Risk of epilepsy in pediatric patients with febrile seizures: Insights from nationwide registry data in Korea

PURPOSE

The incidence of epilepsy following febrile seizures (FS) is estimated at 2 %-7 %. Early identification of children at risk of epilepsy could have clinical implications, as these children may require special attention. This study investigated epilepsy incidence in children with FS and identified risk factors that increase the likelihood of developing epilepsy in Korea.

METHODS

This nationwide, population-based study used data from the Korean Health Insurance Review and Assessment Service database. Patients aged 6 months to <6 years at their first visit between January 2010 and June 2013 with primary, secondary, or additional FS diagnostic codes were selected. Patient demographics, diagnostic codes, and prescriptions were retrieved from the database.

RESULTS

A total of 130,248 patients diagnosed with FS were identified. During a median follow-up period of 11.8 years (interquartile range, 11.0-12.8), 3,047 patients (2.3 %) were subsequently diagnosed with epilepsy, while 127,201 patients (97.7 %) did not develop epilepsy. A higher number of FS episodes (2 episodes, odds ratio (OR) 1.61; 3 episodes, OR 2.17; 4 episodes, OR 2.40; 5+ episodes, OR 4.85) and prolonged FS (OR 25.82) were associated with increased epilepsy risk (p < 0.05). Epilepsy was most common during toddler and preschool years (2,049/3,047, 67.2 %), while it was relatively low during adolescence (141/3,047, 4.6 %).

CONCLUSION

Recognizing the risk factors and age distribution of epilepsy onset can assist clinicians in identifying children at high risk early, facilitating targeted monitoring and timely intervention. This approach may ultimately reduce unnecessary investigations and optimize follow-up for children with FS.

Validation of ICD codes for the identification of patients with functional seizures

OBJECTIVE

To evaluate the validity of ICD-9-CM and ICD-10 codes for the identification of patients with functional seizures (FS).

METHODS

We evaluated the charts of 800 patients including 400 in an institution wide sample and 400 in an epilepsy monitoring unit (EMU) sample. Half of the patients from each sample came from 2012-2013 and 2022-2023 since ICD-9-CM codes and ICD-10 codes were exclusively used in these respective periods. The charts of each patient were manually reviewed and evaluated for the presence of epilepsy and FS. Based on the 2013 International League Against Epilepsy (ILAE) Nonepileptic Seizures Task Force guidelines we determined whether a patient had either presumptive (clinically established or documented) or probable/possible FS. We evaluated ICD-9-CM codes 300.11 (conversion disorder) and 780.39 (other convulsions) as well as ICD-10 codes F44.5 (conversion disorder or functional neurological disorder with seizures or convulsions) and R56.9 (unspecified convulsions). The positive predictive value (PPV) of each ICD code was calculated in the institution wide sample and the sensitivity, specificity, PPV and negative predictive values (NPV) were calculated in the EMU sample.

RESULTS

In the institution wide sample, F44.5 had a PPV of 74.0 % (64.6-81.6) for presumptive FS and 80.0 % (71.1-86.7) when probable/possible FS patients were included. The code 300.11 had a PPV of 52.0 % (42.3-61.5) for presumptive FS and 59.0 % (49.2-68.1) when probable/possible FS patients were included. Codes R56.9 and 780.39 had PPVs that were equal to or less than 20 %. In the EMU sample, the code F44.5 had a sensitivity, specificity, PPV and NPV of 67.1 % (56.3-76.3), 95.8 % (90.5-98.2), 91.7 % (81.9-96.4), and 80.7 % (73.4-86.4), respectively for presumptive FS. The code 300.11 had a sensitivity, specificity, PPV and NPV of 30.1 % (20.8-41.4), 95.3 % (90.1-97.8), 78.6 % (60.5-89.8), and 70.4 % (63.1-76.7), respectively for presumptive FS. The codes R56.9 and 780.39 performed poorly.

SIGNIFICANCE

ICD codes had a mixed performance when used to identify patients with FS. ICD-10 code F44.5 appeared to perform the best overall.

How Reliable Is the G41 Discharge Code for Status Epilepticus?

INTRODUCTION

Medico-administrative databases are increasingly used to study the epidemiology of status epilepticus (SE), targeting hospitalizations with the SE G41 ICD-10 code. However, the positive predictive value (PPV) of the G41 code, which measures the percentage of true cases among those identified by the code, is unknown.

METHODS

We identified all hospitalizations with a primary or secondary diagnosis coded as G41 in five different hospitals. Medical reports for each hospitalization were reviewed to classify the stays as really related to SE or not, using two distinct approaches (sensitive and specific). The clinical characteristics of SE cases were also extracted.

RESULTS

Among the 797 hospitalizations identified, the PPV ranged from 85.7% using the sensitive approach to 70.6% with the specific approach. Hospitalizations coded with G41 as the main diagnosis had the highest PPV, whereas codes G411 and G418 showed the lowest PPV. Of the 400 hospitalizations with a G410 (generalized convulsive SE) code, 72.7% were classified as generalized convulsive SE, while 76.5% of the 149 hospitalizations with a G412 (focal SE) code were classified as focal SE.

CONCLUSION

Our findings highlight that PPV varies by G41 subtype and diagnostic position. Studies requiring a higher PPV should exclude certain codes or hospitalizations with G41 code only as an associated diagnosis. Further studies are needed to estimate the sensitivity and specificity of G41 code.

Is geographical variation in emergency epilepsy admissions related to variation in new epilepsy diagnoses among children and young people across England? An observational study using linked datasets

INTRODUCTION

Previous studies have reported widespread unexplained geographical variations in emergency paediatric admissions for epilepsy.

OBJECTIVES

Our aim was to investigate the extent to which geographical variation in epilepsy admissions among children and young people (CYP) aged 0-18 years, in England, reflects variation in new epilepsy diagnoses.

DESIGN AND SETTING

A retrospective secondary analysis of Hospital Episode Statistics data for emergency admissions between April 2018 and March 2019, and Epilepsy12 audit data for new epilepsy diagnoses in England, between July and November 2018.

OUTCOME MEASURES

The ratios of observed to expected epilepsy admissions and new diagnoses were calculated for each hospital Trust, based on their catchment population, and adjusted for age, sex and deprivation. Standardised ratios of observed to expected epilepsy admissions were plotted against standardised ratios of observed to expected new diagnoses of epilepsy at Trust level and the Pearson correlation coefficient was calculated.

RESULTS

There were 9246 emergency admissions for CYP to 134 Trusts with a primary diagnosis of epilepsy in England during the study period. 60 Trusts (44.4%) had either significantly lower or higher than expected standardised admission ratios for a primary diagnosis of epilepsy. There were 960 new diagnoses of epilepsy between July and November 2018 for 74 Trusts. 14 Trusts (18.9%) had either lower or higher standardised diagnosis ratios for a new diagnosis of epilepsy. There was no correlation between standardised emergency epilepsy admissions ratios and standardised new epilepsy diagnoses ratios at Trust level (Pearson r -0.06, p 0.63).

CONCLUSIONS

Widespread unexplained variation in epilepsy admissions cannot be explained by variation in new epilepsy diagnosis. This raises concerns about the equity and accessibility of epilepsy services. Unit-level benchmarking data on new diagnoses and admissions for epilepsy can inform strategies to improve access to care and health outcomes.

Risk of Epilepsy Following a First Posttraumatic Seizure: A Register-Based Study

Background and Objectives

Traumatic brain injury (TBI) is a common cause of epilepsy, and the risk increases with injury severity. Whether a first posttraumatic seizure (PTS) represents epilepsy is a common clinical problem, but often unknown. Prognostication is important for providing correct patient information and consideration of antiseizure medication. Our objective was to understand how trauma severity and latency from the injury affect the risk of epilepsy after a first PTS.

Methods

The register-based cohort study including all individuals hospitalized following a TBI in Sweden 2000-2010, in addition to 3 age-matched and sex-matched controls per case. We analyzed the 10-year probability of epilepsy following a first seizure using the Kaplan-Meier estimator.

Results

The risk of an epilepsy diagnosis was 41.1% (95% CI 38.6-43.7) following a PTS, higher than the risk of 33.4% (95% CI 30.3-36.5) in those without prior TBI. The risk increased with injury severity, with the highest risk following focal cerebral injuries, 62.3% (95% CI 53.7-70.9). Mild injuries and skull fractures showed a similar risk to the group without previous TBI. In addition, the risk was higher if the seizure occurred <2 years following the trauma.

Discussion

Severity of the injury and latency are major modulators of epilepsy risk following a first PTS. The risk was high in the most severe types of TBI, but a substantial proportion did not develop epilepsy, highlighting the need for further research on prognostication and biomarkers, as well as caution in diagnosing epilepsy based on a first PTS.

Using electronic medical records to analyze outpatient visits of persons with epilepsy during the pandemic-experience from a low middle income country

BACKGROUND

Electronic medical records (EMR) can be utilized to understand the impact of the disruption in care provision caused by the pandemic. We aimed to develop and validate an algorithm to identify persons with epilepsy (PWE) from our EMR and to use it to explore the effect of the pandemic on outpatient service utilization.

METHODS

EMRs from the neurology specialty, covering the period from January 2018 to December 2023, were used. An algorithm was developed using an iterative approach to identify PWE with a critical lower bound of 0.91 for negative predictive value. Manual internal validation was performed. Outpatient visit data were extracted and modeled as a time series using the autoregressive integrated moving average model. All statistical analyses were performed using STATA version 14.2 (Statacorp, USA).

RESULTS

Four iterations resulted in an algorithm, with a negative predictive value 0.98 (95% CI: 0.95-0.99), positive predictive value of 0.98 (95% CI: 0.85-0.99), and an F-score accuracy of 0.96, which identified 4474 PWE. The outpatient service utilization was abruptly reduced by the pandemic, with a change of -902.1 (95%CI: -936.55 to -867.70), and the recovery has also been slow, with a decrease of -5.51(95%CI: -7.00 to -4.02). Model predictions aligned closely with actual visits with median error of -3.5%.

CONCLUSIONS

We developed an algorithm for identifying people with epilepsy with good accuracy. Similar methods can be adapted for use in other resource-limited settings and for other diseases. The COVID pandemic appears to have caused a lasting reduction of service utilization among PWE.

Air Pollution and Temperature in Seizures and Epilepsy: A Scoping Review of Epidemiological Studies

PURPOSE OF THE REVIEW

Seizures and epilepsy can be debilitating neurological conditions and have few known causes. Emerging evidence has highlighted the potential contribution of environmental exposures to the etiology of these conditions, possibly manifesting via neuroinflammation and increased oxidative stress in the brain. We conducted a scoping review of epidemiological literature linking air pollution and temperature exposures with incidence and acute aggravation of seizures and epilepsy. We systematically searched PubMed, Embase, Web of Science, and APA PsycINFO databases for peer-reviewed journal articles published in English from inception to February 7, 2024.

RECENT FINDINGS

We identified a total of 34 studies: 16 examined air pollution exposure, 12 ambient temperature, and six examined both air pollution and ambient temperature. Most studies were conducted in Asia (China, Taiwan, South Korea, and Japan). Nearly all studies retrospectively derived acute (daily average), ambient, and postnatal exposure estimates from ground monitoring systems and ascertained epilepsy cases or seizure events through record linkage with medical records, health registry systems, or insurance claims data. Commonly assessed exposures were particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), and daily mean ambient temperature. Overall, the main findings across studies lacked consistency, with mixed results reported for the associations of air pollutants and temperature metrics with both seizure incidence and acute aggravations of epilepsy.

Demographic and regional patterns of epilepsy-related mortality in the USA: Insights from CDC WONDER data

Background

Epilepsy poses significant challenges globally, with varied clinical, social, and economic impacts. Despite advances in treatment, epilepsy-related mortality remains a concern. This study aimed to analyze the demographic and regional distributions of epilepsy-related mortality in the United States (U.S.) from 1999 to 2020, identifying high-risk populations for targeted interventions.

Methods

Data on death certificates were obtained from the 1999 to 2020 Centers for Disease Control and Prevention Wide-Ranging Online Study Epidemiologic Research (CDC-WONDER) database. We gathered data on demographics, place of death, and urban/rural classification. Mortality rates per 100,000 people were computed and classified according to state, year, sex, race/ethnicity, and urban/rural status. Trends were examined using Joinpoint regression.

Results

A total of 12,573 deaths (age <35), 22,947 (35-64), and 21,782 (65+) were attributed to epilepsy. Mortality rates varied by age group, sex, race/ethnicity, and region. Trends showed significant increases, notably in middle-aged and older adults, with higher rates in males and nonHispani, African American populations.

Conclusion

Epilepsy-related mortality exhibits demographic and regional disparities in the U.S. Understanding these patterns can guide targeted interventions to mitigate mortality risk.

Poststroke seizures and epilepsy increase the risk of dementia among stroke survivors: A population-based study

OBJECTIVE

With global aging, the occurrence of stroke and associated outcomes like dementia are on the rise. Seizures and epilepsy are common poststroke complications and have a strong connection to subsequent dementia. This study examines the relationship between poststroke seizures (PSS) or poststroke epilepsy (PSE) and dementia using a national health care database.

METHODS

We conducted a retrospective study using data from the Taiwan National Health Insurance Research Database from 2009 to 2020. We identified acute stroke patients from 2010 to 2015, excluding those with pre-existing neurological conditions. Based on age, sex, stroke severity level, and the year of index stroke, patients with PSS or PSE were matched to those without. The main outcome was incident dementia.

RESULTS

This study included 62 968 patients with an average age of 63 years, with males accounting for 62.9%. Of them, 60.3% had ischemic strokes, and 39.7% had hemorrhagic strokes. After an average follow-up period of 5.2 years, dementia developed in 15.9% of patients who had PSS or PSE, as opposed to 8.4% of those without these conditions. A time-dependent Fine and Gray competing risk analysis showed that PSS and PSE were significantly associated with dementia across all stroke types. Subgroup analyses revealed significantly increased risk of dementia across all age groups (<50, 50-64, and ≥65 years), sexes, and various stroke severity levels. The link between PSS or PSE and dementia was particularly pronounced in men, with a less distinct correlation in women.

SIGNIFICANCE

The risk of incident dementia was higher in patients with PSS or PSE. The potential for therapeutic interventions for seizures and epilepsy to reduce poststroke dementia underscores the importance of seizure screening and treatment in stroke survivors.

Morbidity and mortality risks associated with valproate withdrawal in young adults with epilepsy

Valproate is the most effective treatment for idiopathic generalized epilepsy. Current guidance precludes its use in females of childbearing potential, unless other treatments are ineffective or not tolerated, because of high teratogenicity. This risk was recently extended to males. New guidance will limit use both in males and females aged <55 years, resulting in withdrawal of valproate from males already taking it, as occurs for females. Whether there are risks of personal harm (including injury or death) associated with valproate withdrawal has not yet been quantified for males or females ON valproate, meaning clinicians cannot reliably counsel either sex when discussing valproate withdrawal with them, despite that this concern may be at the forefront of patients' and clinicians' minds. We assessed whether there are any morbidity or mortality risks associated with valproate withdrawal in young males and females. We performed a retrospective cohort study of internationally derived electronic health data within the TriNetX Global Collaborative Network. Included were males and females aged 16-54 years with ≥1 epilepsy disease or symptom code between 1 December 2017 and 1 December 2018, and ≥2 valproate prescriptions over the preceding 2 years (1 January 2015-30 November 2017). Five-year propensity-matched risks of mortality and a range of morbidity outcomes were compared between those remaining ON versus withdrawn from valproate during the 1 December 2017-1 December 2018 recruitment period, regardless of whether switched to another antiseizure medication. Survival analysis was undertaken using Cox-proportional hazard models, generating hazard ratios (HRs) with 95% confidence intervals (CIs). In total, 8991 males and 5243 females taking valproate were recruited. Twenty-eight per cent of males and 36% of females were subsequently withdrawn from valproate. Valproate withdrawal was associated with significantly increased risks of emergency department attendance [HRs overall: 1.236 (CI 1.159-1.319), males: 1.181 (CI 1.083-1.288), females: 1.242 (CI 1.125-1.371)], hospital admission [HRs overall: 1.160 (CI 1.081-1.246), males: 1.132 (CI 1.027-1.249), females: 1.147 (CI 1.033-1.274)], falls [HRs overall: 1.179 (CI 1.041-1.336), males: 1.298 (CI 1.090-1.546)], injuries [HRs overall: 1.095 (CI 1.021-1.174), males: 1.129 (CI 1.029-1.239)], burns [HRs overall: 1.592 (CI 1.084-2.337)] and new-onset depression [HRs overall 1.323 (CI 1.119-1.565), females: 1.359 (CI 1.074-1.720)]. The risk of these outcomes occurring was 1%-7% higher in those withdrawn from valproate than in those remaining ON valproate. Overall, valproate withdrawal was not associated with increased mortality. These results may help patients and clinicians have a more informed discussion about personal safety when considering valproate withdrawal.

Hospitalisations for chronic conditions among care experienced and general population children and young people: evidence from the Children's Health in Care in Scotland (CHiCS) cohort study, 1990-2016

OBJECTIVE

There is limited evidence on how the physical health of children and young people (CYP) who are care experienced (eg, in foster or out-of-home care) compares to the general population. UK research suggests that the prevalence of some chronic conditions may be similar for these groups.

DESIGN

We undertook longitudinal population-wide data linkage of social care, prescription and hospitalisation records for care experienced and general population CYP born 1990-2004, followed from birth to August 2016. We compared prevalence estimates for asthma, diabetes (type 1) and epilepsy between the cohorts and used Poisson and survival models to estimate the association between social care and hospitalisations for these conditions.

RESULTS

Care experience was not associated with a higher prevalence of asthma and diabetes, but epilepsy was more prevalent. Care was associated with increased hospitalisation rates for all three conditions, particularly for males. HRs for hospitalisations were highest before and after care and lower while the child was in care, for diabetes these were, respectively 1.88 (95% CI 1.28 to 2.77), 2.40 (95% CI 1.55 to 3.71) and 1.31 (95% CI 0.91 to 1.88) for care experienced CYP compared with general population.

CONCLUSIONS

Hospitalisations for chronic conditions are higher among care experienced CYP, particularly for males, and outside care episodes. Families with children with chronic conditions should be offered support to manage these conditions and help keep families together. Higher hospitalisations after care suggest that care leavers should be provided more support to help manage their health.

In-hospital outcomes in people with autism and epilepsy - A population-based study

Autism is a common comorbid diagnosis in those with epilepsy. Understanding the health needs and outcomes in patients with this dual diagnosis is important for optimizing healthcare outcomes. We compared hospital-level variables amongst patients with co-occurring autism and epilepsy, to those with epilepsy alone. Non-elective hospital admissions amongst patients with epilepsy alone and co-occurring autism and epilepsy were identified in the 2003-14 National Inpatient Sample (NIS) using previously validated ICD-9-CM case definitions. One patient with co-occurring epilepsy and autism was matched to three epilepsy patients for age and sex. Multinomial logistic regressions were performed to examine outcomes of interest. Compared to those with epilepsy alone (n = 27,762), patients with autism and epilepsy (n = 9254) had a higher odds of transfer to another facility (OR = 1.09, p = 0.048), in-hospital mortality (OR = 1.36, p = 0.011), longer mean length of stay (5.63 days vs. 5.12 days, p < 0.0001), and septicemia (4.21 % vs. 3.08 %, p < 0.0001). Distributions of demographics, insurance type, socioeconomic status, and comorbidities significantly differed between both groups. Our findings demonstrate that patients with comorbid autism and epilepsy are a unique population with health outcomes significantly differing from those with epilepsy alone. Given the effect that dual diagnosis has on hospital trajectory, focused treatment plans must be adopted to optimize care and hospital outcomes in these patients.

An international study to investigate and optimise the safety of discontinuing valproate in young men and women with epilepsy: Protocol

Valproate is the most effective treatment for idiopathic generalised epilepsy. Currently, its use is restricted in women of childbearing potential owing to high teratogenicity. Recent evidence extended this risk to men's offspring, prompting recommendations to restrict use in everybody aged <55 years. This study will evaluate mortality and morbidity risks associated with valproate withdrawal by emulating a hypothetical randomised-controlled trial (called a "target trial") using retrospective observational data. The data will be drawn from ~250m mainly US patients in the TriNetX repository and ~60m UK patients in Clinical Practice Research Datalink (CPRD). These will be scanned for individuals aged 16-54 years with epilepsy and on valproate who either continued, switched to lamotrigine or levetiracetam, or discontinued valproate between 2014-2024, creating four groups. Randomisation to these groups will be emulated by baseline confounder adjustment using g-methods. Mortality and morbidity outcomes will be assessed and compared between groups over 1-10 years, employing time-to-first-event and recurrent events analyses. A causal prediction model will be developed from these data to aid in predicting the safest alternative antiseizure medications. Together, these findings will optimise informed decision-making about valproate withdrawal and alternative treatment selection, providing immediate and vital information for patients, clinicians and regulators.

Revascularization Therapies for Ischemic Stroke and Association With Risk of Epilepsy: A Danish Nationwide Register-Based Study

BACKGROUND

The association between stroke revascularization therapies and poststroke epilepsy is only sparsely investigated, and results are conflicting. The aim of this study is to investigate whether stroke revascularization therapies are associated with different risks of poststroke epilepsy.

METHODS AND RESULTS

We conducted a nationwide, register-based, propensity score-matched cohort study. We identified 40 816 patients admitted with a first ischemic stroke and no prior history of epilepsy in Denmark between January 1, 2011, and December 16, 2018. Of these, 6541 were treated with thrombolysis, 379 with thrombectomy, and 1005 with both thrombolysis and thrombectomy. The 3 treatment groups were each matched 1:1 to patients with stroke not treated with revascularization. Exact matching was done for sex, while propensity scores included information on stroke severity, cortical involvement, age, comorbidities, and socioeconomic parameters. Outcome was any diagnosis of epilepsy. We used Cox regressions to estimate adjusted hazard ratios (HRs) of epilepsy after ischemic stroke. Compared with matched patients with ischemic stroke not receiving revascularization treatment, patients who received thrombolysis alone had 32% lower risk of epilepsy (adjusted HR, 0.68 [95% CI, 0.57-0.81]) and patients who received thrombolysis and thrombectomy had 45% lower risk of epilepsy (adjusted HR, 0.55 [95% CI, 0.41-0.73]). Thrombectomy alone was not associated with significantly lower risk of epilepsy compared with matched patients with ischemic stroke not receiving revascularization therapy (adjusted HR, 0.78 [95% CI, 0.57-1.29]).

CONCLUSIONS

Thrombolysis alone and in combination with thrombectomy in ischemic stroke was associated with lower risk of epilepsy, whereas thrombectomy alone was not associated with lower risk of epilepsy.

Mortality among veterans with epilepsy: Temporal significance of traumatic brain injury exposure

OBJECTIVE

Epilepsy is associated with significant mortality risk. There is limited research examining how traumatic brain injury (TBI) timing affects mortality in relation to the onset of epilepsy. We aimed to assess the temporal relationship between epilepsy and TBI regarding mortality in a cohort of post-9/11 veterans.

METHODS

This retrospective cohort study included veterans who received health care in the Defense Health Agency and the Veterans Health Administration between 2000 and 2019. For those diagnosed with epilepsy, the index date was the date of first antiseizure medication or first seizure; we simulated the index date for those without epilepsy. We created the study groups by the index date and first documented TBI: (1) controls (no TBI, no epilepsy), (2) TBI only, (3) epilepsy only, (4) TBI before epilepsy, (5) TBI within 6 months after epilepsy, and (6) TBI >6 months after epilepsy. Kaplan-Meier estimates of all-cause mortality were calculated, and log-rank tests were used to compare unadjusted cumulative mortality rates among groups compared to controls. Cox proportional hazard models were used to compute hazard ratios (HRs) with 95% confidence intervals (CIs).

RESULTS

Among 938 890 veterans, 27 436 (2.92%) met epilepsy criteria, and 264 890 (28.22%) had a TBI diagnosis. Mortality was higher for veterans with epilepsy than controls (6.26% vs. 1.12%; p < .01). Veterans with TBI diagnosed ≤6 months after epilepsy had the highest mortality hazard (HR = 5.02, 95% CI = 4.21-5.99) compared to controls, followed by those with TBI before epilepsy (HR = 4.25, 95% CI = 3.89-4.58), epilepsy only (HR = 4.00, 95% CI = 3.67-4.36), and TBI >6 months after epilepsy (HR = 2.49, 95% CI = 2.17-2.85). These differences were significant across groups.

SIGNIFICANCE

TBI timing relative to epilepsy affects time to mortality; TBI within 6 months after epilepsy or before epilepsy diagnosis was associated with earlier time to death compared to those with epilepsy only or TBI >6 months after epilepsy.

Authors reply

(There is no abstract) for this article type.

Second antiseizure medication monotherapy in patients with adult-onset epilepsy: A register-based analysis

OBJECTIVE

Revision of therapy is fundamental in epilepsy care, since only half of patients achieve seizure freedom and tolerate the first antiseizure medication (ASM). We studied the selection and retention of second antiseizure medication monotherapy in adults who discontinued treatment with one of the three most frequently prescribed first ASMs, and the impact of age or brain comorbidities.

METHODS

Using Swedish national registers, we conducted a population-based, retrospective cohort study from 2007 to 2019 on patients age ≥ 30 at the epilepsy diagnosis that had switched to a second monotherapy after the three most common initial monotherapies (n = 7369). Retention rates (RR) were estimated via Kaplan-Meier. Discontinuation of the second monotherapy was defined as 12-month prescription gap or initiation of a third ASM. Analyses were stratified by sex, age, and presence of stroke or dementia.

RESULTS

The three most commonly prescribed second ASMs were carbamazepine, levetiracetam, and lamotrigine. The 1-year retention rate was 63-76% in all patients. For groups with stroke or dementia, the maximal 1-year RRs were 77% and 87%, respectively. After five years, retention rates ranged from 12% to 39%. There were no major differences between ASMs, apart from in patients discontinuing carbamazepine, where lamotrigine had a superior retention compared to levetiracetam as second monotherapy.

SIGNIFICANCE

The three most often prescribed second ASMs seem to be suitable treatment options according to present guidelines. The second ASMs' retention rates were initially high in all studied patient groups but dropped to approximately the expected proportion of second monotherapy responders over the next five years. This suggests that therapy revision could be expedited.

Health care disparities in morbidity and mortality in adults with acute and remote status epilepticus: A national study

OBJECTIVE

Although disparities have been described in epilepsy care, their contribution to status epilepticus (SE) and associated outcomes remains understudied.

METHODS

We used the 2010-2019 National Inpatient Sample to identify SE hospitalizations using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)/ICD-10-CM codes. SE prevalence was stratified by demographics. Logistic regression was used to assess factors associated with electroencephalographic (EEG) monitoring, intubation, tracheostomy, gastrostomy, and mortality.

RESULTS

There were 486 861 SE hospitalizations (2010-2019), primarily at urban teaching hospitals (71.3%). SE prevalence per 10 000 admissions was 27.3 for non-Hispanic (NH)-Blacks, 16.1 for NH-Others, 15.8 for Hispanics, and 13.7 for NH-Whites (p < .01). SE prevalence was higher in the lowest (18.7) compared to highest income quartile (18.7 vs. 14, p < .01). Older age was associated with intubation, tracheostomy, gastrostomy, and in-hospital mortality. Those ≥80 years old had the highest odds of intubation (odds ratio [OR] = 1.5, 95% confidence interval [CI] = 1.43-1.58), tracheostomy (OR = 2, 95% CI = 1.75-2.27), gastrostomy (OR = 3.37, 95% CI = 2.97-3.83), and in-hospital mortality (OR = 6.51, 95% CI = 5.95-7.13). Minority populations (NH-Black, NH-Other, and Hispanic) had higher odds of tracheostomy and gastrostomy compared to NH-White populations. NH-Black people had the highest odds of tracheostomy (OR = 1.7, 95% CI = 1.57-1.86) and gastrostomy (OR = 1.78, 95% CI = 1.65-1.92). The odds of receiving EEG monitoring rose progressively with higher income quartile (OR = 1.47, 95% CI = 1.34-1.62 for the highest income quartile) and was higher for those in urban teaching compared to rural hospitals (OR = 12.72, 95% CI = 8.92-18.14). Odds of mortality were lower (compared to NH-Whites) in NH-Blacks (OR = .71, 95% CI = .67-.75), Hispanics (OR = .82, 95% CI = .76-.89), and those in the highest income quartiles (OR = .9, 95% CI = .84-.97).

SIGNIFICANCE

Disparities exist in SE prevalence, tracheostomy, and gastrostomy utilization across age, race/ethnicity, and income. Older age and lower income are also associated with mortality. Access to EEG monitoring is modulated by income and urban teaching hospital status. Older adults, racial/ethnic minorities, and populations of lower income or rural location may represent vulnerable populations meriting increased attention to improve health outcomes and reduce disparities.

Characterization and quantification of epilepsy patients with hospital episodes in Portugal: A multicenter retrospective study from Liga Portuguesa Contra a Epilepsia

INTRODUCTION

Epilepsy affects around 50 million people worldwide and is associated with lower quality of life scores, an increased risk of premature death, and significant socio-economic implications. The lack of updated evidence on current epidemiology and patient characterization creates considerable uncertainty regarding the epilepsy burden in Portugal. The study aims to characterize and quantify the epilepsy patients who have been hospitalized, with medical or surgical procedures involved, and to analyze their associated comorbidities and mortality rates.

METHODS

A multicenter retrospective study was conducted using hospital production data of epilepsy patients. The study included all patients diagnosed with epilepsy-related International Classification of Diseases-9/10 codes between 2015 and 2018 in 57 Portuguese National Health Service (NHS) hospitals (n = 57 institutions). Patient characterization and quantification were done for all patients with an epilepsy diagnosis, with specific analyses focusing on those whose primary diagnosis was epilepsy. Baseline, demographic, and clinical characteristics were analyzed using descriptive statistics.

RESULTS

Between 2015 and 2018, a total of 80,494 hospital episodes (i.e., patient visit that generates hospitalization and procedures) were recorded, with 18 % to 19 % directly related to epilepsy. Among these epilepsy-related hospital episodes, 13.0 % led to short term hospitalizations (less than 24 h). Additionally, the average length of stay for all these epilepsy-related episodes was 8 days. A total of 49,481 patients were identified with epilepsy based on ICD-9/10 codes. The median age of patients was 64 years (min: 0; max: 104), with a distribution of 4.8 patients per 1,000 inhabitants. From the total of deaths (9,606) between 2015 and 2018, 14% were associated with patients whose primary diagnosis was epilepsy, with 545 of these being epilepsy-related deaths. Among patients with a primary diagnosis of epilepsy, the most common comorbidities were hypertension (24%) and psychiatric-related or similar comorbidities (15%), such as alcohol dependance, depressive and major depressive disorders, dementia and other convulsions.

CONCLUSION

This study showed similar results to other European countries. However, due to methodological limitations, a prospective epidemiological study is needed to support this observation. Furthermore, the present study provides a comprehensive picture of hospitalized epilepsy patients in Portugal, their comorbidities, mortality, and hospital procedures.

A Capture-Recapture-based Ascertainment Probability Weighting Method for Effect Estimation With Under-ascertained Outcomes

Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates capture-recapture and propensity score weighting. We propose a nonparametric estimator of effects on binary outcomes that combines exposure propensity scores with data from two conditionally independent outcome measurements to simultaneously adjust for confounding and under-ascertainment. Demonstrating its practical application, we apply the method to estimate the relationship between health care work and coronavirus disease 2019 testing in a Swedish region. We find that ascertainment probability weighting greatly influences the estimated association compared to conventional inverse probability weighting, underscoring the importance of accounting for under-ascertainment in studies with limited outcome data coverage. We conclude with practical guidelines for the method's implementation, discussing its strengths, limitations, and suitable scenarios for application.

Hospital variation of outcomes in status epilepticus

OBJECTIVE

Understanding factors driving variation in status epilepticus outcomes would be critical to improve care. We evaluated the degree to which patient and hospital characteristics explained hospital-to-hospital variability in intubation and postacute outcomes.

METHODS

This was a retrospective cohort study of Medicare beneficiaries admitted with status epilepticus between 2009 and 2019. Outcomes included intubation, discharge to a facility, and 30- and 90-day readmissions and mortality. Multilevel models calculated percent variation in each outcome due to hospital-to-hospital differences.

RESULTS

We included 29 150 beneficiaries. The median age was 68 years (interquartile range [IQR] = 57-78), and 18 084 (62%) were eligible for Medicare due to disability. The median (IQR) percentages of each outcome across hospitals were: 30-day mortality 25% (0%-38%), any 30-day readmission 14% (0%-25%), 30-day status epilepticus readmission 0% (0%-3%), 30-day facility stay 40% (25%-53%), and intubation 46% (20%-61%). However, after accounting for many hospitals with small sample size, hospital-to-hospital differences accounted for 2%-6% of variation in all unadjusted outcomes, and approximately 1%-5% (maximally 8% for 30-day readmission for status epilepticus) after adjusting for patient, hospitalization, and/or hospital characteristics. Although many characteristics significantly predicted outcomes, the largest effect size was cardiac arrest predicting death (odds ratio = 10.1, 95% confidence interval = 8.8-11.7), whereas hospital characteristics (e.g., staffing, accreditation, volume, setting, services) all had lesser effects.

SIGNIFICANCE

Hospital-to-hospital variation explained little variation in studied outcomes. Rather, certain patient characteristics (e.g., cardiac arrest) had greater effects. Interventions to improve outcomes after status epilepticus may be better focused on individual or prehospital factors, rather than at the inpatient systems level.

Association of antiseizure medications and adverse cardiovascular events: A global health federated network analysis

OBJECTIVE

A diagnosis of epilepsy has been associated with adverse cardiovascular events (CEs), but the extent to which antiseizure medications (ASMs) may contribute to this is not well understood. The aim of this study was to compare the risk of adverse CEs associated with ASM in patients with epilepsy (PWE).

METHODS

A retrospective case-control cohort study was conducted using TriNetX, a global health federated network of anonymized patient records. Patients older than 18 years, with a diagnosis of epilepsy (International Classification of Diseases, 10th Revision code G40) and a medication code of carbamazepine, lamotrigine, or valproate were compared. Patients with cardiovascular disease prior to the diagnosis of epilepsy were excluded. Cohorts were 1:1 propensity score matched (PSM) according to age, sex, ethnicity, hypertension, heart failure, atherosclerotic heart disease, atrial and cardiac arrythmias, diabetes, disorders of lipoprotein metabolism, obesity, schizophrenia and bipolar disorder, medications, and epilepsy classification. The primary outcome was a composite of adverse CEs (ischemic stroke, acute ischemic heart disease, and heart failure) at 10 years. Cox regression analyses were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) following 1:1 PSM.

RESULTS

Of 374 950 PWE included; three cohorts were established after PSM: (1) carbamazepine compared to lamotrigine, n = 4722, mean age 37.4 years; (2) valproate compared to lamotrigine, n = 5478, mean age 33.9 years; and (3) valproate compared to carbamazepine, n = 4544, mean age 37.0 years. Carbamazepine and valproate use were associated with significantly higher risk of composite cardiovascular outcome compared to lamotrigine (HR = 1.390, 95% CI = 1.160-1.665 and HR = 1.264, 95% CI = 1.050-1.521, respectively). Valproate was associated with a 10-year higher risk of all-cause death than carbamazepine (HR = 1.226, 95% CI = 1.017-1.478), but risk of other events was not significantly different.

SIGNIFICANCE

Carbamazepine and valproate were associated with increased CE risks compared to lamotrigine. Cardiovascular risk factor monitoring and careful follow-up should be considered for these patients.

Increasing incidence of Parkinson's disease in patients with epilepsy: A Nationwide cohort study

BACKGROUND

Although epilepsy is an uncommon comorbidity of Parkinson's disease (PD), the exact incidence of PD among the patients with epilepsy is not clarified yet.

OBJECTIVES

We aimed to estimate the incidence of PD in patients with epilepsy and explore the association between epilepsy and PD.

METHODS

Epilepsy patients enrolled in the National Health Insurance Service Health Screening Cohort (NHIS-HealS) (2002-2013) between 2003 and 2007 were set up as the experimental group. The major outcome was the occurrence of PD. Non-epilepsy patients were obtained through Propensity Score Matching of 'greedy nearest neighbor' algorithm in 1:1 ratio. The Cox Proportional Hazards model was used to calculate PD incidence and hazard ratio (HR).

RESULTS

A total of 10,510 patients were finally included in the study, which contained 5255 patients in epilepsy and non-epilepsy groups, respectively. During the follow-up period, 85 patients with Parkinson's disease among 5255 patients with epilepsy and 57 patients with Parkinson's disease among 5255 patients without epilepsy occurred. The 10,000 Person-Year (PY), representing the number of PD patients per 10,000 per year, was 21.38 in the epilepsy group and 11.18 in the non-epilepsy group. When all variables were adjusted, it was found that the epilepsy group had a 2.19 times significantly higher risk of developing Parkinson's disease than the control group (The adjusted HR: 2.19 (95% CI, 1.55-3.12)).

CONCLUSION

This study indicates an increased risk of PD in patients with epilepsy. However, further research is needed to prove an exact causal relationship between these two brain disorders.

Healthcare utilization and clinical characteristics of genetic epilepsy in electronic health records

Understanding the clinical characteristics and medical treatment of individuals affected by genetic epilepsies is instrumental in guiding selection for genetic testing, defining the phenotype range of these rare disorders, optimizing patient care pathways and pinpointing unaddressed medical need by quantifying healthcare resource utilization. To date, a matched longitudinal cohort study encompassing the entire spectrum of clinical characteristics and medical treatment from childhood through adolescence has not been performed. We identified individuals with genetic and non-genetic epilepsies and onset at ages 0-5 years by linkage across the Cleveland Clinic Health System. We used natural language processing to extract medical terms and procedures from longitudinal electronic health records and tested for cross-sectional and temporal associations with genetic epilepsy. We implemented a two-stage design: in the discovery cohort, individuals were stratified as being 'likely genetic' or 'non-genetic' by a natural language processing algorithm, and controls did not receive genetic testing. The validation cohort consisted of cases with genetic epilepsy confirmed by manual chart review and an independent set of controls who received negative genetic testing. The discovery and validation cohorts consisted of 503 and 344 individuals with genetic epilepsy and matched controls, respectively. The median age at the first encounter was 0.1 years and 7.9 years at the last encounter, and the mean duration of follow-up was 8.2 years. We extracted 188,295 Unified Medical Language System annotations for statistical analysis across 9659 encounters. Individuals with genetic epilepsy received an earlier epilepsy diagnosis and had more frequent and complex encounters with the healthcare system. Notably, the highest enrichment of encounters compared with the non-genetic groups was found during the transition from paediatric to adult care. Our computational approach could validate established comorbidities of genetic epilepsies, such as behavioural abnormality and intellectual disability. We also revealed novel associations for genitourinary abnormalities (odds ratio 1.91, 95% confidence interval: 1.66-2.20, P = 6.16 × 10-19) linked to a spectrum of underrecognized epilepsy-associated genetic disorders. This case-control study leveraged real-world data to identify novel features associated with the likelihood of a genetic aetiology and quantified the healthcare utilization of genetic epilepsies compared with matched controls. Our results strongly recommend early genetic testing to stratify individuals into specialized care paths, thus improving the clinical management of people with genetic epilepsies.

On the Dependence of the Critical Success Index (CSI) on Prevalence

The critical success index (CSI) is an established metric used in meteorology to verify the accuracy of weather forecasts. It is defined as the ratio of hits to the sum of hits, false alarms, and misses. Translationally, CSI has gained popularity as a unitary outcome measure in various clinical situations where large numbers of true negatives may influence the interpretation of other, more traditional, outcome measures, such as specificity (Spec) and negative predictive value (NPV), or when unified interpretation of positive predictive value (PPV) and sensitivity (Sens) is needed. The derivation of CSI from measures including PPV has prompted questions as to whether and how CSI values may vary with disease prevalence (P), just as PPV estimates are dependent on P, and hence whether CSI values are generalizable between studies with differing prevalences. As no detailed study of the relation of CSI to prevalence has been undertaken hitherto, the dataset of a previously published test accuracy study of a cognitive screening instrument was interrogated to address this question. Three different methods were used to examine the change in CSI across a range of prevalences, using both the Bayes formula and equations directly relating CSI to Sens, PPV, P, and the test threshold (Q). These approaches showed that, as expected, CSI does vary with prevalence, but the dependence differs according to the method of calculation that is adopted. Bayesian rescaling of both Sens and PPV generates a concave curve, suggesting that CSI will be maximal at a particular prevalence, which may vary according to the particular dataset.

Epilepsy and the risk of adverse cardiovascular events: A nationwide cohort study

BACKGROUND AND PURPOSE

Epilepsy is associated with higher morbidity and mortality compared to people without epilepsy. We performed a retrospective cross-sectional and longitudinal cohort study to evaluate cardiovascular comorbidity and incident vascular events in people with epilepsy (PWE).

METHODS

Data were extracted from the French Hospital National Database. PWE (n = 682,349) who were hospitalized between January 2014 and December 2022 were matched on age, sex, and year of hospitalization with 682,349 patients without epilepsy. Follow-up was conducted from the date of first hospitalization with epilepsy until the date of each outcome or date of last news in the absence of the outcome. Primary outcome was the incidence of all-cause death, cardiovascular death, myocardial infarction, hospitalization for heart failure, ischaemic stroke (IS), new onset atrial fibrillation, sustained ventricular tachycardia or fibrillation (VT/VF), and cardiac arrest.

RESULTS

A diagnosis of epilepsy was associated with higher numbers of cardiovascular risk factors and adverse cardiovascular events compared to controls. People with epilepsy had a higher incidence of all-cause death (incidence rate ratio [IRR] = 2.69, 95% confidence interval [CI] = 2.67-2.72), cardiovascular death (IRR = 2.16, 95% CI = 2.11-2.20), heart failure (IRR = 1.26, 95% CI = 1.25-1.28), IS (IRR = 2.08, 95% CI = 2.04-2.13), VT/VF (IRR = 1.10, 95% CI = 1.04-1.16), and cardiac arrest (IRR = 2.12, 95% CI = 2.04-2.20). When accounting for all-cause death as a competing risk, subdistribution hazard ratios for ischaemic stroke of 1.59 (95% CI = 1.55-1.63) and for cardiac arrest of 1.73 (95% CI = 1.58-1.89) demonstrated higher risk in PWE.

CONCLUSIONS

The prevalence and incident rates of cardiovascular outcomes were significantly higher in PWE. Targeting cardiovascular health could help reduce excess morbidity and mortality in PWE.

Comparing the efficacy of anti-seizure medications using matched cohorts on a large insurance claims database

Epilepsy is a severe chronic neurological disease affecting 60 million people worldwide. Primary treatment is with anti-seizure medicines (ASMs), but many patients continue to experience seizures. We used retrospective insurance claims data on 280,587 patients with uncontrolled epilepsy (UE), defined as status epilepticus, need for a rescue medicine, or admission or emergency visit for an epilepsy code. We conducted a computational risk ratio analysis between pairs of ASMs using a causal inference method, in order to match 1034 clinical factors and simulate randomization. Data was extracted from the MarketScan insurance claims Research Database records from 2011 to 2015. The cohort consisted of individuals over 18 years old with a diagnosis of epilepsy who took one of eight ASMs and had more than a year of history prior to the filling of the drug prescription. Seven ASM exposures were analyzed: topiramate, phenytoin, levetiracetam, gabapentin, lamotrigine, valproate, and carbamazepine or oxcarbazepine (treated as the same exposure). We calculated the risk ratio of UE between pairs of ASM after controlling for bias with inverse propensity weighting applied to 1034 factors, such as demographics, confounding illnesses, non-epileptic conditions treated by ASMs, etc. All ASMs exhibited a significant reduction in the prevalence of UE, but three drugs showed pair-wise differences compared to other ASMs. Topiramate consistently was associated with a lower risk of UE, with a mean risk ratio range of 0.68-0.93 (average 0.82, CI: 0.56-1.08). Phenytoin and levetiracetam were consistently associated with a higher risk of UE with mean risk ratio ranges of 1.11 to 1.47 (average 1.13, CI 0.98-1.65) and 1.15 to 1.43 (average 1.2, CI 0.72-1.69), respectively. Large-scale retrospective insurance claims data - combined with causal inference analysis - provides an opportunity to compare the effect of treatments in real-world data in populations 1,000-fold larger than those in typical randomized trials. Our causal analysis identified the clinically unexpected finding of topiramate as being associated with a lower risk of UE; and phenytoin and levetiracetam as associated with a higher risk of UE (compared to other studied drugs, not to baseline). However, we note that our data set for this study only used insurance claims events, which does not comprise actual seizure frequencies, nor a clear picture of side effects. Our results do not advocate for any change in practice but demonstrate that conclusions from large databases may differ from and supplement those of randomized trials and clinical practice and therefore may guide further investigation.

Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research

Objectives: Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of "real-world" patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. Methods: We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Results: Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. Conclusions: The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.

Critical success index or F measure to validate the accuracy of administrative healthcare data identifying epilepsy in deceased adults in Scotland

BACKGROUND

Methods to undertake diagnostic accuracy studies of administrative epilepsy data are challenged by lack of a way to reliably rank case-ascertainment algorithms in order of their accuracy. This is because it is difficult to know how to prioritise positive predictive value (PPV) and sensitivity (Sens). Large numbers of true negative (TN) instances frequently found in epilepsy studies make it difficult to discriminate algorithm accuracy on the basis of negative predictive value (NPV) and specificity (Spec) as these become inflated (usually >90%). This study demonstrates the complementary value of using weather forecasting or machine learning metrics critical success index (CSI) or F measure, respectively, as unitary metrics combining PPV and sensitivity. We reanalyse data published in a diagnostic accuracy study of administrative epilepsy mortality data in Scotland.

METHOD

CSI was calculated as 1/[(1/PPV) + (1/Sens) - 1]. F measure was calculated as 2.PPV.Sens/(PPV + Sens). CSI and F values range from 0 to 1, interpreted as 0 = inaccurate prediction and 1 = perfect accuracy. The published algorithms were reanalysed using these and their accuracy re-ranked according to CSI in order to allow comparison to the original rankings.

RESULTS

CSI scores were conservative (range 0.02-0.826), always less than or equal to the lower of the corresponding PPV (range 39-100%) and sensitivity (range 2-93%). F values were less conservative (range 0.039-0.905), sometimes higher than either PPV or sensitivity, but were always higher than CSI. Low CSI and F values occurred when there was a large difference between PPV and sensitivity, e.g. CSI was 0.02 and F was 0.039 in an instance when PPV was 100% and sensitivity was 2%. Algorithms with both high PPV and sensitivity performed best in terms of CSI and F measure, e.g. CSI was 0.826 and F was 0.905 in an instance when PPV was 90% and sensitivity was 91%.

CONCLUSION

CSI or F measure can combine PPV and sensitivity values into a convenient single metric that is easier to interpret and rank in terms of diagnostic accuracy than trying to rank diagnostic accuracy according to the two measures themselves. CSI or F prioritise instances where both PPV and sensitivity are high over instances where there are large differences between PPV and sensitivity (even if one of these is very high), allowing diagnostic accuracy thresholds based on combined PPV and sensitivity to be determined. Therefore, CSI or F measures may be helpful complementary metrics to report alongside PPV and sensitivity in diagnostic accuracy studies of administrative epilepsy data.

Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study

BACKGROUND

The evaluation and management of first-time seizure-like events in children can be difficult because these episodes are not always directly observed and might be epileptic seizures or other conditions (seizure mimics). We aimed to evaluate whether machine learning models using real-world data could predict seizure recurrence after an initial seizure-like event.

METHODS

This retrospective cohort study compared models trained and evaluated on two separate datasets between Jan 1, 2010, and Jan 1, 2020: electronic medical records (EMRs) at Boston Children's Hospital and de-identified, patient-level, administrative claims data from the IBM MarketScan research database. The study population comprised patients with an initial diagnosis of either epilepsy or convulsions before the age of 21 years, based on International Classification of Diseases, Clinical Modification (ICD-CM) codes. We compared machine learning-based predictive modelling using structured data (logistic regression and XGBoost) with emerging techniques in natural language processing by use of large language models.

FINDINGS

The primary cohort comprised 14 021 patients at Boston Children's Hospital matching inclusion criteria with an initial seizure-like event and the comparison cohort comprised 15 062 patients within the IBM MarketScan research database. Seizure recurrence based on a composite expert-derived definition occurred in 57% of patients at Boston Children's Hospital and 63% of patients within IBM MarketScan. Large language models with additional domain-specific and location-specific pre-training on patients excluded from the study (F1-score 0·826 [95% CI 0·817-0·835], AUC 0·897 [95% CI 0·875-0·913]) performed best. All large language models, including the base model without additional pre-training (F1-score 0·739 [95% CI 0·738-0·741], AUROC 0·846 [95% CI 0·826-0·861]) outperformed models trained with structured data. With structured data only, XGBoost outperformed logistic regression and XGBoost models trained with the Boston Children's Hospital EMR (logistic regression: F1-score 0·650 [95% CI 0·643-0·657], AUC 0·694 [95% CI 0·685-0·705], XGBoost: F1-score 0·679 [0·676-0·683], AUC 0·725 [0·717-0·734]) performed similarly to models trained on the IBM MarketScan database (logistic regression: F1-score 0·596 [0·590-0·601], AUC 0·670 [0·664-0·675], XGBoost: F1-score 0·678 [0·668-0·687], AUC 0·710 [0·703-0·714]).

INTERPRETATION

Physician's clinical notes about an initial seizure-like event include substantial signals for prediction of seizure recurrence, and additional domain-specific and location-specific pre-training can significantly improve the performance of clinical large language models, even for specialised cohorts.

FUNDING

UCB, National Institute of Neurological Disorders and Stroke (US National Institutes of Health).

Lamotrigine and exogenous estrogen among females with epilepsy: A retrospective analysis of administrative claims data

OBJECTIVE

Exogenous estrogen reduces lamotrigine serum concentrations. Little is known about whether providers adjust lamotrigine doses for addition of exogenous estrogen among people with epilepsy, despite expert recommendations. We determined the incidence of dose increases in lamotrigine following incident prescription of estrogen among females with epilepsy (FWE) in claims data.

METHODS

We used Optum's de-identified Clinformatics® Data Mart Database to create a cohort of U.S. FWE prescribed lamotrigine at a stable dose, with a subsequent prescription for estrogen from 2011 to 2021. We calculated cumulative incidence functions of dose increases in lamotrigine following prescription of exogenous estrogen. We performed a Cox proportional hazards model for multiple candidate predictors of a lamotrigine dose increase.

RESULTS

The cohort included 643 FWE, with median age of 31 (interquartile ratio [IQR] 20-42). The cumulative incidence of any lamotrigine increase was 28% (95% confidence interval [CI] 25%-32%). The median number of days after the first estrogen fill until the first lamotrigine adjustment was 118 (IQR 48-188). In unadjusted Cox models, older age, use of estrogen in hormone replacement therapy as opposed to contraception, and annual household income of $50,000-$99,999 (compared with <$50,000) were significant negative predictors of a dose adjustment in lamotrigine with hazard ratios (HRs) of 0.82 (95% CI 0.72-0.92), 0.63 (95% CI 0.42-0.95), and 0.62 (95% CI 0.40-0.95). In the adjusted Cox model, age and income remained significant predictors with HRs of 0.79 (95% CI 0.66-0.94) and 0.59 (95% CI 0.36-0.95).

CONCLUSION

Dose increase of lamotrigine following addition of exogenous estrogen is rare among U.S. FWE, with potential disparities based on age and income level. More guidance may be needed for providers on this topic.

John M, Taylor SC, Krishnaswamy G, Milinovich A, Aziz PF, Pestana-Knight E, Lal D. Natural language processing and expert follow-up establishes tachycardia association with CDKL5 deficiency disorder

Purpose

CDKL5 deficiency disorder (CDD) is a developmental and epileptic encephalopathy with multisystemic comorbidities. Cardiovascular involvement in CDD was shown in animal models but is yet poorly described in CDD cohorts.

Methods

We identified 38 individuals with genetically confirmed CDD through the Cleveland Clinic CDD specialty clinic and matched 190 individuals with non-genetic epilepsy to them as a comparison group. Natural language processing was applied to yield Human Phenotype Ontology (HPO) terms from medical records. We conducted HPO association testing and manual chart review to explore cardiovascular comorbidities associated with CDD.

Results

We extracted 243,541 HPO terms from 30,512 medical encounters. Phenome-wide analysis confirmed well-established CDD phenotypes and identified association of tachycardia with CDD (Odds ratio 4.2, 95% confidence interval (CI) 1.75-9.93, P adj < .001). We found a 99.6-fold enrichment of supraventricular tachycardia (SVT) in CDD encounter notes (P adj < .001), which led to identification of 2 cases of fetal/neonatal onset SVT previously undescribed in CDD. Tachycardia in CDD individuals was associated with the presence of other autonomic symptoms (Odds ratio 5.63, 95% CI 1.08-40.3, P = .038).

Conclusion

CDD is associated with tachycardia, potentially including early-onset SVT. Alongside prospective validation studies, semiautomated genotype-phenotype analysis with matched controls is a scalable, rapid, and efficient approach for validating known and identifying novel phenotype associations.

Epilepsy hospitalizations and mental disorders: A Portuguese population-based observational retrospective study (2008-2015)

BACKGROUND

Psychiatric comorbidities are highly frequent in people with epilepsy and were found to be markers of poorer prognosis. These comorbidities increase the use of healthcare resources, including emergency department visits and inpatient care. Despite this, there is little information on healthcare utilization associated with a wide range of comorbid mental disorders in people with epilepsy (PWE).

OBJECTIVE

To characterize registered mental disorders among all hospitalizations with a primary diagnosis of epilepsy and to analyze their association with crucial hospitalization outcomes.

METHODS

An observational retrospective study was performed using administrative data from hospitalization episodes with epilepsy as the primary diagnosis discharged between 2008 and 2015. Mental disorder categories 650 to 670 from Clinical Classification Software were selected as secondary diagnoses. Mann-Whitney U, Kruskall-Wallis, and Chi-squared tests were used to establish comparisons. For each episode, data regarding hospitalization outcomes was retrieved, including length of stay (LoS), in-hospital mortality (IHM), 8-year period readmissions, and total estimated charges.

RESULTS

Overall, 27,785 hospitalizations were analyzed and 33.9% had registered mental disorders, with alcohol-related disorders being the most prevalent (11.7%). For episodes with a concomitant register of a mental disorder, LoS was significantly longer (5.0 vs. 4.0 days, P <0.001), and IHM was higher (2.8% vs. 2.2%, P <0.001), as were readmissions (25.5% vs. 23.7%, P <0.001), and median episodes' charges (1,578.7 vs. 1,324.4 euros, P <0.001).

CONCLUSION

Epilepsy-related hospitalizations with registered mental disorders heightened the utilization of healthcare resources, stressing the importance of diagnosing and treating mental disorders in PWE.

Epilepsy-related mortality during the COVID-19 pandemic: A nationwide study of routine Scottish data

OBJECTIVE

To examine whether epilepsy-related deaths increased during the COVID-19 pandemic and if the proportion with COVID-19 listed as the underlying cause is different between people experiencing epilepsy-related deaths and those experiencing deaths unrelated to epilepsy.

METHODS

This was a Scotland-wide, population-based, cross-sectional study of routinely-collected mortality data pertaining to March-August of 2020 (COVID-19 pandemic peak) compared to the corresponding periods in 2015-2019. ICD-10-coded causes of death of deceased people of any age were obtained from a national mortality registry of death certificates in order to identify those experiencing epilepsy-related deaths (coded G40-41), deaths with COVID-19 listed as a cause (coded U07.1-07.2), and deaths unrelated to epilepsy (death without G40-41 coded). The number of epilepsy-related deaths in 2020 were compared to the mean observed through 2015-2019 on an autoregressive integrated moving average (ARIMA) model (overall, men, women). Proportionate mortality and odds ratios (OR) for deaths with COVID-19 listed as the underlying cause were determined for the epilepsy-related deaths compared to deaths unrelated to epilepsy, reporting 95% confidence intervals (CIs).

RESULTS

A mean number of 164 epilepsy-related deaths occurred through March-August of 2015-2019 (of which a mean of 71 were in women and 93 in men). There were subsequently 189 epilepsy-related deaths during the pandemic March-August 2020 (89 women, 100 men). This was 25 more epilepsy-related deaths (18 women, 7 men) compared to the mean through 2015-2019. The increase in women was beyond the mean year-to-year variation seen in 2015-2019. Proportionate mortality with COVID-19 listed as the underlying cause was similar between people experiencing epilepsy-related deaths (21/189, 11.1%, CI 7.0-16.5%) and deaths unrelated to epilepsy (3,879/27,428, 14.1%, CI 13.7-14.6%), OR 0.76 (CI 0.48-1.20). Ten of 18 excess epilepsy-related deaths in women had COVID-19 listed as an additional cause.

CONCLUSIONS

There is little evidence to suggest there have been any major increases in epilepsy-related deaths in Scotland during the COVID-19 pandemic. COVID-19 is a common underlying cause of both epilepsy-related and unrelated deaths.

Selection and Continuation of Antiseizure Medication in Children With Epilepsy in Sweden From 2007 to 2020

BACKGROUND

Knowledge on antiseizure medication (ASM) use and retention for children with epilepsy is limited, partly because of extensive off-label use of newer drugs with limited registration. We used prescription data to study prescription patterns on a population-wide scale and compared the proportion of patients remaining on monotherapy of ASMs with and without formal indication for different age groups.

METHODS

A total of 14,681 individuals aged <18 years were included, using cross-referenced Swedish registers from 2007 to 2020. Kaplan-Meier retention rates were calculated for all ASMs. The most common pathways of the first three medications per patient were analyzed.

RESULTS

In children older than one month and up to age one year, monotherapy retention rates were the highest for oxcarbazepine, valproic acid, and carbamazepine. Among children aged one to five years, oxcarbazepine and levetiracetam were among ASMs that do not have a monotherapy indication in Sweden but still had high retention rates. In the age group five to 12 years, lamotrigine and oxcarbazepine had the highest retention rate. In males aged 12 to 18 years, valproic acid was the most common choice followed by lamotrigine, whereas lamotrigine was the first choice of ASM for females, exceeding the second and third most common options levetiracetam and oxcarbazepine by a factor of two and three, respectively.

CONCLUSION

Off-label medication is common in children with epilepsy but does not seem to be associated with lower retention. The restrictions regarding valproic acid for females of childbearing age seem to have been well implemented in Swedish neuropediatric care.

Identification of patients with epilepsy using automated electronic health records phenotyping

OBJECTIVE

Unstructured data present in electronic health records (EHR) are a rich source of medical information; however, their abstraction is labor intensive. Automated EHR phenotyping (AEP) can reduce the need for manual chart review. We present an AEP model that is designed to automatically identify patients diagnosed with epilepsy.

METHODS

The ground truth for model training and evaluation was captured from a combination of structured questionnaires filled out by physicians for a subset of patients and manual chart review using customized software. Modeling features included indicators of the presence of keywords and phrases in unstructured clinical notes, prescriptions for antiseizure medications (ASMs), International Classification of Diseases (ICD) codes for seizures and epilepsy, number of ASMs and epilepsy-related ICD codes, age, and sex. Data were randomly divided into training (70%) and hold-out testing (30%) sets, with distinct patients in each set. We trained regularized logistic regression and an extreme gradient boosting models. Model performance was measured using area under the receiver operating curve (AUROC) and area under the precision-recall curve (AUPRC), with 95% confidence intervals (CI) estimated via bootstrapping.

RESULTS

Our study cohort included 3903 adults drawn from outpatient departments of nine hospitals between February 2015 and June 2022 (mean age = 47 ± 18 years, 57% women, 82% White, 84% non-Hispanic, 70% with epilepsy). The final models included 285 features, including 246 keywords and phrases captured from 8415 encounters. Both models achieved AUROC and AUPRC of 1 (95% CI = .99-1.00) in the hold-out testing set.

SIGNIFICANCE

A machine learning-based AEP approach accurately identifies patients with epilepsy from notes, ICD codes, and ASMs. This model can enable large-scale epilepsy research using EHR databases.

Premature Mortality and Causes of Death Among People With Epilepsy: A Nationwide Population-Based Incident Cohort Study

BACKGROUND AND OBJECTIVES

People with epilepsy (PWE) are at risk of premature death with considerable variability according to the study population. We aimed to estimate the risk and causes of death in PWE according to age, disease severity, disease course, comorbidities, and socioeconomic status in Korea.

METHODS

We conducted a nationwide population-based retrospective cohort study using the National Health Insurance database linked with the national death register. Newly treated PWE from 2008 to 2016 who were identified by antiseizure medication (ASM) prescriptions and diagnostic codes for epilepsy/seizure were included and observed until 2017. We assessed all-cause and cause-specific crude mortality rates and standardized mortality ratios (SMRs).

RESULTS

Among 138,998 PWE, 20,095 deaths were identified, and the mean follow-up period was 4.79 years. The SMR was 2.25 in the overall group of PWE, with a higher value in the younger age group at diagnosis and a shorter time interval after diagnosis. The SMR in the monotherapy group was 1.56, while that in the group with 4 or more ASMs was 4.93. PWE without any comorbidities had an SMR of 1.61. PWE who were rural residents had a higher SMR than those who were urban residents (2.47 vs 2.03, respectively). The causes of death among PWE were cerebrovascular disease (18.9%, SMR 4.50), malignant neoplasms outside the CNS (15.7%, SMR 1.37), malignant neoplasms of the CNS (6.7%, SMR 46.95), pneumonia (6.0%, SMR 2.08), and external causes (7.2%, SMR 2.17), including suicide (2.6%, SMR 2.07). Epilepsy itself and status epilepticus accounted for 1.9% of the overall death. The excess mortality associated with pneumonia and external causes was persistently high, whereas the excess mortality associated with malignancy and cerebrovascular diseases tended to decrease with increasing time since diagnosis.

DISCUSSION

This study showed excess mortality in PWE, even in those without comorbidities and those receiving monotherapy. Regional disparities and sustained risks of deaths from external causes over 10 years imply potential points of intervention. In addition to active control of seizures, education about injury prevention, monitoring for suicidal ideation, and efforts to improve accessibility to epilepsy care are all required to reduce mortality.

Comparison of Perinatal Outcomes for Women With and Without Epilepsy: A Systematic Review and Meta-analysis

Importance

Pregnant women who have epilepsy need adequate engagement, information, and pregnancy planning and management to improve pregnancy outcomes.

Objective

To investigate perinatal outcomes in women with epilepsy compared with women without epilepsy.

Data Sources

Ovid MEDLINE, Embase, CINAHL, and PsycINFO were searched with no language or date restrictions (database inception through December 6, 2022). Searches also included OpenGrey and Google Scholar and manual searching in journals and reference lists of included studies.

Study Selection

All observational studies comparing women with and without epilepsy were included.

Data Extraction and Synthesis

The PRISMA checklist was used for abstracting data and the Newcastle-Ottawa Scale for risk-of-bias assessment. Data extraction and risk-of-bias assessment were done independently by 2 authors with mediation conducted independently by a third author. Pooled unadjusted odds ratios (OR) or mean differences were reported with 95% CI from random-effects (I2 heterogeneity statistic >50%) or fixed-effects (I2 < 50%) meta-analyses.

Main Outcomes and Measures

Maternal, fetal, and neonatal complications.

Results

Of 8313 articles identified, 76 were included in the meta-analyses. Women with epilepsy had increased odds of miscarriage (12 articles, 25 478 pregnancies; OR, 1.62; 95% CI, 1.15-2.29), stillbirth (20 articles, 28 134 229 pregnancies; OR, 1.37; 95% CI, 1.29-1.47), preterm birth (37 articles, 29 268 866 pregnancies; OR, 1.41; 95% CI, 1.32-1.51) and maternal death (4 articles, 23 288 083 pregnancies; OR, 5.00; 95% CI, 1.38-18.04). Neonates born to women with epilepsy had increased odds of congenital conditions (29 articles, 24 238 334 pregnancies; OR, 1.88; 95% CI, 1.66-2.12), neonatal intensive care unit admission (8 articles, 1 204 428 pregnancies; OR, 1.99; 95% CI, 1.58-2.51), and neonatal or infant death (13 articles, 1 426 692 pregnancies; OR, 1.87; 95% CI, 1.56-2.24). The increased odds of poor outcomes was increased with greater use of antiseizure medication.

Conclusions and Relevance

This systematic review and meta-analysis found that women with epilepsy have worse perinatal outcomes compared with women without epilepsy. Women with epilepsy should receive pregnancy counseling from an epilepsy specialist who can also optimize their antiseizure medication regimen before and during pregnancy.

Risk of major congenital malformations associated with first-trimester antihypertensives, including amlodipine and methyldopa: A large claims database study 2010-2019

OBJECTIVES

To evaluate the major congenital malformation (MCM) risk of first-trimester antihypertensive exposure, specifically of amlodipine and methyldopa.

STUDY DESIGN

A large administrative claims database was used.

MAIN OUTCOME MEASURES

The prevalence of antihypertensive prescriptions during pregnancy was described in 91,390 women giving birth between 2010 and 2019. The MCM risk of first-trimester antihypertensives was evaluated in 1,185 women diagnosed with hypertensive disorders in the first trimester. The MCM risk of first-trimester amlodipine and methyldopa was evaluated in 178 women who were prescribed antihypertensives in the first trimester.

RESULTS

Antihypertensives were prescribed to 278 (0.30%) women during their first trimester. The prescription prevalence in the first trimester was highest for methyldopa (115, 0.13%), followed by amlodipine (55, 0.06%). Antihypertensives were prescribed to 2,955 (3.23%) women during pregnancy. Nifedipine (903, 0.99%) and nicardipine (758, 0.83%) were the most frequently prescribed oral and injectable antihypertensives during pregnancy, both with a significant increase in annual prevalence. Of the 1,185 women diagnosed with hypertensive disorders in the first trimester, antihypertensives were prescribed to 178 women. The adjusted odds ratio (aOR) of MCMs in the first-trimester prescription of any antihypertensive medication was 1.124 (95% confidence interval [CI], 0.618-2.045). Amlodipine and methyldopa were prescribed to 44 and 93 of the 178 women, respectively. The aORs of MCMs in the first-trimester prescription of amlodipine and methyldopa were 1.219 (95% CI, 0.400-3.721) and 0.921 (0.331-2.564), respectively.

CONCLUSIONS

The MCM risk of first-trimester exposure to antihypertensives, including amlodipine and methyldopa, was not suggested.

Long-term risk of seizure after posterior reversible encephalopathy syndrome

OBJECTIVE

Patients with posterior reversible encephalopathy syndrome (PRES) can develop seizures during the acute phase. We sought to determine the long-term risk of seizure after PRES.

METHODS

We performed a retrospective cohort study using statewide all-payer claims data from 2016-2018 from nonfederal hospitals in 11 US states. Adults admitted with PRES were compared to adults admitted with stroke, an acute cerebrovascular disorder associated with long-term risk of seizure. The primary outcome was seizure diagnosed during an emergency room visit or hospital admission after the index hospitalization. The secondary outcome was status epilepticus. Diagnoses were determined using previously validated ICD-10-CM codes. Patients with seizure diagnoses before or during the index admission were excluded. We used Cox regression to evaluate the association of PRES with seizure, adjusting for demographics and potential confounders.

RESULTS

We identified 2095 patients hospitalized with PRES and 341,809 with stroke. Median follow-up was 0.9 years (IQR, 0.3-1.7) in the PRES group and 1.0 years (IQR, 0.4-1.8) in the stroke group. Crude seizure incidence per 100 person-years was 9.5 after PRES and 2.5 after stroke. After adjustment for demographics and comorbidities, patients with PRES had a higher risk of seizure than patients with stroke (HR, 2.9; 95% CI, 2.6-3.4). Results were unchanged in a sensitivity analysis that applied a two-week washout period to mitigate detection bias. A similar relationship was observed for the secondary outcome of status epilepticus.

INTERPRETATION

PRES was associated with an increased long-term risk of subsequent acute care utilization for seizure compared to stroke.

Risk of poststroke epilepsy after reperfusion therapies: A national cohort study

BACKGROUND AND PURPOSE

The risk of poststroke epilepsy (PSE) after endovascular treatment (EVT) is not well characterized. In this nationwide study, we assessed the risk of PSE after EVT and identified associated predictors.

METHODS

We included all individuals (n = 3319) treated with EVT (±intravenous thrombolysis [IVT]) between 2015 and 2019 in the Swedish National Quality Register for EVT. Two control groups were identified from the Swedish Stroke Register: the first treated with IVT alone (n = 3132) and the second with no treatment (n = 3184), both matched for age, sex, stroke severity, and time of stroke.

RESULTS

PSE developed in 7.9% (n = 410). The survival-adjusted 2-year risk was 6.5% (95% confidence interval [CI] = 5.28-7.70) after EVT, 10.0% (95% CI = 8.25-11.75) after IVT, and 12.3% after no revascularization (95% CI = 10.33-14.25). The hazard ratio (HR) of PSE after EVT was almost half compared to no treatment (HR = 0.51, 95% CI = 0.41-0.64). The risk of PSE after EVT was lower compared to no treatment in a multivariable Cox model that adjusted for age, sex, hemicraniectomy, and stroke severity (HR = 0.76, 95% CI = 0.60-0.96). Multivariable predictors of PSE after EVT were large infarction on computed tomography Day 1, high posttreatment National Institutes of Health Stroke Scale score, and need of assistance 3 months after stroke. IVT before EVT was associated with a lower risk of PSE (HR = 0.66, 95% CI = 0.46-0.94).

CONCLUSIONS

This nationwide study identified a reduced risk of PSE after EVT. Markers of severe infarction after EVT were associated with PSE, whereas IVT given before EVT was protective.

No association between major congenital malformations and exposure to Kampo medicines containing rhubarb rhizome: A Japanese database study

Traditional Japanese (Kampo) medicines containing rhubarb rhizome are prescribed for constipation during pregnancy; however, detailed safety information of their use for pregnant women is lacking. The aim of current study was to clarify the association between prescription Kampo-containing rhubarb rhizome (KRR) in the first trimester of pregnancy and congenital malformations in newborns. Using a large Japanese health insurance claims database, we included pregnant women who enrolled the same health insurance society from 3 months before pregnancy to the delivery date, who gave birth between 2010 and 2019, and those with data related to their infants. Pregnant women who were prescribed magnesium oxide (MgO), commonly used for constipation, during the first trimester of pregnancy and their infants were extracted as controls. Associations between KRR prescribed in the first pregnancy trimester and major congenital malformations (MCM) in the infants were examined using multivariate logistic regression analysis. Of 75,398 infants, 4,607 (6.1%) were diagnosed with MCMs within the first year after birth. Furthermore, 9,852 infants were born to women prescribed MgO, among whom 680 (6.9%) had MCMs; 450 infants were born to women prescribed KRR, among whom 28 (6.2%) had MCMs. Multivariate logistic regression analysis identified no difference in MCM risk between the two types of prescriptions [crude odds ratio (OR) 0.895, 95% confidence interval (CI) 0.606-1.322, adjusted OR 0.889, 95% CI 0.599-1.320]. In conclusion, the risk of MCMs did not differ between those prescribed KRR or MgO in the first trimester of pregnancy.

Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study

BACKGROUND

For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal.

METHODS

This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions.

RESULTS

Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44).

CONCLUSIONS

Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate.

Psychiatric comorbidities and all-cause mortality in epilepsy: A nationwide cohort study

Background

People with epilepsy (PWE) having comorbid psychiatric conditions may be at greater risk of death. We aimed to determine the association between psychiatric disorders and all-cause mortality among PWE after adjustment for somatic comorbidities.

Methods

Based on data from the National Health Insurance Fund, a Cox survival analysis was done within a retrospective open cohort of all PWE (≥12 years) in Lithuania between January 2014 and June 2020. Cox models comparing mortality between PWE with or without psychiatric comorbidities were adjusted for sex, age, hospitalizations, and the epilepsy-specific comorbidity index.

Results

Of 47,964 PWE (age Md = 49, IQR = 34–62 years, 60.3% male, follow-up Md = 4.4, IQR = 2.1–6.1 years), 10,290 (21.5%) died during the study. The diagnosis of any psychiatric disorder (n = 26,137, 54.5%) was associated with increased mortality when adjusted for only sex and age (HR = 1.13, 95% CI = 1.09 to 1.18). After including the epilepsy-specific comorbidity index, the number of hospitalizations and hospital days in the analysis, only self-harm (HR = 1.55, 95% CI = 1.40 to 1.71) and substance use disorders (HR = 1.39 95% CI = 1.32 to 1.47), but not any psychiatric comorbidities (HR = 0.92 95% CI = 0.88 to 0.96) were related to elevated all-cause mortality. Mood, anxiety and behavioral disorders were associated with lower odds of mortality; however, they were rarely documented.

Conclusions

Our results suggest that psychiatric comorbidities increase all-cause mortality among PWE through their association with coexisting somatic conditions as only substance use disorders and self-harm were independently related to elevated all-cause mortality. Future clinical interview-based studies should explore the relationship between mortality in epilepsy and psychiatric comorbidities while adjusting for somatic comorbidities.

Cognitive disorders in childhood epilepsy: a comparative longitudinal study using administrative healthcare data

OBJECTIVE

The study aimed to assess the risk of cognitive impairment in patients with epilepsy, the impact of age of epilepsy onset on cognition and the temporal relationship of epilepsy onset and intellectual impairment.

METHODS

This longitudinal study analyzed birth cohorts and followed-up children born 2005-2007 up to the age of ten using administrative healthcare data of about 8.9 million members insured by the statutory health insurance "BARMER" in Germany. We compared prevalence of cognitive impairment (ICD-code F7*) in children with epilepsy (ICD-code G40) to controls, and calculated relative risks by age groups at onset of epilepsy and assessed differences in relation to the temporal sequence of the diagnoses.

RESULTS

Of the 142,563 pre-pubertal children included in the analysis, 2728 (1.9%) had an epilepsy diagnosis within the first 10 years of life. 17.4% (475/2728) of children with epilepsy had a diagnosis of cognitive impairment compared to 1.7% (2309/139835) in controls. The relative risk for cognitive impairment compared to age-matched controls was 10.5 (95% CI 9.6, 11.6) and was highest in epilepsy cases with seizure manifestation within the first 2 years of life compared to older children. The prevalence of cognitive impairment before epilepsy diagnosis was slightly increased compared to controls, while it was increased by a factor of nine in children diagnosed with cognitive impairment in the year of onset of epilepsy or afterwards.

CONCLUSIONS

Pre-pubertal children with epilepsy have a ten-fold higher risk for intellectual impairment compared to age-matched controls. This risk inversely correlates with the age of epilepsy manifestation. Cognitive impairment was diagnosed after epilepsy manifestation in the majority of patients.

Antiseizure medication treatment pathways for US Medicare beneficiaries with newly treated epilepsy

OBJECTIVE

This study was undertaken to characterize antiseizure medication (ASM) treatment pathways in Medicare beneficiaries with newly treated epilepsy.

METHODS

This was a retrospective cohort study using Medicare claims. Medicare is the United States' federal health insurance program for people aged 65 years and older plus younger people with disabilities or end-stage renal disease. We included beneficiaries with newly treated epilepsy (International Classification of Diseases codes for epilepsy/convulsions 2014-2017, no ASM in the previous 2 years). We displayed the sequence of ASM fills using sunburst plots overall, then stratified by mood disorder, age, and neurologist prescriber. We tabulated drug costs for each pathway.

RESULTS

We included 21 458 beneficiaries. Levetiracetam comprised the greatest number of pill days (56%), followed by gabapentin (11%) and valproate (8%). There were 22 288 unique treatment pathways. The most common pathways were levetiracetam monotherapy (43%), gabapentin monotherapy (10%), and valproate monotherapy (5%). Gabapentin was the most common second- and third-line ASM. Whereas only 2% of pathways involved first-line lacosamide, those pathways accounted for 19% of cost. Gabapentin and valproate use was increased and levetiracetam use was decreased in beneficiaries with mood disorders compared to beneficiaries without mood disorders. Levetiracetam use was increased and gabapentin, valproate, lamotrigine, and topiramate use was decreased in beneficiaries aged >65 years compared with those aged 65 years or less. Lamotrigine, levetiracetam, and lacosamide use was increased and gabapentin use was decreased in beneficiaries whose initial prescriber was a neurologist compared to those whose prescriber was not a neurologist.

SIGNIFICANCE

Levetiracetam monotherapy was the most common pathway, although substantial heterogeneity existed. Lacosamide accounted for a small percentage of ASMs but a disproportionately large share of cost. Neurologists were more likely to prescribe lamotrigine compared with nonneurologists, and lamotrigine was prescribed far less frequently than may be endorsed by guidelines. Future work may explore patient- and physician-driven factors underlying ASM choices.

Estimates of epilepsy prevalence, psychiatric co-morbidity and cost

PURPOSE

This study estimated epilepsy prevalence, psychiatric co-morbidity and annual costs associated with epilepsy.

METHODS

We used Danish national health registers to identify persons diagnosed with epilepsy and psychiatric disorders, and persons using antiseizure medication and persons using drugs for psychiatric disorders. We calculated the prevalence of epilepsy and co-morbid psychiatric disorders in Denmark on December 31, 2016, using information on epilepsy and psychiatric disorders based on combinations of hospital contacts and use of antiseizure and psychoactive medication. Further, direct and indirect annual costs associated with epilepsy were calculated using individual-level data from a range of socioeconomic registers.

RESULTS

There were 5,044,367 persons alive and living in Denmark on December 31, 2016, including 33,628 persons with at least one hospital contact with epilepsy in the previous five years (epilepsy prevalence 0.67% (0.69% males; 0.65% females)). Among these persons with epilepsy, we identified 12,562 (37.4%) persons with a psychiatric disorder or use of drugs used for psychiatric disorders as compared with 801,052 (15.9%) persons in the general population. The estimated total annual individual net costs associated with epilepsy was €30,683. Compared with prevalence estimates on December 31, 2006, the prevalence of epilepsy on December 31, 2016, was slightly higher in the older population and slightly lower in children CONCLUSIONS: Population estimates from national registers provide epilepsy prevalence estimates of approximately 0.6-0.7% - similar to previous reviews of epilepsy prevalence. In addition, the national sample allowed idenitfication of high prevalence of psychiatric disorders and high societal costs associated with epielspy.

Severity of Epilepsy and Response to Antiseizure Medications in Individuals with Multiple Sclerosis: Analysis of a Real-World Dataset

Background and objectives:

Epilepsy is an important comorbidity that affects outcomes for people with multiple sclerosis (MS). However, it is unclear if seizure severity among individuals with coexistence of multiple sclerosis and epilepsy (MS+E) is higher than in those with other focal epilepsies. Our goal was to compare the overall severity of epilepsy in individuals with MS+E versus those with focal epilepsy without MS (E-MS) as defined by seizure-related healthcare utilization, frequency and duration of status epilepticus, and frequency of antiseizure medication (ASM) regimen changes.

Methods:

In this hypothesis-generating study, we analyzed a U.S. commercial nationwide de-identified claims dataset with > 86 million individuals between 1/1/2008 and 8/31/2019. Using validated algorithms, we identified adults with E-MS and those with MS+E. We compared the number and length of seizure-related hospital admissions, the number of claims and unique days with claims for status epilepticus, and the rates of ASM regimen changes between the MS+E and the E-MS groups.

Results:

During the study period, 66,708 individuals with E-MS and 537 with MS+E had ≥ 2 years of coverage after their initial diagnosis of epilepsy. There was no difference between the MS+E and E-MS groups in the percentage of individuals admitted for seizures and/or status epilepticus. However, MS+E with seizure-related admissions had more admissions and longer hospital stays than those with E-MS. MS+E who experienced status epilepticus had more unique days with status epilepticus claims compared to E-MS. MS+E were more likely to have ASM regimen changes in Year 2 after the initial diagnosis of epilepsy and had more ASM changes during Year 2 compared to E-MS. Among individuals with MS+E, there were no differences in our measures of seizure severity for those treated with sodium channel blockers/modulators versus other ASM classes.

Discussion:

This study supports the notion that individuals with MS+E can have more severe epilepsy than those with E-MS. Seizure severity among individuals with MS+E treated with sodium-channel blockers/modulators versus other ASM classes shows no significant differences.

Classification of evidence:

This study provides Class III evidence that individuals with MS+E can have more severe epilepsy than those with E-MS.