Mortality in Patients With Late-Onset Epilepsy: Results From the Atherosclerosis Risk in Communities Study

Late-onset epilepsy clinic: From clinical diagnostics to biomarkers

The unique patho-clinical entity of late-onset epilepsy (LOE), distinguished by its distinct natural history, from its onset to the prognosis it portends, necessitates specialized care. We lack a universally accepted definition, but LOE is typically identified as epilepsy onset after the age of 60 or 65. Unlike epilepsy in younger individuals, LOE is almost by default focal in origin, secondary to acquired etiologies, and presents unique diagnostic and management challenges due to its atypical semiology, higher comorbidity burden, frailty, and increased risks of subsequent stroke and dementia. LOE clinics have been established to address these challenges, providing a multidisciplinary approach to optimize outcomes in patients with new-onset seizures beyond the fifth decade of life. LOE clinics are essential for comprehensive care, offering not only seizure management but also monitoring and addressing associated comorbidities. The care model involves collaboration among neurologists, primary care providers, cardiologists, mental health professionals, and social workers to manage LOE patients' complex needs effectively. The prevalence of cognitive dysfunction in LOE patients underscores the need for regular cognitive assessments and interventions. Biomarker research, particularly involving amyloid beta, offers promising avenues for early diagnosis and a better understanding of the interplay between LOE and Alzheimer's disease. Establishing LOE clinics in major referral centers can enhance provider expertise, improve patient outcomes, and facilitate research to advance diagnostic and therapeutic strategies. In conclusion, LOE clinics play a critical role in addressing the multifaceted needs of older adults with epilepsy, tailored to local resources and challenges, thus enhancing epilepsy care in an aging global population.

Diagnosing epileptic seizures in patients with Alzheimer's disease and deciding on the appropriate treatment plan

INTRODUCTION

Alzheimer's disease (AD) is the predominant cause of dementia and a significant contributor to morbidity among the elderly. Patients diagnosed with AD face an increased risk of epileptic seizures.

AREAS COVERED

Herein, the authors review the challenges in the diagnosis of seizures in patients with AD, the risks of seizures related to medications used in AD and the pharmacological treatment of seizures in AD. The authors also provide the reader with their expert opinion on the subject matter and future perspectives.

EXPERT OPINION

Healthcare professionals should maintain a vigilant approach to suspecting seizures in AD patients. Acute symptomatic seizures triggered by metabolic disturbances, infections, toxins, or drug-related factors often have a low risk of recurrence. In such cases, addressing the underlying cause may suffice without initiating antiseizure medications (ASMs). However, unprovoked seizures in certain AD patients carry a higher risk of recurrence over time, warranting the use of ASMs. Although data is limited, both lamotrigine and levetiracetam appear to be reasonable choices for controlling seizures in elderly AD patients. Decisions should be informed by the best available evidence, the treating physician's clinical experience, and the patient's preferences.

Bidirectional relationship between late-onset epilepsy (LOE) and dementia: A systematic review and meta-analysis of cohort studies

OBJECTIVE

To explore the bidirectional relationship of late-onset epilepsy (LOE) with dementia and Alzheimer's disease (AD).

METHODS

Using the common electronic databases, including PubMed, Cochrane Library databases and EMBASE, we systematically reviewed published cohort studies that assessed the risk of LOE in individuals comorbid with dementia or AD, and those with dementia or AD comorbid with LOE that had been published up to 31 March 2023. The data extraction process was carried out independently by two authors. The summary adjusted relative ratio (aRR) was calculated by employing Rev Man 5.3 for the inclusion of studies. To investigate the origins of heterogeneity, we conducted both subgroup and sensitivity analyses. In the presence of heterogeneity, a random-effects model was employed. To evaluate potential publication bias, we utilized the funnel plot and conducted Begg's and Egger's tests.

RESULTS

We included 20 eligible studies in the final analysis after a rigorous screening process. Pooled results indicated that LOE was association with an increased risk of all-cause dementia (aRR: 1.34, 95% confidence interval [CI]: 1.13-1.59) and AD (aRR: 2.49, 95% CI: 1.16-5.32). In addition, the pooled effect size for LOE associated with baseline AD and all-cause dementia were 3.51 (95% CI: 3.47-3.56) and 2.53 (95% CI: 2.39-2.67), respectively. Both sensitivity and subgroup analyses showed that these positive correlations persisted. According to the results of the Egger's and Begg's tests, as well as visual inspection of funnel plots, none of the studies appeared to be biased by publication.

CONCLUSION

The findings suggested that LOE is a potential risk factor for dementia and AD, and vice versa, dementia and AD are both potential risk indicators for LOE. Since there is substantial heterogeneity among the cohorts analyzed and more cohort studies should be conducted to confirm the correlations found in the current study.

The crosstalk between epilepsy and dementia: A systematic review and meta-analysis

BACKGROUND

Epilepsy and dementia are bidirectional. The purpose of this review was to investigate the epidemiological characteristics of and to identify the risk factors for epilepsy in patients with dementia and dementia in patients with epilepsy.

METHODS

We retrieved the PubMed, Embase, Cochrane and Web of Science databases through January 2023. Two individuals screened the articles, extracted the data, and used a random effects model to pool the estimates and 95% confidence intervals (CIs).

RESULTS

From 3475 citations, 25 articles were included. The prevalence of seizures/epilepsy was 4% among dementia patients and 3% among Alzheimer's disease (AD) patients. For vascular dementia, Lewy body dementia, and frontotemporal dementia, the pooled period prevalence of seizures/epilepsy was 6%, 3%, and 2%, respectively. Baseline early-onset AD was associated with the highest risk of 5-year epilepsy (pooled hazard ratios: 4.06; 95% CI: 3.25-5.08). Dementia patients had a 2.29-fold greater risk of seizures/epilepsy than non-dementia patients (95% CI: 1.37-3.83). Moreover, for baseline epilepsy, the pooled prevalence of dementia was 17% (95% CI: 10-25%), and that of AD was 15% (95% CI: 9-21%). The pooled results suggested that epilepsy is associated with a greater risk of dementia (risk ratio: 2.83, 95% CI: 1.64-4.88).

CONCLUSIONS

There are still gaps in epidemiology regarding the correlation between dementia types and epilepsy, vascular risk factors, and the impact of antiseizure medication or cognitive improvement drugs on epilepsy and AD comorbidity.

Premature mortality risk in individuals with convulsive epilepsy: Results from a longitudinal, prospective, population-based study

OBJECTIVE

To assess premature mortality and identify associated risk factors among individuals with convulsive epilepsy in resource-poor settings using a longitudinal, prospective, population-based approach.

METHOD

The study recruited people with convulsive epilepsy who underwent assessment and management of epilepsy at primary healthcare centers in rural Northwest China, including newly diagnosed individuals and previously identified prevalent cases. All participants were confirmed to have epilepsy by neurologists according to strict criteria and were followed up monthly by primary care physicians. Demographic data and cause of death (COD) were obtained from death certificates or verbal autopsies conducted by neurologists, following the International Classification of Diseases, 10th Edition. The standardized mortality ratio (SMR) and proportionate mortality ratio (PMR) for each cause of death were estimated using the Cause-Of-Death Surveillance Dataset of China (2020). Survival analysis was used to identify risk factors associated with all-cause mortality and death directly due to epilepsy.

RESULTS

During 5.9 years of follow-up with 40,947 person-years, there were 781 (11.2%) deaths among 6967 participants. The risk of premature death in people with convulsive epilepsy was 2.7-fold higher than that in the general population. Young participants had a significantly higher risk (standardized mortality ratio 26.5-52.5) of premature death. The proportionate mortality ratio was higher for cerebrovascular disease (15%), sudden unexpected death in epilepsy (SUDEP) (13.4%), cardiovascular disease (11.7%), status epilepsy (SE) (11.3%), and epilepsy-related accidents (14.0%) than other premature mortality cause of deaths. Additionally, the highest standardized proportional mortality ratio (SPMR) was observed from drowning in all cause of death (10.4, 95% confidence interval [CI]: 7.6-13.8), followed by burning (9.0, 95% CI: 3.7-18.9). Factors that increased the risk of all-cause mortality included male sex, late age of onset, short disease duration, high body mass index, monotherapy, and the frequency of generalized tonic-clonic seizures (GTCS). High frequency of generalized tonic-clonic seizures (> 3 attacks in the last year) was an independent risk factor for premature death directly due to epilepsy (including sudden unexpected death in epilepsy, status epilepsy, and epilepsy-related accidents), while early age of onset (≤ 14 years) and long duration of epilepsy (> 20 years) were independent risk factors for sudden unexpected death in epilepsy. In addition, short duration of epilepsy (≤ 20 years) was an independent risk factor for status epilepsy.

CONCLUSIONS

This study demonstrated that individuals with poorly controlled seizures are more likely to experience premature death, with most deaths being epilepsy-related and preventable. These findings underline the importance of effective seizure treatment and the potential impact on reducing premature mortality among people with convulsive epilepsy.

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

SIGNIFICANCE

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

Cognitive phenotypes in late-onset epilepsy: results from the atherosclerosis risk in communities study

Introduction

Cognitive phenotyping is a widely used approach to characterize the heterogeneity of deficits in patients with a range of neurological disorders but has only recently been applied to patients with epilepsy. In this study, we identify cognitive phenotypes in older adults with late-onset epilepsy (LOE) and examine their demographic, clinical, and vascular profiles. Further, we examine whether specific phenotypes pose an increased risk for progressive cognitive decline.

Methods

Participants were part of the Atherosclerosis Risk in Communities Study (ARIC), a prospective longitudinal community-based cohort study of 15,792 individuals initially enrolled in 1987-1989. LOE was identified from linked Centers for Medicare and Medicaid Services claims data. Ninety-one participants with LOE completed comprehensive testing either prior to or after seizure onset as part of a larger cohort in the ARIC Neurocognitive Study in either 2011-2013 or 2016-2017 (follow-up mean = 4.9 years). Cognitive phenotypes in individuals with LOE were derived by calculating test-level impairments for each participant (i.e., ≤1 SD below cognitively normal participants on measures of language, memory, and executive function/processing speed); and then assigning participants to phenotypes if they were impaired on at least two tests within a domain. The total number of impaired domains was used to determine the cognitive phenotypes (i.e., Minimal/No Impairment, Single Domain, or Multidomain).

Results

At our baseline (Visit 5), 36.3% met criteria for Minimal/No Impairment, 35% for Single Domain Impairment (with executive functioning/ processing speed impaired in 53.6%), and 28.7% for Multidomain Impairment. The Minimal/No Impairment group had higher education and occupational complexity. There were no differences in clinical or vascular risk factors across phenotypes. Of those participants with longitudinal data (Visit 6; n = 24), 62.5% declined (i.e., progressed to a more impaired phenotype) and 37.5% remained stable. Those who remained stable were more highly educated compared to those that declined.

Discussion

Our results demonstrate the presence of identifiable cognitive phenotypes in older adults with LOE. These results also highlight the high prevalence of cognitive impairments across domains, with deficits in executive function/processing speed the most common isolated impairment. We also demonstrate that higher education was associated with a Minimal/No Impairment phenotype and lower risk for cognitive decline over time.

Alzheimer Disease and Epilepsy: A Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Observational studies suggested a bidirectional relationship between Alzheimer disease (AD) and epilepsies. However, it remains debated whether and in which direction a causal association exists. This study aims to explore the relationship between genetic predisposition to AD, CSF biomarkers of AD (β-amyloid [Aβ] 42 and phosphorylated tau [pTau]), and epilepsies with 2-sample, bidirectional Mendelian randomization (MR) method.

METHODS

Genetic instruments were obtained from large-scale genome-wide meta-analysis of AD (Ncase/proxy = 111,326, Ncontrol = 677,663), CSF biomarkers of AD (Aβ42 and pTau, N = 13,116), and epilepsy (Ncase = 15,212, Ncontrol = 29,677) of European ancestry. Epilepsy phenotypes included all epilepsy, generalized epilepsy, focal epilepsy, childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy, generalized epilepsy with tonic-clonic seizures, focal epilepsy with hippocampal sclerosis (focal HS), and lesion-negative focal epilepsy. Main analyses were performed using generalized summary data-based MR. Sensitivity analyses included inverse variance weighted, MR pleiotropy residual sum and outlier, MR-Egger, weighted mode, and weighted median.

RESULTS

For forward analysis, genetic predisposition to AD was associated with an increased risk of generalized epilepsy (odds ratio [OR] 1.053, 95% CI 1.002-1.105, p = 0.038) and focal HS (OR 1.013, 95% CI 1.004-1.022, p = 0.004). These associations were consistent across sensitivity analyses and replicated using a separate set of genetic instruments from another AD genome-wide association study. For reverse analysis, there was a suggestive effect of focal HS on AD (OR 3.994, 95% CI 1.172-13.613, p = 0.027). In addition, genetically predicted lower CSF Aβ42 was associated with an increased risk of generalized epilepsy (β = 0.090, 95% CI 0.022-0.158, p = 0.010).

DISCUSSION

This MR study supports a causal link between AD, amyloid pathology, and generalized epilepsy. This study also indicates a close association between AD and focal HS. More effort should be made to screen seizure in AD, unravel its clinical implications, and explore its role as a putative modifiable risk factor.

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.

Late-onset epilepsy and the risk of dementia: a systematic review and meta-analysis

BACKGROUND

Patients with dementia have higher risk of epilepsy. However, it remains not comprehensively evaluated if late-onset epilepsy (LOE) is associated with higher risk of dementia. We, therefore, performed a meta-analysis to systematically evaluate the association.

METHODS

Relevant cohort studies were identified by search of electronic databases including PubMed, Embase, and Web of Science. A randomized-effect model incorporating the possible between-study heterogeneity was used to pool the results.

RESULTS

Overall, seven cohort studies including 873,438 adults were included, and 16,036 (1.8%) of them had LOE. With a mean follow-up duration of 8.7 years, 33,727 of them were diagnosed as dementia. Pooled results showed that LOE was associated with a higher risk of dementia (risk ratio [RR] 2.39, 95% confidence interval [CI] 2.04-2.81, p < 0.001, I² = 67%). Results of subgroup analysis showed that the association between LOE and the risk of dementia was stronger in hospital-derived participants (RR 4.23, 95% CI 2.67-6.70, p < 0.001) than that in community-derived population (RR 2.25, 95% CI 1.93-2.63, p < 0.001; p for subgroup difference = 0.01). Pooled results of three studies showed that LOE was associated with a higher risk of Alzheimer's disease (RR 2.35, 95% CI 1.08-5.08, p = 0.03, I² = 85%). One study suggested a significant association between LOE and risk of vascular dementia (RR 2.0, 95% CI 1.77-2.26, p < 0.001).

CONCLUSIONS

Evidence from cohort studies suggests that LOE may be a risk factor of dementia.