•The number and type of antiseizure medications (ASMs) may impact seizure clustering in the epilepsy monitoring unit (EMU), with long-acting ASMs likely providing protection during medication ...withdrawal.•A higher number of pre-admissions ASMs and temporal lobe epilepsy were associated with increased seizure clustering in the EMU.•Seizure clustering in the EMU may be associated with other adverse events, such as falls and injuries.
Seizure clustering, is the most frequently reported adverse event in epilepsy monitoring unit (EMU) safety studies which, can also potentiate other adverse events, such as falls, status epilepticus, and increased length of stay. The purpose of this study is to determine variables associated with increased risk of seizure clustering among patients admitted to the EMU.
A retrospective review of patients admitted to the EMU over a two-year period was completed. Data collected included patient demographics, types of epilepsy, seizure frequency, anti-seizure medications (ASMs) and hospital and EMU course including incidence of seizure clustering.
Two hundred seven patients were included in our study; of these, ninety patients experienced two or more seizures in a 24-hour period (24SC), and 68 patients experienced two or more seizures in a 4-hour period (4SC). Logistic regression analysis associated the absence of long-acting ASM with increased clustering within the 4SC group (p = 0.038). For every additional ASM taken by a patient at home, the odds of seizure clustering increased by 81% in the 4SC group (p = 0.009) and by 61% in the 24SC group (p = 0.022). In addition, patients with a diagnosis of temporal lobe epilepsy had some association with clustering in the 24SC group (p = 0.061).
Our data showed that long-acting ASMs can be protective against seizure clustering. Furthermore, patients with temporal lobe epilepsy, and those on increased numbers of ASMs, were more likely to experience seizure clustering when undergoing medication withdrawal during an EMU evaluation.
Background
In this study, we identify factors associated with ketamine success in the treatment of refractory status epilepticus (SE). We also evaluate for adverse events including systemic and ...cerebral hemodynamic stability and fluid volume overload.
Methods
In this retrospective, large, single-center, observational study over a 10-year period, 879 consecutive patients receiving intravenous (IV) ketamine were reviewed, and 81 patients were identified as receiving IV ketamine for the treatment of SE. Descriptive analysis was done to determine treatment response and adverse events in patients receiving IV ketamine for SE. Multivariable logistic regression analyses were fitted to determine prediction models for seizure cessation.
Results
Permanent cessation of SE was achieved in 49 of 81 (60.5%) of patients for whom ketamine was part of the treatment plan. Of those, 36 (44.4%) were attributed to ketamine as the last drug used (ketamine-associated cessation AC). Prior history of epilepsy had an odds ratio of 3.19 (confidence interval 0.83–12.67,
p
= 0.09) associated with efficacious medication response. Increased latency to ketamine was associated with cessation of SE specifically in patients in the AC group (
p
= 0.077). Longer SE duration (
p
= 0.04), administration of ketamine loading dose (bolus;
p
= 0.03), and anoxia (
p
= 0.007) were negatively associated with AC. Administration of ketamine loading dose (
p
= 0.02) and anoxia (
p
= 0.009) were negatively associated with overall SE cessation. There was no significant impact of ketamine on cerebral hemodynamics, but evidence of fluid volume overload was seen (28.4% of patients).
Conclusions
Our cohort is a large observational study showing a high success rate of permanent cessation of SE after the addition of ketamine. Using multivariable analysis, we demonstrate a significant association with seizure cessation in patients with prior history of epilepsy and those with prolonged latency to ketamine initiation. Furthermore, we describe the impact of fluid volume overload as an anticipated complication with ketamine use.
Summary
Refractory status epilepticus (RSE) can lack overt clinical manifestation and is usually treated with continuous infusion of intravenous anesthetic drugs (IVADs), where the use of continuous ...electroencephalography (cEEG) is imperative. Ketamine has recently been shown to be effective in the treatment of RSE. We retrospectively review a cohort of 11 patients receiving ketamine as part of their treatment regimen for RSE. We report on the presence of a characteristic EEG rhythm consisting of a generalized archiform theta to beta rhythms (7–20 Hz) appearing after ketamine administration. This pattern was seen in five patients, four of whom achieved successful resolution of RSE. Ketamine‐induced EEG pattern may serve as a biomarker predictive of successful treatment outcome in RSE.
•A validated fatigue scale can help identify moderate-to-severe fatigue in epilepsy.•The 9-item FSS showed fair psychometric properties in patients with epilepsy.•There was evidence of item misfit ...for the first two of the original items.•A modified version of the FSS, omitting the misfit items, serves as a better scale.
To utilize the Rasch model to validate and assess the psychometric properties of the Fatigue Severity Scale (FSS) in patients with epilepsy.
A total of 307 patients (age > 18 years) with a confirmed diagnosis of epilepsy were consented to participate. Exclusion criteria included patients with psychogenic nonepileptic events, cognitive disabilities, and patients who did not speak/understand English. The nine-step FSS was programmed into software administered to patients on electronic tablets, and patient responses were auto-scored. The Rasch rating scale model (RSM) was used to evaluate the unidimensionality, reliability, and targeting of the FSS. To assess unidimensionality, we examined infit and outfit mean squares. We also assessed unidimensionality of the FSS using a principal component analysis of Rasch residuals, where residuals are understood as the difference between observed and expected data values. We evaluated the internal consistency of person and item performance by examining separation reliability estimates and separation ratio. Differential Item Functioning (DIF) was calculated for gender.
There was mixed evidence regarding the extent to which the FSS fit the Rasch model. Outfit values ranged from 0.52 to 2.72 and infit values were 0.60 to 2.18, strongly suggesting the presence of misfitting items: Item 1 (“My motivation is lower when I am fatigued”) and Item 2 (“Exercise brings on my fatigue”).
The nine-item FSS showed fair psychometric properties in this sample of patients with epilepsy. Our study provides unique, supportive information for the use of a modified version of the FSS, omitting the first two items, in patients with epilepsy. Given the prevalence of fatigue and other neuropsychiatric comorbidities of epilepsy, having a validated fatigue scale can aid healthcare providers to identify moderate-to-severe fatigue levels in patients with epilepsy and address the plausible risk factors.
Background
Prior studies show hospital admission volume to be associated with poor outcomes following elective procedures and inpatient medical hospitalizations. However, it is unknown whether ...hospital volume impacts Inpatient outcomes for status epilepticus (SE) hospitalizations. In this study, we aimed to assess the impact of hospital volume on the outcome of patients with SE and related inpatient medical complications.
Methods
The 2005 to 2013 National Inpatient Sample database was queried using International Classification of Diseases 9th Edition diagnosis code 345.3 to identify patients undergoing acute hospitalization for SE. The National Inpatient Sample hospital identifier was used as a unique facility identifier to calculate the average volume of patients with SE seen in a year. The study cohort was divided into three groups: low volume (0–7 patients with SE per year), medium volume (8–22 patients with SE per year), and high volume (> 22 patients with SE per year). Multivariate logistic regression analyses were used to assess whether medium or high hospital volume had lower rates of inpatient medical complications compared with low-volume hospitals.
Results
A total of 137,410 patients with SE were included in the analysis. Most patients (
n
= 50,939; 37%) were treated in a low-volume hospital, 31% (
n
= 42,724) were treated in a medium-volume facility, and 18% (
n
= 25,207) were treated in a high-volume hospital. Patients undergoing treatment at medium-volume hospitals (vs. low-volume hospitals) had higher odds of pulmonary complications (odds ratio OR 1.18 95% confidence interval {CI} 1.12–1.25;
p
< 0.001), sepsis (OR 1.24 95% CI 1.08–1.43
p
= 0.002), and length of stay (OR 1.13 95% CI 1.0 –1.19
p
< 0.001). High-volume hospitals had significantly higher odds of urinary tract infections (OR 1.21 95% CI 1.11–1.33
p
< 0.001), pulmonary complications (OR 1.19 95% CI 1.10–1.28,
p
< 0.001), thrombosis (OR 2.13 95% CI 1.44–3.14,
p
< 0.001), and renal complications (OR 1.21 95% CI 1.07–1.37,
p
= 0.002). In addition, high-volume hospitals had lower odds of metabolic (OR 0.81 95% CI 0.72–0.91,
p
< 0.001), neurological complications (OR 0.80 95% CI 0.69–0.93,
p
= 0.004), and disposition to a facility (OR 0.89 95% CI 0.82–0.96,
p
< 0.001) compared with lower-volume hospitals.
Conclusions
Our study demonstrates certain associations between hospital volume and outcomes for SE hospitalizations. Further studies using more granular data about the type, severity, and duration of SE and types of treatment are warranted to better understand how hospital volume may impact care and prognosis of patients.
•This is the first case series on the changes in lacosamide levels in seven women during pregnancy.•Lacosamide dose normalized concentrations had a significant decrease during trimesters 2 and ...3.•None of the infants with exposure to lacosamide had significant major congenital malformations.•Lacosamide metabolism increase during pregnancy could result in lower levels and more seizures.
Still considered a new ASD, teratogenicity from lacosamide (LCM) exposure during pregnancy is unknown. LCM metabolism through several cytochrome P450 enzymes and minor glucuronidation metabolism in the liver may increase during pregnancy and theoretically lead to lower LCM levels during pregnancy and the risk of increased seizures. Our objective was to determine the impact of pregnancy on serum LCM levels in a series of women with epilepsy (WWE).
We identified seven pregnancies with exposure to LCM with at least one level drawn during pregnancy. Patient ages ranged from 18 to 38 years (mean 26.4 years) and total daily doses of LCM ranged from 200 to 600 mg/day. Two patients had increased dose adjustments in response to breakthrough seizures. Dose normalized concentrations (DNC) showed an overall decrease over time through each trimester (p = 0.002) and significantly lower during trimester 2 and 3 (p = 0.001 and p = 0.004, respectively) compared to pre-pregnancy levels. There were no significant changes in seizure frequency and none of the neonates had teratogenic findings at time of birth. We are the first to report a case series on the changes in LCM levels during pregnancy with significant decreased LCM DNC levels during the second and third trimesters in comparison to pre-pregnancy values.
•Medial and inferior frontal lobe hypometabolism on FDG-PET was associated with high SUDEP risk in our cohort.•This pattern may serve as an imaging biomarker for those at increased risk of ...SUDEP.•Definite and probable SUDEP patients demonstrated a similar metabolic pattern on their individual PET scans.•Frontal lobe dysfunction may play a role in the pathophysiology of SUDEP, and FDG PET can be used to identify patients at high risk.
Abnormalities of brain structures and neuronal networks have been identified in MRI studies of patients with Sudden Unexpected Death in Epilepsy (SUDEP) as well as in those at elevated risk. The goal of this study was to identify common patterns of objectively detected brain glucose metabolic abnormalities associated with SUDEP patients and those at high SUDEP risk.
Patients with refractory epilepsy (n = 78, age: 16–61 years, 44 females), who underwent comprehensive presurgical evaluation, were assessed for their risk of SUDEP using the revised SUDEP-7 inventory. From the 57 patients with low SUDEP risk, 35 were selected to match their demographic and clinical characteristics to those with high SUDEP risk (n = 21). 18Ffluoro-deoxy-glucose positron emission tomography (FDG-PET) abnormalities were evaluated in the high- and low-SUDEP risk subgroups compared to FDG-PET scans of a healthy adult control group using statistical parametric mapping (SPM). Individual FDG-PET scans of 4 additional patients, who died from SUDEP, were also analyzed by SPM.
Mean SUDEP-7 score was 6.1 in the high and 2.7 in the low SUDEP risk group. MRI showed no lesion in 36 patients (64%). Statistical parametric mapping analysis of the high SUDEP risk subgroup showed bilateral medial frontal and inferior frontal hypometabolism as a common pattern. The low-risk group showed no specific common metabolic abnormalities on SPM group analysis. Individual PET scans of all 4 patients who died from SUDEP also showed bilateral frontal lobe hypometabolism.
These data show that bilateral frontal lobe involvement on FDG-PET, especially the medial and inferior frontal cortex, may be a common metabolic pattern associated with high SUDEP risk and SUDEP itself, in patients with refractory focal epilepsy.
Lacosamide (LCM) is a third-generation anti-epileptic drug (AED) for partial-onset epilepsy with minimal hepatic metabolism and drug-drug interactions. The impact of individual patient variables such ...as race on drug metabolism have been under-reported in AEDs and LCM has not been specifically investigated. Our aim was to assess the role race plays on serum LCM levels in the management of epilepsy. Thus, we retrospectively reviewed patients with focal seizures who received LCM and had LCM levels as part of their routine clinical care in our Level IV Epilepsy Center. Variables including age, race, gender, LCM serum levels, LCM daily dose, and concomitant AEDs were collected and analyzed. A total of 93 patients with 1–3 clinic visits yielded 122 LCM serum levels. African Americans (AA) comprised 62.3% of our serum samples. Daily LCM doses averaged 350 mg/day (range 50–1000 mg/day). Eighty-nine percent of patients took 1–2 other AEDs. Overall, AA patients had lower LCM levels (mean 6.8 μg/mL) compared to White patients (mean of 7.1 μg/mL) (p = .017) even when considering for the daily dose effect (p = .007). Analysis of co-variables did not have significant effect on LCM levels. Overall, AA patients had a weaker relationship between LCM daily dose (adjusted for weight) and serum levels as compared to White patients and require a higher LCM dose per weight to achieve similar levels. Differences in pharmacogenetics may play an important role in these findings and focus on how these variations impact seizure burden.
•Lacosamide (LCM) serum concentration can be highly variable in routinely collected sera.•African American (AA) patients can have lower lacosamide (LCM) concentration levels when compared to White patients.•Type of concomitant antiepileptic drugs did not have a significant effect on LCM levels.•Overall, AA epilepsy patients may require a higher LCM dose to achieve LCM sera levels similar to White patients.
The retrospective nature of most available epilepsy quality improvement (QI) tools focuses on changing health care provider (HCP) clinical habits and documentation practices rather than a focus on ...real-time patient interventions. Furthermore, patient-reported outcome data are often not available to determine the efficacy of these tools. Our primary objective was to demonstrate the improvement of HCPs' documentation and review of epilepsy quality measures (EQMs) during the patient visit with the implementation of a novel web application, NeuroMeasures. Our secondary objective was to improve the percentage of point-of-care counseling and interventions based on quality measures during the patient encounter based on the results of the NeuroMeasures tool.
Our QI study focused on comparing a preintervention and postintervention cohort of patients with epilepsy (PWE) before the implementation of NeuroMeasures, a web-based application that takes a self-guided patient survey through self-scoring algorithms focused on the American Academy of Neurology (AAN)'s 2017 EQMs. This e-tool then provides the HCP a tool to directly review the EQMs highlighted and perform any necessary counseling or interventions at the point-of-care visit. After intervention, EQMs were gained from the review of the NeuroMeasures HCP quality measures tool and a chart review for physician documentation. Patients with language barriers and severe cognitive disabilities were excluded from the study.
The preintervention cohort consisted of 150 unique PWE, and the postintervention cohort included 379 unique adult PWE and 515 total encounters. Overall percentages of review/adherence of EQMs were significantly improved between the preintervention and postintervention group for counseling for women of childbearing potential (91.7%), intractable epilepsy referral to a comprehensive epilepsy center (74%), quality of life assessment (80%), improvement of quality of life measurements (41.7%), and depression and anxiety screening (85.6%), demonstrating a significant increase when compared with the preintervention group (
< 0.00001).
A web-based point-of-care EQM application demonstrated significant improvement of the HCP's ability to perform and review EQMs at the point-of-care patient visit. Furthermore, the application was successful in creating opportunities for direct intervention based on the EQMs and chances for better patient education and provider-patient communication. Further considerations would include automated survey requests and expansion into other AAN QMs.
Background/Objectives. To illustrate characteristic electroencephalogram (EEG) features in patients prior to their first cardiac arrest. Methods. We identified 15 patients who suffered cardiac arrest ...during continuous EEG at our institution from June 2016 to June 2019. Eight patients were excluded due to co-administration of intravenous anesthetics (which may confound EEG) or if they had a previous prolonged cardiac arrest (>5 minutes) during the same hospitalization. We collected background information, analyzed the time span and vital signs between the initial background change and cardiac arrest. Results. The time span range (minutes) from initial background change to cardiac arrest was 4 to 483 (average 128.9), initial background change to suppression was 0 to 372 (average 75.6), suppression to cardiac arrest was 1 to 140 (average 53.3), suppression to complete suppression was 0 to 66 (average 20.4), and complete suppression to cardiac arrest was 1 to 111 (average 32.9). Three patients showed background changes more than 160 minutes before cardiac arrest. All patients showed progressive heart rate (HR) decline at or before the beginning of suppression on EEG. HR (beats/min) (mean ± SE) at background change, background suppression, complete suppression, and cardiac arrest was 86.3 ± 7.5, 63.9± 7.5, 36.0 ± 6.8, and 0, respectively. We found statistically significant HR changes (P < .05) between background change and complete suppression time points. Conclusions. Our data indicate that EEG pattern change can occur minutes to hours before the initial cardiac arrest. These patterns may be due to progressive cerebral ischemia. Further studies with broad-scale monitoring of vital signs and evoked potentials may help develop models for predicting cardiac insufficiency.
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