Socio-Demographic Influences on Epilepsy Outcomes in an Inner-City Population

Association Between Standardized Mortality Ratio and Utilization of Care in US Veterans With Drug-Resistant Epilepsy Compared With All US Veterans and the US General Population

Importance

Drug-resistant epilepsy (DRE) is thought to be associated with increased mortality, but larger population-based studies are lacking. Additionally, the benefit of effective management in DRE lacks evidence.

Objective

To examine the association of utilization of care with mortality in US veterans with DRE.

Design, Setting, and Participants

Observational cohort study conducted between October 1, 2013, and March 31, 2020. Mortality statistics in US veterans with DRE were compared to the US general population and all veterans within the Veterans Health Administration. Epilepsy was defined as use of 1 or more antiseizure medications (ASMs) for 30 days or longer with a seizure diagnosis or 1 inpatient or 2 outpatient encounters with an epilepsy diagnosis. DRE was defined as the use of 2 or more ASMs. Among 9.6 million US veterans, 164 435 (1.7%) had epilepsy, of whom 55 571 (33.8%) had DRE. Epilepsy and DRE were administratively identified based on criteria noted in design. Identified participants were included for analysis.

Exposures

Veterans with DRE.

Main Outcomes and Measures

Standardized mortality ratio (SMR).

Results

Among US veterans with DRE, the mean (SD) age was 58.3 (15.4) years, and 49 430 individuals (88.9%) were male. Of ethnicity data gathered, 3170 individuals (5.7%) were Hispanic or Latino, 50 599 (91.1%) were not Hispanic or Latino, 842 (1.5%) declined to answer, and 960 (1.7%) were recorded as unknown. Of race data gathered, 516 individuals (0.9%) were American Indian or Alaskan Native, 270 (0.5%) were Asian, 11 316 (20.4%) were Black or African American, 587 (1.1%) were of multiple races, 453 (0.8%) were Native Hawaiian or Pacific Islander, 39 543 (71.2%) were White, 1697 (3.1%) declined to answer, and 1189 (2.1%) were recorded as unknown. SMR was 1.50 (95% CI, 1.47-1.53) compared with the US general population and 1.56 (95% CI, 1.53-1.59) compared with all veterans. Utilization rates were 81.1% (n = 45 057) for neurology clinic evaluation, 66.4% (n = 36 905) for magnetic resonance imaging (MRI), and 49.6% (n = 27 546) for electroencephalography (EEG) testing. Only 8350 individuals (15.0%) had comprehensive epilepsy evaluations and 3357 (6.0%) had epilepsy monitoring. Multivariable analysis revealed an association between lower mortality and neurology clinic evaluation, EEG, MRI, epilepsy monitoring, and the use of more than 2 ASMs after adjusting for age and comorbidities.

Conclusions and Relevance

Mortality rates were significantly higher in US veterans with DRE compared to the general population. Better utilization of comprehensive epilepsy care, diagnostic services, and medications were each associated with reduced mortality. These findings indicate that appropriate management of DRE is critical in this population.

Seizure control during the COVID-19 pandemic: Correlating Responsive Neurostimulation System data with patient reports

Objective

To understand the impact of the Coronavirus Disease-2019 (COVID-19) pandemic on seizure frequency in persons with epilepsy with a Responsive Neurostimulation (RNS) system implanted.

Methods

Weekly long episode counts (LEC) were used as a proxy for seizures for six months pre-COVID-19 and during the COVID-19 period. Telephone surveys and chart reviews were conducted to assess patient mental health during the pandemic. The change in LEC between the two time periods was correlated to reported stressors.

Results

Twenty patients were included. Comparing the pre-COVID-19 period to the COVID-19 period, we found that only 5 (25%) patients had increased seizures, which was positively correlated with change in anti-seizure medications (ASM, p = 0.03) and bitemporal seizures (p = 0.03). Increased seizures were not correlated to anxiety (p = 1.00), depression (p = 0.58), and sleep disturbances (p = 1.00). The correlation between RNS-detected and patient-reported seizures was poor (p = 0.32).

Conclusions

Most of our patients did not have an increase in seizures following the COVID-19 pandemic. Changes in ASM and bitemporal seizures were positively correlated to increased LEC. There was no correlation between pandemic-related stress and seizures in those found to have increased seizures.

Significance

This is the first study correlating RNS-derived objective LECs with patient self-reports and potential seizure risk factors during the COVID-19 pandemic.

Social determinants do not affect access to specialized epilepsy care in veterans

INTRODUCTION

It is well established that sociodemographic and neighborhood determinants impact access to healthcare. Veterans with epilepsy (VWE) face unique challenges that may limit access to specialized epilepsy care, though institutional initiatives have aimed to minimize disparities. We assessed the extent to which surrogate markers of access to quality care in VWE were impacted by sociodemographic and neighborhood determinants.

METHODS

The sample included 180 VWE. Surrogate markers included time between initial diagnosis and admission to epilepsy monitoring unit (EMU) (time to referral, TTR), and the number of CT, MRI, and EEGs conducted prior to initial EMU evaluation. Sociodemographic and neighborhood determinants included age, sex, race, education, neighborhood advantage, rural status, distance from home to the nearest VAMC, and number of service connection (SC) conditions. Significant correlations across variables of interest were entered into a linear regression. Group differences between social factors were assessed for early and late TTR groups (based on 1st and 4th quartiles).

RESULTS

The mean TTR was 12 years (SD ± 13.18). Longer TTR was correlated to older age (p < 0.001) and fewer SC conditions (p = 0.03). None of the other factors were significantly correlated to TTR. Older age significantly predicted longer TTR on regression. The earlier TTR group was younger, had more SC conditions, lived closer to a VAMC, and was more likely to be female. Greater geographic distance was correlated with fewer CT scans (p = 0.01). A greater number of MRIs was correlated with older age (p = 0.04). Younger age (p < 0.01) and greater education (p = 0.01) were correlated with more SC.

CONCLUSION

Access to epilepsy care among VWE was largely unimpacted by social determinants, with the exception of older age leading to longer TTR. The TTR in VWE was considerably shorter than has been reported in the literature for civilian patients. The Veterans Health Administration model of care may harbor certain advantages in epilepsy treatment.

Poverty, insurance, and region as predictors of epilepsy treatment among US adults

Disparities in epilepsy treatment have previously been reported. In the current study, we examine the role of socioeconomic status, health insurance, place of residence, and sociodemographic characteristics in past-year visit to a neurology or epilepsy provider and current use of antiseizure medications. Multiple years of data were compiled from the National Health Interview Surveys, Sample Adult Epilepsy Modules. The sample (n = 1655) included individuals 18 years and older who have been told by a doctor to have epilepsy or seizures. Independent variables included number of seizures in the past year, health insurance, poverty status, education, region, race/ethnicity, foreign-born status, age, and sex/gender. Two sets of weighted hierarchical logistic regression models were estimated predicting past-year epilepsy visit and current medication use. Accounting for recent seizure activity and other factors, uninsured and people residing outside of the Northeast were less likely to see an epilepsy provider, and people living in poverty were less likely to use medications, relative to their comparison groups. However, no racial/ethnic and nativity-based differences in specialty service or medication use were observed. Further research, including longitudinal studies of care trajectories and outcomes, are warranted to better understand healthcare needs of people with epilepsy, in particular treatment-resistant seizures, and to develop appropriate interventions at the policy, public health, and health system levels.

Factors Associated with Good Seizure Control in Patients on Valproic Acid

Objective

This study aims to generate a reference range for valproic acid (VPA) in this cohort and determine the factors associated with good seizure control in patients taking this drug.

Materials and Methods

We conducted a prospective, cohort, observational study among patients with epilepsy who received VPA treatment at Hospital Kuala Lumpur. The patients were considered to have good control if they had a 50% or higher seizure reduction in the one-year study period compared with the previous year. The VPA reference range was generated from those patients who had good control and whose drug concentration values were available. Multiple logistic regression analysis with a backward likelihood ratio method was applied to assess the predicting factors for good seizure control.

Results

A total of 242 patients were recruited and followed up for one year. The VPA reference range was determined to be 40-85 mg/L. After multivariate analysis, significant predictive variables for good control were monotherapy [adjusted OR 4.74, 95% CI: 2.258, 9.947, p<0.001], non-smoking [adjusted OR 3.23, 95% CI: 1.099, 9.473, p=0.033], normal brain imaging results [adjusted OR 5.83, 95% CI: 2.507, 13.552, p<0.001], and the absence of stress [adjusted OR 19.98, 95% CI: 9.255, 42.764, p<0.001].

Conclusion

Monotherapy, non-smoking, normal brain imaging results, and the absence of stress are predictive of good seizure control in patients on VPA. However, a serum concentration of VPA in the reference range failed to predict good seizure control.

Racial and Ethnic Differences in Pediatric Readmissions for Common Chronic Conditions

OBJECTIVE

To compare the timing and magnitude of variation of pediatric readmission rates across race/ethnicity for selected chronic conditions: asthma, diabetes, seizures, migraines, and depression.

STUDY DESIGN

Retrospective analysis of hospitalizations at 48 children's hospitals in the 2013 Pediatric Health Information System database for children (ages 0-18 years) admitted for asthma (n = 36 910), seizure (n = 35 361), diabetes (n = 12 468), migraine (n = 5882), and depression (n = 5132). Generalized linear models with a random effect for hospital were used to compare the likelihood of readmission by patients' race/ethnicity, adjusting for severity of illness, age, payer, and medical complexity. Adjusted readmission rates were calculated by week over 1 year.

RESULTS

Significant variation in adjusted readmission rates by race/ethnicity existed for conditions aside from depression. Disparities for diabetes and asthma emerged at 3 and 4 weeks, respectively; they remained divergent up to 1 year with the highest 1-year readmission rates in non-Hispanic blacks vs other race/ethnicities (diabetes: 21.7% vs 13.4%, P < .001; asthma: 21.4% vs 14.6%, P < .001). Disparities for migraines and seizure emerged at 6 and 7 weeks, respectively; they remained up to 1 year, with the highest 1-year readmission rates in non-Hispanic whites vs other race/ethnicities (migraine: 17.3% vs 13.6%, P < .001; seizure: 23.9% vs 21.9%, P < .001).

CONCLUSIONS

Readmission disparities behave differently across chronic conditions. They emerge more quickly after discharge for children hospitalized with asthma or diabetes than for seizures or migraines. The highest readmission rates were not consistently observed for 1 particular race/ethnicity. Study findings can impact pediatric chronic disease management to improve care for children with these conditions.

Does adherence to epilepsy quality measures correlate with reduced epilepsy-related adverse hospitalizations? A retrospective experience

In 2011, the American Academy of Neurology (AAN) established eight epilepsy quality measures (EQMs) for chronic epilepsy treatment to address deficits in quality of care. This study assesses the relationship between adherence to these EQMs and epilepsy-related adverse hospitalizations (ERAHs). A retrospective chart review of 475 new epilepsy clinic patients with an ICD-9 code 345.1-9 between 2010 and 2012 was conducted. Patient demographics, adherence to AAN guidelines, and annual number of ERAHs were assessed. Fisher's exact test was used to assess the relationship between adherence to guidelines (as well as socioeconomic variables) and the presence of one or more ERAH per year. Of the eight measures, only documentation of seizure frequency, but not seizure type, correlated with ERAH (relative risk [RR] 0.343, 95% confidence interval [CI] 0.176-0.673, p = 0.010). Among patients in the intellectually disabled population (n = 70), only review/request of neuroimaging correlated with ERAH (RR 0.128, 95% CI 0.016-1.009, p = 0.004). ERAHs were more likely in African American patients (RR 2.451, 95% CI 1.377-4.348, p = 0.008), Hispanic/Latino patients (RR 4.016, 95% CI 1.721-9.346, p = 0.016), Medicaid patients (RR 2.217, 95% CI 1.258-3.712, p = 0.009), and uninsured patients (RR 2.667, 95% CI 1.332-5.348, p = 0.013). In this retrospective series, adherence to the eight AAN quality measures did not strongly correlate with annual ERAH.

Social determinants of health in epilepsy

Social factors have been identified as key drivers of epilepsy care, outcomes, and disparities, but there is a limited understanding of what these factors are and how they translate into disparities. This targeted review provides an overview of the social determinants of health framework and applies this perspective to the literature about social and psychosocial factors in epilepsy; a social determinants of health--epilepsy model is proposed. The key social determinants of health in epilepsy include socioeconomic status, race/ethnicity, age, and gender. For example, low socioeconomic status and minority status have been associated with a higher risk of epilepsy, more hospitalizations and emergency room visits (versus neurology services), antiepileptic drug nonadherence, and a lower rate of epilepsy surgery. Such differences in care/treatment and outcomes translate into health disparities, many of which are considered unjust (inequitable) and modifiable through social action. Other social determinants of health include structural and sociocultural contextual conditions (e.g., health economy, policy, and social stigma/discrimination) and mediating mechanisms including material (e.g., housing), behavioral/biological (e.g., adherence), psychosocial (e.g., perceived stigma), and health system (e.g., access) factors. There are complex relationships among social determinants of health in epilepsy, which remain poorly understood and hamper efforts to address and eliminate disparities in epilepsy care and outcomes. Further empirical work grounded in sound theory and robust methodologies is needed to identify points of intervention and design effective and socially acceptable solutions to any pervasive disparities in epilepsy.