Can machine learning predict late seizures after intracerebral hemorrhages? Evidence from real-world data.

INTRODUCTION: Intracerebral hemorrhage represents 15 % of all strokes and it is associated with a high risk of post-stroke epilepsy. However, there are no reliable methods to accurately predict those at higher risk for developing seizures despite their importance in planning treatments, allocating resources, and advancing post-stroke seizure research. Existing risk models have limitations and have not taken advantage of readily available real-world data and artificial intelligence. This study aims to evaluate the performance of Machine-learning-based models to predict post-stroke seizures at 1 year and 5 years after an intracerebral hemorrhage in unselected patients across multiple healthcare organizations. DESIGN/METHODS: We identified patients with intracerebral hemorrhage (ICH) without a prior diagnosis of seizures from 2015 until inception (11/01/22) in the TriNetX Diamond Network, using the International Classification of Diseases, Tenth Revision (ICD-10) I61 (I61.0, I61.1, I61.2, I61.3, I61.4, I61.5, I61.6, I61.8, and I61.9). The outcome of interest was any ICD-10 diagnosis of seizures (G40/G41) at 1 year and 5 years following the first occurrence of the diagnosis of intracerebral hemorrhage. We applied a conventional logistic regression and a Light Gradient Boosted Machine (LGBM) algorithm, and the performance of the model was assessed using the area under the receiver operating characteristics (AUROC), the area under the precision-recall curve (AUPRC), the F1 statistic, model accuracy, balanced-accuracy, precision, and recall, with and without seizure medication use in the models. RESULTS: A total of 85,679 patients had an ICD-10 code of intracerebral hemorrhage and no prior diagnosis of seizures, constituting our study cohort. Seizures were present in 4.57 % and 6.27 % of patients within 1 and 5 years after ICH, respectively. At 1-year, the AUROC, AUPRC, F1 statistic, accuracy, balanced-accuracy, precision, and recall were respectively 0.7051 (standard error: 0.0132), 0.1143 (0.0068), 0.1479 (0.0055), 0.6708 (0.0076), 0.6491 (0.0114), 0.0839 (0.0032), and 0.6253 (0.0216). Corresponding metrics at 5 years were 0.694 (0.009), 0.1431 (0.0039), 0.1859 (0.0064), 0.6603 (0.0059), 0.6408 (0.0119), 0.1094 (0.0037) and 0.6186 (0.0264). These numerical values indicate that the statistical models fit the data very well. CONCLUSION: Machine learning models applied to electronic health records can improve the prediction of post-hemorrhagic stroke epilepsy, presenting a real opportunity to incorporate risk assessments into clinical decision-making in post-stroke care clinical care and improve patients' selection for post-stroke epilepsy research.

Post-stroke Everything.

PURPOSE OF REVIEW: This review aims at providing updates on selected post-stroke complications. We examined recent advances in diagnosing and treating the following post-stroke complications: cognitive impairment, epilepsy, depression, fatigue, tremors, dysphagia, and pain. RECENT FINDINGS: Advances in understanding the mechanisms of post-stroke complications, in general, are needed despite advances made in understanding, treating, and preventing these complications. There are growing progresses in integrating new tools to diagnose post-stroke cognitive impairment. The potential role of acute stroke reperfusion treatment in post-stroke epilepsy and its impact on other stroke complications is getting more transparent. Post-stroke depression remains underestimated and new tools to diagnose depression after stroke are being developed. New promising pharmacological approaches to treating post-stroke pain are emerging. Tremors related to stroke are poorly understood and under-evaluated, while treatment towards post-stroke dysphagia has benefited from new non-pharmacological to pharmacological approaches. CONCLUSIONS: An integrative approach to stroke complications and collaborations between providers across specialties are more likely to improve stroke outcomes.

Associations of small vessel disease and acute symptomatic seizures in ischemic stroke patients.

BACKGROUND AND PURPOSE: Cerebral microbleeds (CMBs), markers of small vessel disease are frequent in ischemic stroke, yet the association with acute symptomatic seizures (ASS) has not been well characterized. METHODS: A retrospective cohort of hospitalized patients with anterior circulation ischemic stroke. The association of CMBs with acute symptomatic seizures was assessed using a logistic regression model and causal mediation analysis. RESULTS: Of 381 patients, 17 developed seizures. Compared with patients without CMBs, those with CMBs had a three-fold higher unadjusted odds of seizures (unadjusted OR: 3.84, 95% 1.16-12.71, p = 0.027). After adjusting for confounders such as stroke severity, cortical infarct location, and hemorrhagic transformation, the association between CMBs and ASS was attenuated (adjusted OR: 3.11, 95%CI: 0.74-11.03, p = 0.09). The association was not mediated by stroke severity. CONCLUSION: In this cohort of hospitalized patients with anterior circulation ischemic stroke, CMBs were more likely to be found in patients with ASS than those without ASS, an association that was attenuated when accounting for stroke severity, cortical infarct location, and hemorrhagic transformation. Evaluation of the long-term risk of seizures associated with CMBs and other markers of small vessel disease is warranted.

Prevalence and prognosis of seizures among patients undergoing mechanical thrombectomy for acute ischemic stroke: A look at pre-2015 aha/asa guidelines update regarding endovascular treatment.

BACKGROUND: Mechanical Thrombectomy (MT) is standard of care for eligible patients with Acute Ischemic Stroke (AIS) due to large vessel occlusion (LVO). With increasing use of MT, clinicians are more likely to encounter seizures, a potential complication of AIS treated with MT. Tracking future trends in the burden of post-stroke seizure associated with MT will require baseline pre-approval benchmark estimates of its frequency and outcomes. METHODS: All patients with AIS who underwent MT (International Classification of Diseases, Ninth Revision, Clinical Modification; ICD-9-CM procedure code: 39.74) were identified from the National Inpatient Sample (NIS) 2006-2014, using appropriate ICD-9-CM codes. We identified a subset of patients with seizures using ICD-9-CM secondary discharge diagnoses codes 780.3x and 345.x. We computed the rate of seizures overall and across pre-specified demographic, clinical, and healthcare system-related variables. Finally, we assessed the independent association of mortality with seizures using a multivariable logistic regression model. RESULTS: Of 30137 (weighted) patients with AIS who underwent MT, 1,363 (4.5%) had seizures. Patients who had seizures were younger, privately insured, or Medicaid beneficiaries, and frequently died in the hospital. There were no statistically significant differences between the seizures and no-seizures groups by race, sex, IV thrombolysis with recombinant tissue plasminogen activator, length of stay, and the number of medical comorbidities. However, patients who underwent MT and developed seizures had 75% higher odds of in-hospital mortality (adjusted OR 95% CI 1.75; 1.22-2.49). CONCLUSION: In this nationwide sample, prior to the 2015 AHA/ASA guidelines update supporting MT use, seizures occurred in one of twenty patients with AIS treated with MT, and occurrence of seizure was independently associated with a nearly two-fold increase in the odds of in-hospitality death.

Birth prevalence of neural tube defects in eastern Africa: a systematic review and meta-analysis.

BACKGROUND: Neural tube defects (NTDs) are associated with high rates of neonatal mortality and morbidity worldwide. The promotion of folic acid fortification and supplementation in pregnant women by the Food and Drug Administration significantly decreased the incidence of NTDs in the United States. This practice is not widely adopted in Eastern Africa countries. We hypothesized that these countries experience a higher burden of NTDs than countries that promote the use of folic acid. We aimed to estimate the birth prevalence of NTDs in the United Nations (UN) Eastern African region. METHODS: PubMed (Medline), Embase, and Cochrane Library databases were systematically searched from inception to December 17, 2021. We included randomized controlled trials or observational studies that reported the prevalence estimates of NTDs in Eastern Africa. Random effects model was used to pool the effect estimates. The GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach was used to assess the certainty of the evidence. Outcome measures were overall and specific (spina bifida, anencephaly, encephalocele) rates of NTDs per 10,000 births, including live and stillborn cases. RESULTS: The meta-analysis included 20 studies consisting of 752,936 individuals. The pooled prevalence of all NTDs per 10,000 births in Eastern Africa was 33.30 (95% CI: 21.58 to 51.34). Between-study heterogeneity was high (I2 = 97%, p < 0.0001), The rate was highest in Ethiopia (60 per 10,000). Birth prevalence of spina bifida (20 per 10,000) was higher than anencephaly (9 per 10,000) and encephalocele (2.33 per 10,000). No studies on NTDs were identified in 70% of the UN Eastern Africa region. Birth prevalence increased by 4% per year from 1983 to 2018. The level of evidence as qualified with GRADE was moderate. CONCLUSION: The birth prevalence of NTDs in the United Nations region of Eastern Africa is 5 times as high as observed in Western countries with mandatory folic acid supplementation in place. Therefore, mandatory folic acid supplementation of stable foods may decrease the risk of NTDs in Eastern Africa.

The association of multiple chronic conditions and healthcare expenditures among adults with epilepsy in the United States.

RATIONALE: Epilepsy is a frequent neurologic condition with important financial strains on the US healthcare system. The co-occurrence of multiple chronic conditions (MCC) may have additional financial repercussions on this patient population. We aimed to assess the association of coexisting chronic conditions on healthcare expenditures among adult patients with epilepsy. METHODS: We identified a total of 1,942,413 adults (≥18 years) with epilepsy using the clinical classification code 83 from the MEPS-HC (Medical Expenditure Panel Survey Household Component) database between 2003 and 2014. Chronic conditions were selected using the clinical classification system (ccs), and categorized into 0, 1, or 2 chronic conditions in addition to epilepsy. We computed unadjusted healthcare expenditures per year and per individual (total direct healthcare expenditure, inpatient expenditure, outpatient expenditure, prescription medication expenditure, emergency room visit expenditure, home healthcare expenditure and other) by number of chronic conditions. We applied a two-part model with probit (probability of zero vs non-zero cost) and generalized linear model (GLM) gamma family and log link (for cost greater than zero) to examine the independent association between chronic conditions, and annual expenditures per individual, generating incremental costs with 0 chronic condition as reference. RESULTS: Over half of the patients with epilepsy had at least two chronic conditions (CC). Yearly, for each patient with one and two chronic conditions, unadjusted total healthcare expenditures were two times ($10,202; 95 %CI $6,551-13,853) to nearly three times ($21,277; 95 %CI $12,971-25,583) higher than those with no chronic conditions ($6,177; 95 %CI $4,895-7,459), respectively. In general healthcare expenditures increased with the number of chronic conditions for pre-specified cost categories. The incremental (adjusted) total healthcare expenditure increased with the number of chronic conditions (1CC vs 0 CC: $3,238; 95 %CI $524-5,851 p-value = 0.015 and ≥2 CC vs 0 CC: $8,145; 95 %CI $5,935-10,895 p-value < 0.001). In general, for all cost categories, incremental healthcare expenditures increased with the number of chronic conditions with the largest increment noted between those with 2 CC and those with 0 CC for inpatient ($2,025: 95 %CI $867-3,1830), outpatient ($2,141; 95 %CI $1,321-2,962), and medication ($1,852; 95 %CI $1,393-2,310). CONCLUSION: Chronic conditions are frequent among adult patients with epilepsy and are associated with a dose-response increase in healthcare expenditure, a difference driven by inpatient, outpatient, and medication prescription expenditures. Greater coordination of epilepsy care accounting for the presence of multiple chronic conditions may help lower the cost of epilepsy.

Prevalence and Predictors of Stroke in Patients with Crohn's Disease: A Nationwide Study.

OBJECTIVES: Mounting evidence points to the microbiome as a susceptibility factor for neurological disorders. Patients with Crohn's disease (CD) are at higher ischemic stroke (IS) risk, but no large scale epidemiologic studies have identified risk factors for stroke in this population. MATERIALS AND METHODS: We analyzed the 2017 Nationwide Inpatient Sample (NIS) dataset to identify patients with a discharge diagnosis of Crohn's disease using the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) code K50.X. We identified patients with a primary/secondary discharge diagnosis of IS using ICD-10-CM code I63.X. We compared sociodemographic and clinical variables between stroke and non-stroke patients with CD. Logistic regression analysis was applied to identify factors associated with IS. RESULTS: Of 30,212 patients with CD, 369 (1.2 %) had a discharge diagnosis of IS. Older age (odds ratio [OR], 1.03 [95% CI, 1.02-1.04], top quartile income (OR, 1.58 [95% CI, 1.10-2.30]), and hospitalization in a South Atlantic (OR, 1.82 [95% CI, 1.11-3.14]), East South Central (OR, 2.30 [95% CI, 1.28-4.25]), or West South Central hospital (OR, 2.40 [95% CI, 1.39-4.28]) were independently associated with IS. Clinical variables independently associated with IS in patients with CD included: atrial fibrillation (OR, 1.66 [95% CI, 1.15-2.33]), atherosclerosis (OR, 2.41 [95% CI, 1.32-4.10]), hyperlipidemia (OR, 1.69 [95% CI, 1.33-2.15]), hypertension (OR, 1.53 [95% CI, 1.18-1.98]) and valvular disease (OR, 1.62 [95% CI, 1.01-2.48). CONCLUSION: A subset of traditional stroke risk factors are associated with IS in patients with CD. CD patients with these conditions could be targeted for vascular risk reduction and surveillance.

Risk models to predict late-onset seizures after stroke: A systematic review.

BACKGROUND AND PURPOSE: We performed a systematic review to evaluate available risk models to predict late seizure onset among stroke survivors. METHODS: We searched major databases (PubMed, SCOPUS, and Cochrane Library) from inception to October 2020 for articles on the development and/or validation of risk models to predict late seizures after a stroke. The impact of models to predict late-onset seizures was also assessed. We included seven articles in the final analysis. For each of these studies, we evaluated the study design and scope of predictors analyzed to derive each model. We assessed the performance of the models during internal and external validation in terms of discrimination and calibration. RESULTS: Three studies focused on ischemic stroke alone, with c-statistic values ranging from 0.73 to 0.77. The SeLECT model from Switzerland was externally validated in Italian, German, and Austrian cohorts where c-statistics ranged from 0.69 to 0.81. This model along with the PSEiCARe model, were internally validated and calibration performance was provided for both models. The CAVS and CAVE models reported on the risk of late-onset seizures in patients with hemorrhagic stroke. The CAVS model derivation cohort was racially diverse. The CAVS model's c-statistic was 0.76, while the CAVE model had a c-statistic of 0.81. Calibration and internal validation were not performed for either study. The CAVS model, created from a Finnish population, was externally validated in American and French cohorts, with c-statistics of 0.73 and 0.69, respectively. Finally, the two studies focusing on both types of stroke came from the PoSERS and INPOSE models. Neither model provided c-statistics, calibration metrics, internal or external validation information. We found no evidence of the presence of impact studies to assess the effect of adopting late-onset seizure risk models after stroke on clinical outcomes. CONCLUSION: The SeLECT model was the only model developed in line with proposed guidelines for appropriate model development. The model, which was externally validated in a very similar and homogeneous population, may need to be tested in a more racially/ethnic diverse and younger population; testing the SeLECT model, accounting for overall brain health is likely to improve the identification of high-risk patients for late post stroke seizures.

Racial Disparities in Ischemic Stroke Among Patients with COVID-19 in the United States.

BACKGROUND: Cerebrovascular prevalence is high in patients with coronavirus disease 2019 (COVID-19). However, whether racial disparities exist among this population have not been systematically explored. METHODS: We performed a retrospective study to assess the prevalence of stroke stratified by race among patients aged 18 years or older with COVID-19 who visited emergency department (ED) up to August 13, 2020 in the United States (US). We used multivariable logistic regression to compare the odds of stroke in Black patients with COVID-19 compared to their non-Black counterparts while adjusting for the major potential confounders. RESULTS: Among 8815 patients with ED visits with COVID-19, 77 (0.87%), 95% confidence interval CI (95% CI): 0.69% to 1.10%) had ischemic stroke. The mean age of patients with stroke was 64 years (SD: 2 years); 28 (43%) were men, 55 (71%) had hypertension, and 29 (50%) were Black. The prevalence of ischemic stroke in Blacks, non-Hispanic Whites and Hispanics was 1.26% (95% CI: 0.86% to 1.83%), 0.84% (95% CI: 0.51% to 1.37%) and 0.49% (95% CI: 0.26% to 0.88%) respectively. After adjustment for age, sex, hypertension, diabetes, obesity, drinking and smoking, the likelihood of stroke was higher in Black than non-Black patients (adjusted odds ratio, 2.76; 95% CI, 1.13 to 7.15, p=0.03). CONCLUSIONS: Racial disparities in the prevalence of stroke among patients with COVID-19 exist, higher in Black population.

Incidence and Association of Reperfusion Therapies With Poststroke Seizures: A Systematic Review and Meta-Analysis.

BACKGROUND AND PURPOSE: We performed a systematic review and meta-analysis to assess the incidence and risk of seizures following acute stroke reperfusion therapy (intravenous thrombolysis [IVT] with r-tPA [recombinant tissue-type plasminogen activator], mechanical thrombectomy or both). METHODS: We searched major databases (MEDLINE, SCOPUS, and Cochrane Library) for articles published between 1995 and October 28, 2019. The primary outcome was the overall and treatment specific pooled incidence of poststroke seizures (PSS) following acute reperfusion therapy. We also computed the pooled incidence of early poststroke seizures and late poststroke seizures separately for all studies. We derived the risk of PSS associated with IVT in the pooled cohort of patients who received only IVT. The small number of studies (<3) that reported on the risk of PSS associated with mechanical thrombectomy alone or in combination with IVT did not allow us to compute an estimate of the risk of seizures associated with this therapy. RESULTS: We identified 13 753 patients with stroke, of which 592 had seizures. The pooled incidence of PSS was 5.9 % (95% CI, 4.2%-8.2%). PSS incidence rates among patients with stroke treated with IVT, mechanical thrombectomy, and both were respectively 6.1% (95% CI, 3.6%-10.2%), 5.9% (95% CI, 4.1%-8.4%), and 5.8 % (95% CI, 3.0%-10.9%). The incidence of late PSS was 6.7% (95% CI, 4.01%-11.02%) and that of early PSS was 3.14% (95% CI, 2.05%-4.76%). The pooled odds ratio for the association between IVT and PSS was 1.24 (95% CI, 0.75-2.05). CONCLUSIONS: The findings of this meta-analysis suggest that about one in 15 ischemic stroke patients treated with IVT, mechanical thrombectomy, or both develop seizures independently of the specific reperfusion treatment that they received.

Trends in prevalence and treatment of depressive symptoms in adult patients with epilepsy in the United States.

OBJECTIVE: Depressive symptoms are a common comorbidity among adults with epilepsy (AWE). Prior estimates regarding prevalence and treatment of depressive symptoms in AWE have been largely based on samples of tertiary care cohorts that may not be generalizable. We aimed to provide a representative population estimate of the prevalence and treatment of depressive symptoms over time in AWE in the United States as measured by a validated depression screen. METHOD: Data from the Medical Expenditure Panel Survey (MEPS) were analyzed from 2004 to 2015 to determine the prevalence of "screen positive" depressive symptoms (SPDS) among AWE as evaluated by the Patient Health Questionnaire-2 (PHQ-2). We defined pharmacotherapy for depressive symptoms as the prescription of any antidepressant, antipsychotic, anxiolytic, or central nervous system stimulant for the "Clinical Classification Code" of mood disorders within the year sampled, and psychotherapy as any outpatient or office-based visit for "mood disorders" for that year sampled. We analyzed temporal trends and explanatory variables for treatment using the Cochran-Armitage test and logistic regression, respectively. RESULTS: Our sample included 2024 AWE, representing 1,736,023 patients nationwide. This included 517 AWE with SPDS (AWE-SPDS), representing 401,452 AWE, and 1507 AWE who screened negative for depressive symptoms (AWE-SNDS), representing 1,334,571 AWE. The prevalence of SPDS was 23.1% (95% confidence interval [CI]: 20.6%-25.8%). Women (odds ratio [OR]: 1.40, 95% CI: 1.05-1.87), patients ages 35-49 (OR: 1.83, 95% CI: 1.23-2.72; compared with patients ages 18-34), and patients with Charlson Comorbidity Index ≥1 (OR: 1.92, 95% CI: 1.41-2.61) had higher odds of SPDS. There was no significant change in depressive symptoms' prevalence or treatment in AWE between the epochs of 2004-2006 and 2013-2015. CONCLUSIONS: Despite a quarter of AWE in the United States with SPDS, fewer than half received treatment. This indicates a need for improved efforts to screen AWE for depression and treat appropriately.

Enzyme-inducing antiseizure medication utilization in patients with epilepsy and vascular risk factors.

OBJECTIVES: Several lines of evidence have suggested that exposure to enzyme-inducing antiseizure medications (EIASMs) may result in the subsequent development of hyperlipidemia, a well-known risk factor for vascular disease. This may be an issue of concern particularly in the context of additional comorbid vascular risk factors. We therefore aimed to investigate trends of and associations with the use of these medications among adult patients with epilepsy. METHODS: The cross-sectional Medical Expenditure Panel Survey (MEPS) was interrogated to ascertain the prevalence of use of EIASMs by noninstitutionalized adult patients with epilepsy in the United States between the years 2004 and 2015. Any patient prescribed carbamazepine, phenytoin, phenobarbital, or primidone within a given year was defined as having been prescribed an EIASM. Trends over three-year epochs were evaluated with univariate logistic regression, while associations with demographic factors, vascular risk factors, and vascular disease were evaluated using a chi-square test corrected for survey design as well as multivariate logistic regression. RESULTS: A total of 2281 (unweighted) patients were identified, representing 1,781,237 individuals. Between 2004 and 2015, 45.9% (95% confidence interval [CI]: 42.4%-49.4%) were prescribed EIASMs. Approximately one-quarter of patients aged 65 years and above used EIASMs compared with 18.5% of younger patients (odds ratio [OR]: 1.83, 95% CI = 1.27-2.65). Female patients (OR = 0.61, 95% CI = 0.47-0.79) and those with heart disease (OR: 0.63, 95% CI = 0.45-0.89) were significantly less likely to be prescribed EIASMs. Among those prescribed EIASMs, 38.9% had hypertension, 12.2% had diabetes, 61.6% were overweight or obese, 17.3% heart disease, 17.2% had a history of a cerebrovascular event, and 28.5% had diagnosed hyperlipidemia. Nonetheless, between 2004-2006 and 2013-2015, the odds of EIASM prescription decreased significantly (OR: 0.39, 95% CI: 0.28-0.55). CONCLUSIONS: A substantial proportion of patients with comorbid vascular disease or vascular risk factors (e.g., hypertension and older age) is prescribed EIASMs. This could potentially increase patients' risk for subsequent negative outcomes such as cardiovascular or cerebrovascular disease. Though utilization of these medications has decreased, further efforts toward increasing use of newer antiseizure medications (ASMs) that are not associated with similar risks may be warranted.

Frequency and predictors of 30-day readmission after an index hospitalization for generalized convulsive status epilepticus: A nationwide study.

OBJECTIVE: The objective of the study was to assess the frequency and factors associated with all-cause 30-day readmission among patients hospitalized with generalized convulsive status epilepticus (GCSE) in a nationwide sample in the United States. METHODS: We used The 2014 Nationwide Readmission Database (NRD) as the data source. We included adults (age ≥18 years) with a primary discharge diagnosis of GCSE, identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 345.3. We excluded patients who died during hospitalization and those who had missing information on the length of stay (LOS). We also excluded those discharged in December 2014. We computed the overall 30-day readmission rate and compared prespecified groups by their 30-day readmission status. We applied a multiple logistic regression analysis to identify independent predictors of all-cause 30-day readmission adjusting for potential confounders. RESULTS: Among 14,562 (weighted 31,062) adults discharged with a diagnosis of GCSE, 2520 (17.3%) were readmitted within 30 days. In multivariate analysis, patients with comorbid conditions (odds ratio (OR) for Charlson Comorbidities Index (CCI) = 1 and ≥2 was 1.12, 95% confidence interval (CI): 1.0-1.36 and 1.32, 95% CI: 1.17-1.48, respectively), LOS >6 days (OR: 1.42; 95% CI: 1.05-192), discharged against medical advice (OR: 1.45; 95% CI: 1.09-1.92), or discharged to a short-term hospital (OR: 1.39; 95% CI: 1.0-1.88), had higher odds of 30-day readmission, while there was an inverse association for those aged ≥45 years or with high income. Seizures were the most common cause associated with readmission, followed by sepsis and cerebrovascular diseases, respectively. SIGNIFICANCE: Little is known about the frequency and predictors of early readmission after GCSE. This study showed that more than one in six patients with GCSE was readmitted within 30 days after discharge. More considerable attention to high-risk subgroups may identify opportunities to ameliorate the clinical outcome and lessen the economic burden of early readmission after GCSE.

Contemporary relationship between medical expenditures and quality of life among adults with epilepsy in the United States.

AIMS: Epilepsy exacts substantial adverse economic and quality of life (QoL) costs. Clarifying the quantitative and qualitative relationships between total and out-of-pocket (OOP) healthcare expenditures and QoL could shed insights into how they influence each other, and have done so over recent times. METHODS: We used the Medical Expenditure Household Components 2003-2014 to identify a total of 2450 adults with epilepsy, representing a weighted population of 1,942,413. Quality of life was assessed using the Physical Component Summary (PCS) and the Mental Component Summary (MCS) derived from the Short-form 12 Version 2 (SF-12 V2), converted into quartiles of equal distribution, with higher quartiles indicating a better QoL. We computed unadjusted mean and adjusted (through a generalized linear model (GLM)) total and OOP healthcare expenditures by QoL categories among adults with epilepsy (reported as dollars in 2016). RESULTS: The pooled estimates of total healthcare expenditures decreased as PCS and MCS quartiles of QoL increased [PCS: costs for quartile 1 = $21,792 (95% confidence interval (CI): $18,416-$25,168 vs. costs for quartile 4 = $6057 (95% CI: $4648-$7466) and MCS: costs for quartile 1 = $19,040 (95% CI: $15,544-$22,535) vs. quartile 4 = $12,939 (95% CI: $8450-$17,429)]. Similarly, the pooled estimates of OOP healthcare expenditures and QoL were inversely related [PCS: costs for quartile 1 = $1849 (95% CI: $1583-$2114) vs. costs for quartile 4 = $948 ($709-$1187) and MCS: costs for quartile 1 = 1812 (95% CI: $1483-2141) vs. quartile 4 = $1317 (95% CI: $982-$1652)]. The association between QoL and total and OOP healthcare expenditures was unchanged after adjusting for socioeconomic and healthcare system related confounders in the GLM. Overall, healthcare expenditures were stable across years independently of the QoL; only OOP expenditures decreased between 2003-2006 and 2011-2014 for quartile 1 of PCS and MCS. CONCLUSION: Quality of life and OOP health expenditures are independently and inversely related to each other among adults with epilepsy. Over the decade studied in the United States, there was a decrease in OOP health expenditures among those patients with epilepsy with the lowest QoL, possibly reflecting a rise in insurance coverage after the Affordable Care Act.

Association of seizure co-morbidity with early hospital readmission among traumatic brain injury patients.

OBJECTIVE: To assess the frequency of seizure co-morbidity and its independent association with 30-day readmission rate among patients hospitalized with traumatic brain injury (TBI) in the United States. METHODS: The data source was the 2014 Nationwide Readmission Database. We included adults (Age ≥18 years) with a primary discharge diagnosis of TBI, identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes 800.0, 801.9, 803.0, 804.9, 850.0-854.1, and 959.01. Seizures were diagnosed using the ICD-9-CM codes of 345.x and 780.39. Overall and across pre-specified groups 30-readmission rate was computed. Logistic regression analysis was used to identify independent predictors of 30-day readmission. RESULTS: Among 76,062 unweighted adults discharged with a diagnosis of TBI, 7,776 (10.14%) had a secondary discharge diagnosis of seizures.A total of 1,751 (2.3%) patients with a primary discharge diagnosis of TBI were readmitted within 30 days. On multivariate logistic analysis, patients discharged with a secondary diagnosis of seizures were 18% more likely to be readmitted within 30 days compared to those without seizures (OR 1.18, 95% CI: 1.01-1.39, P = .42). CONCLUSION: One in 10 patients hospitalized with TBI in the US have a co-morbid seizure disorder. Seizure co-morbidity conferred 18% greater odds of being readmitted within 30 days.

Stroke Thrombectomy Utilization Rates by Sex: What were Things Like before 2015?

BACKGROUND: Little is known about any potential sex disparities in access to mechanical thrombectomy (MT), including before the pivotal clinical trials establishing MT as a standard of care for acute ischemic stroke management. METHODS: All ischemic stroke patients included in the National Inpatient Sample between 2006 and 2014, were identified using the international classification of disease, Ninth Revision, Clinical Modification 433.X1, 434.X1, and 436. Those who received MT were identified using the procedure code 39.74. We computed the rate and trend in MT utilization among stroke patient by sex. We also applied a logistic regression model to examine the association between sex and the rate of MT, accounting for potential extraneous confounders. RESULTS: Of the 520,963 (weighted 1,032,940) with ischemic stroke, 6049 (.59%) received mechanical thrombectomy (MT), including 3012 (.58%) women and 3037 (.60%) men (P = .2807). For both men and women the rate of MT increased by nearly 30-fold from .04% in 2006 to 1.13% in 2014. On univariate analysis there was no difference in annual change in the utilization of MT; however, after adjusting for confounders, women with ischemic stroke were 12% more likely to have received treatment with MT than their male counterparts. CONCLUSION: The rate of MT has increased in both genders by nearly 30-fold in the 9 years preceding the publication of pivotal clinical trials on MT in 2015 with a 12% higher likelihood for women to receive MT after ischemic stroke.

Influence of a Comorbid Diagnosis of Seizure on 30-Day Readmission Rates Following Hospitalization for an Index Stroke.

OBJECTIVE: To examine the association of a comorbid seizure diagnosis with early hospital readmission rates following an index hospitalization for stroke in the United States. METHODS: Retrospective analysis of the 2014 National Readmission Database. The study population included adult patients (age >18 years old) with stroke, identified using the International Classification of Disease Ninth Revision, Clinical Modification (ICD-9-CM) codes 433.X1, 434.X1, and 436 for ischemic stroke as well as 430, 431, 432.0, 432.1, and 432.9 for hemorrhagic stroke. A subgroup of patients with a secondary discharge diagnosis of seizures was identified using the ICD-9-CM codes 780.39 and 345.X. We computed all-cause 30-day readmission rates for all strokes and by stroke type (ischemic versus hemorrhagic). Finally, we used a multivariable logistic regression model to examine the independent association between seizure and readmission by stroke type. RESULTS: Of 271,148 stroke patients, 6.3% (16,970) had a secondary discharge diagnosis of seizures including 5.0% (11,562) of patients with ischemic stroke and 13.4% (5,409) with hemorrhagic stroke. Overall readmission rate for stroke patients was 11.9% (hemorrhagic stroke: 14.2% versus ischemic strokes: 11.6%). Thirty-day readmission rate was higher in patients with seizures for all strokes (15.6% versus 11.7%, P value <.001), ischemic strokes (15.0% versus11.4%, P value <.001), and hemorrhagic strokes (16.7% versus 13.8%, P value <.001). After adjusting for several patient-specific and healthcare system-specific confounders, hospitalized stroke patients with comorbid seizure diagnosis were more likely than those without seizures to be readmitted within 30 days (OR: 1.20, 95% CI: 1.14-1.25). CONCLUSION: The presence of a comorbid diagnosis of seizure disorder in a hospitalized stroke patient significantly raises the occurrence of early hospital readmission in the United States.

Recent patterns of vagal nerve stimulator use in the United States: Is there a racial disparity?

OBJECTIVE: Patients with refractory epilepsy are at a high risk of complications but may not receive the same level of care across racial groups. We aimed to ascertain racial inequalities and trends in the use of a vagal nerve stimulator (VNS) among adult patients with refractory epilepsy. METHODS: A total of 24 159 adults (18 years and older) with refractory epilepsy from the National Inpatient Sample between the years 2006 and 2014 were included in this analysis. We used a multivariate logistic regression analysis to evaluate independent predictors of VNS use among patients with refractory epilepsy. Covariates included gender, age, insurance type, and household income. In addition, we evaluated for trends in VNS use over the 9-year period of data collection. RESULTS: A total of 1.56% of patients with refractory epilepsy had used a VNS between 2006 and 2014. Overall, there was a trend of decreased use of a VNS between 2006-2008 (2.1%) and 2012-2014 (0.9%). In the adjusted multivariate logistic regression analysis, blacks (odds ratio [OR] = 0.52, 95% confidence interval [CI] = 0.35-0.77) were significantly less likely to have used a VNS relative to non-Hispanic whites. Additional factors independently associated with a decreased likelihood of VNS use were age > 65 years (OR = 0.51, 95% CI = 0.28-0.95) and years 2012-2014 (OR = 0.44, 95% CI = 0.28-0.67). SIGNIFICANCE: There was a trend toward a decrease in the use of a VNS among adult patients with refractory epilepsy. Our results also suggest that black patients with refractory epilepsy were less likely to receive a VNS independently of other variables. Increased work toward effectively reducing racial disparities in access to quality epilepsy care is crucial.

Costs and cost-drivers of a diagnosis of depression among adults with epilepsy in the United States.

OBJECTIVE: The objective of this study was to evaluate the amount of direct costs associated with occurrence of depression in people with epilepsy. METHODS: The Medical Expenditure Panel Survey Household Components (MEPS-HC) served as data source to identify adults (≥18 years) with epilepsy from 2003 to 2014, using the Clinical Classification Code CCC-83. Annual unadjusted per person total healthcare expenditures and individual cost components (inpatient, outpatient, prescription, emergency room, and home health) were compared between people with epilepsy and depression vs. without depression. A two-part model estimated the adjusted incremental direct cost of depression (total and individual cost components) among adults with epilepsy. The model was adjusted for sex, race/ethnicity, education, marital status, insurance status, census region, income, Charlson Comorbidities index (CCI), and year trend. RESULTS: Out of a weighted 1,942,413 US adults with epilepsy, 675,037 (34.7%) had a diagnosis of depression. Annual total unadjusted per person direct cost of depression was $5290 higher in people with epilepsy vs. without [$18,776 (95% confidence interval [CI]: 16,241-21,311) vs. $13,486 (95%CI: 9780-17,191)]. Costs for outpatient and prescriptions were higher among people with epilepsy plus depression vs. without depression, but no differences were observed for inpatient, emergency room, and home health costs. In the adjusted model, total costs [$2523 (95%CI: 62-4984)], incremental annual direct costs per person for outpatient [$1940 (95%CI: 1266-2613)], prescriptions [$1285 (95%CI: 772-1798)], and emergency room [$191 (95%CI: 20-361)] were significantly higher for people with epilepsy plus depression. Unadjusted and adjusted incremental total aggregate annual direct costs of depression for people with epilepsy were $3.5 billion and $1.7 billion respectively. CONCLUSION: Costs of epilepsy with presence of depression in the US are high, and primarily driven by outpatient, prescriptions, and emergency room costs.

Seizure comorbidity boosts odds of 30-day readmission after an index hospitalization for sepsis.

OBJECTIVE: The objective of this study was to evaluate the association between comorbid seizures and hospital readmissions within 30 days following an index hospitalization for sepsis. METHODS: We analyzed data from 445,489 adult discharges derived from the 2014 National Readmission Database, to evaluate the association of an International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis of seizure during an index hospitalization for sepsis and 30-day readmission rates. We excluded patients who died during hospitalization and those who had missing information on the length of stay or were discharged in December 2014. Prespecified groups were compared by their 30-day readmission and seizure status. We applied a multivariable logistic regression analysis to assess the independent association between seizure and readmission. RESULTS: Nearly one out of 15 patients discharged with a primary diagnosis of sepsis had comorbid seizures, of which 97% were status epilepticus. Patients with sepsis and comorbid seizures were 30% more likely to be readmitted within 30-days postdischarge, compared to those with sepsis and no comorbid seizures. Additional factors associated with a significantly higher risk for hospital readmission included male sex, age 45-84 years, increased length of stay and cost of primary admission, greater medical comorbidities, and discharge destination. Patients with seizures during their index hospitalization were significantly more likely to have also had a concurrent stroke or the central nervous system (CNS) infection compared with patients without seizures. CONCLUSIONS: Seizures are not uncommon, and patients with sepsis and comorbid seizures are 30% more likely to be readmitted within 30-days postdischarge, compared to those with sepsis and no comorbid seizures.