Methods

This retrospective study was conducted at the adult neurology clinic at the Korle Bu Teaching Hospital between 2003 and 2019. We retrospectively reviewed charts of all cases seen at the clinic over the period to document main neurological diagnosis, and captured age and sex of participants. Neurologic diseases were classified using the revised International Statistical Classification of Diseases and Related Health Problems ICD 11 tool.

Results

There were 7950 patients sought consultation over the period with 7076 having a primary neurological disorder. The mean age ± SD of patients included in the analysis was 43.0 ± 19.8 years with 3777 (53.4%) being males. The frequencies of the top 5 neurological disorders were epilepsy (23.0%), peripheral neuropathies (19.6%), movement disorders (14.7%), cerebrovascular diseases (11.1%) and headache disorders (7.7%). Neurocognitive disorders, autoimmune demyelinating disorders of the nervous system, and motor neuron disorders were infrequently observed.

Conclusion

A wide spectrum of neurological disorders were encountered in this clinic, similar to previous report from other centers in SSA. There is an urgent need to build local capacity to provide optimal care to meet the demand of the rising burden of neurological diseases in Ghana.

Stroke in Africa: profile, progress, prospects and priorities

Stroke is a leading cause of disability, dementia and death worldwide. Approximately 70% of deaths from stroke and 87% of stroke-related disability occur in low-income and middle-income countries. At the turn of the century, the most common diseases in Africa were communicable diseases, whereas non-communicable diseases, including stroke, were considered rare, particularly in sub-Saharan Africa. However, evidence indicates that, today, Africa could have up to 2-3-fold greater rates of stroke incidence and higher stroke prevalence than western Europe and the USA. In Africa, data published within the past decade show that stroke has an annual incidence rate of up to 316 per 100,000, a prevalence of up to 1,460 per 100,000 and a 3-year fatality rate greater than 80%. Moreover, many Africans have a stroke within the fourth to sixth decades of life, with serious implications for the individual, their family and society. This age profile is particularly important as strokes in younger people tend to result in a greater loss of self-worth and socioeconomic productivity than in older individuals. Emerging insights from research into stroke epidemiology, genetics, prevention, care and outcomes offer great prospects for tackling the growing burden of stroke on the continent. In this article, we review the unique profile of stroke in Africa and summarize current knowledge on stroke epidemiology, genetics, prevention, acute care, rehabilitation, outcomes, cost of care and awareness. We also discuss knowledge gaps, emerging priorities and future directions of stroke medicine for the more than 1 billion people who live in Africa.