Alcohol for seizure induction in the epilepsy monitoring unit.

RATIONALE: Seizure induction techniques are used in the epilepsy monitoring unit (EMU) to increase diagnostic yield and reduce length of stay. There are insufficient data on the efficacy of alcohol as an induction technique. METHODS: We performed a retrospective cohort study using six years of EMU data at our institution. We compared cases who received alcohol for seizure induction to matched controls who did not. The groups were matched on the following variables: age, reason for admission, length of stay, number of antiseizure medications (ASM) at admission, whether ASMs were tapered during admission, and presence of interictal epileptiform discharges. We used both propensity score and exact matching strategies. We compared the likelihood of epileptic seizures and nonepileptic events in cases versus controls using Kaplan-Meier time-to-event analysis, as well as odds ratios for these outcomes occurring at any time during the admission. RESULTS: We analyzed 256 cases who received alcohol (median dose 2.5 standard drinks) and 256 propensity score-matched controls. Cases who received alcohol were no more likely than controls to have an epileptic seizure (X2(1) = 0.01, p = 0.93) or nonepileptic event (X2(1) = 2.1, p = 0.14) in the first 48 h after alcohol administration. For the admission overall, cases were no more likely to have an epileptic seizure (OR 0.89, 95 % CI 0.61-1.28, p = 0.58), nonepileptic event (OR 0.97, CI 0.62-1.53, p = 1.00), nor require rescue benzodiazepine (OR 0.63, CI 0.35-1.12, p = 0.15). Stratified analyses revealed no increased risk of epileptic seizure in any subgroups. Sensitivity analysis using exact matching showed that results were robust to matching strategy. CONCLUSIONS: Alcohol was not an effective induction technique in the EMU. This finding has implications for counseling patients with epilepsy about the risks of drinking alcohol in moderation in their daily lives.

Longitudinal point-of-care assessment of psychomotor vigilance in children in the epilepsy monitoring unit.

The epilepsy monitoring unit (EMU) is a complex and dynamic operational environment, where the cognitive and behavioural consequences of medical and environmental changes often go unnoticed. The psychomotor vigilance task (PVT) has been used to detect changes in cognition and behaviour in numerous contexts, including among astronauts on spaceflight missions, pilots, and commercial drivers. Here, we piloted serial point-of-care administration of the PVT in children undergoing invasive monitoring in the EMU. Seven children completed the PVT throughout their hospital admission and their performance was associated with daily seizure counts, interictal epileptiform discharges, number of antiseizure medications (ASMs) administered, and sleep quality metrics. Using mixed-effects models, we found that PVT reaction time and accuracy were adversely affected by greater number of ASMs and interictal epileptiform activity. We show that serial point-of-care PVT is simple and feasible in the EMU and may enable greater understanding of individual patient responses to medical and environmental alterations, inform clinical decision-making, and support quality-improvement and research initiatives.

Patient Safety in Canadian Epilepsy Monitoring Units: A Survey of Current Practices.

BACKGROUND: Guidelines on epilepsy monitoring unit (EMU) standards have been recently published. We aimed to survey Canadian EMUs to describe the landscape of safety practices and compare these to the recommendations from the new guidelines. METHODS: A 34-item survey was created by compiling questions on EMU structure, patient monitoring, equipment, personnel, standardized protocol use, and use of injury prevention tools. The questionnaire was distributed online to 24 Canadian hospital centers performing video-EEG monitoring (VEM) in EMUs. Responses were tabulated and descriptively summarized. RESULTS: In total, 26 EMUs responded (100% response rate), 50% of which were adult EMUs. EMUs were on average active for 23.4 years and had on average 3.6 beds. About 81% of respondents reported having a dedicated area for VEM, and 65% reported having designated EMU beds. Although a video monitoring station was available in 96% of EMUs, only 48% of EMUs provided continuous observation of patients (video and/or physical). A total of 65% of EMUs employed continuous heart monitoring. The technologist-to-patient ratio was 1:1-2 in 52% of EMUs during the day. No technologist supervision was most often reported in the evening and at night. Nurse-to-EMU-patient ratio was mostly 1:1-4 independent of the time of day. Consent forms were required before admission in 27% of EMUs. CONCLUSION: Canadian EMUs performed decently in terms of there being dedicated space for VEM, continuous heart monitoring, and adequate nurse-to-patient ratios. Other practices were quite variable, and adjustments should be made on a case-by-case basis to adhere to the latest guidelines.

Epilepsy center characteristics and geographic region influence presurgical testing in the United States.

OBJECTIVE: Persons with drug-resistant epilepsy may benefit from epilepsy surgery and should undergo presurgical testing to determine potential candidacy and appropriate intervention. Institutional expertise can influence use and availability of evaluations and epilepsy surgery candidacy. This census survey study aims to examine the influence of geographic region and other center characteristics on presurgical testing for medically intractable epilepsy. METHODS: We analyzed annual report and supplemental survey data reported in 2020 from 206 adult epilepsy center directors and 136 pediatric epilepsy center directors in the United States. Test utilization data were compiled with annual center volumes, available resources, and US Census regional data. We used Wilcoxon rank-sum, Kruskal-Wallis, and chi-squared tests for univariate analysis of procedure utilization. Multivariable modeling was also performed to assign odds ratios (ORs) of significant variables. RESULTS: The response rate was 100% with individual element missingness < 11% across 342 observations undergoing univariate analysis. A total of 278 complete observations were included in the multivariable models, and significant regional differences were present. For instance, compared to centers in the South, those in the Midwest used neuropsychological testing (OR = 2.87, 95% confidence interval [CI] = 1.2-6.86; p = .018) and fluorodeoxyglucose-positron emission tomography (OR = 2.74, 95% CI = = 1.14-6.61; p = .025) more commonly. For centers in the Northeast (OR = .46, 95% CI = .23-.93; p = .031) and West (OR = .41, 95% CI = .19-.87; p = .022), odds of performing single-photon emission computerized tomography were lower by nearly 50% compared to those in the South. Center accreditation level, demographics, volume, and resources were also associated with varying individual testing rates. SIGNIFICANCE: Presurgical testing for drug-resistant epilepsy is influenced by US geographic region and other center characteristics. These findings have potential implications for comparing outcomes between US epilepsy centers and may inject disparities in access to surgical treatment.

Risk factors for behavioral and psychotic dysregulation at the epilepsy monitoring unit in patients with intracranial electrodes.

OBJECTIVE: Aberrant behavior in patients with epilepsy (PWE) admitted to an epilepsy monitoring unit (EMU) can endanger their safety. We sought to identify predictive factors for post-ictal behavioral dysregulation and psychosis in patients with refractory epilepsy being monitored at an EMU. METHODS: Retrospective data were gathered from electronic patient files of all patients with refractory epilepsy who underwent intracranial registration at our EMU. We assessed behavioral and psychotic dysregulations by reviewing clinical notes, administered emergency medication, and reports of injuries or casualties in patients and nurses. In addition, we compared patient demographic characteristics, clinical characteristics, and antiepileptic drug (AED) profiles between patients with and without behavioral and/or psychotic dysregulation. RESULTS: Out of 73 admissions, 23 patients (32%) experienced behavioral dysregulation, and five patients experienced psychosis (7%). Behavioral dysregulation was only significantly associated with a previous history of interictal or postictal psychosis. Psychotic dysregulation is significantly associated with a psychiatric history, including a history of agitation or psychosis, whether or not epilepsy-related. For both types of dysregulations, there was no relation with a pre-admission frequency of seizures, clustering of seizures during monitoring, or a temporal focus of seizures. We could not report a relationship between AED use, tapering, and the occurrence of dysregulation. CONCLUSION: We conclude that a psychiatric history, including a history of agitation and psychosis, is related to an increased risk of behavioral and psychotic dysregulation in patients undergoing invasive seizure monitoring at the EMU.

Creation of an advancing adult and pediatric neurology resident EEG curriculum.

BACKGROUND: The Accreditation Council for Graduate Medical Education (ACGME) milestones state that neurology residents should be able to "interpret common EEG abnormalities, recognize normal EEG variants, and create a report." Yet, recent studies have shown that only 43% of neurology residents express confidence in interpreting EEG without supervision and can recognize less than half of normal and abnormal EEG patterns. Our objective was to create a curriculum to improve both confidence and competence in reading EEGs. METHODS: At Vanderbilt University Medical Center (VUMC), adult and pediatric neurology residents have required EEG rotations in their first and second years of neurology residency and can choose an EEG elective in their third year. A curriculum consisting of specific learning objectives, self-directed modules, EEG lectures, epilepsy-related conferences, supplemental educational material, and tests was created for each of the three years of training. RESULTS: Since the implementation of an EEG curriculum at VUMC from September 2019 until November 2022, 12 adult and 21 pediatric neurology residents completed pre- and post-rotation tests. Among the 33 residents, there was a statistically significant improvement in post-rotation test scores, with a mean score improvement of 17% (60.0 ± 12.9 to 77.9 ± 11.8, n = 33, p < 0.0001). When differentiated by training, the mean improvement of 18.8% in the adult cohort was slightly higher than in the pediatric cohort, 17.3%, though it was not significantly different. Overall improvement was significantly increased in the junior resident cohort with a 22.6% improvement in contrast to 11.5% in the senior resident cohort (p = 0.0097 by Student's t-test, n = 14 junior residents and 15 senior residents). DISCUSSION: With the creation of an EEG curriculum specific to each year of neurology residency, adult and pediatric neurology residents demonstrated a statistically significant mean improvement between pre- and post-rotation test scores. The improvement was significantly higher in junior residents in contrast to senior residents. Our structured and comprehensive EEG curriculum objectively improved EEG knowledge in all neurology residents at our institution. The findings may suggest a model which other neurology training programs may consider for the implementation of a similar curriculum to both standardize and address gaps in resident EEG education.

Patients with psychogenic nonepileptic seizures and suspected epilepsy: An antiseizure medication reduction study.

OBJECTIVE: To examine predictors of ASM reduction/discontinuation and PNES reduction/resolution in patients with PNES with a confirmed or strong suspicion of comorbid ES. METHODS: A retrospective analysis of 271 newly diagnosed Patients with PNESs admitted to the EMU between May 2000 and April 2008, with follow-up clinical data collected until September 2015. Forty-seven patients met our criteria of PNES with either confirmed or probable ES. RESULTS: Patients with PNES reduction were significantly more likely to have come off all ASMs by the time of final follow-up (21.7 vs. 0.0%, p = 0.018), while documented generalized (i.e. epileptic) seizures were much more common in patients with no reduction in PNES frequency (47.8 vs 8.7%, p = 0.003). When comparing patients that reduced their ASMs (n = 18) with those that did not (n = 27), the former were more likely to have neurological comorbid disorders (p = 0.004). When comparing patients with PNES resolution (n = 12) vs not (n = 34), those with PNES resolution were more likely to have a neurological comorbid disorder (p = 0.027), had a younger age at EMU admission (29.8 vs 37.4, p = 0.05) and a greater proportion of patients with ASMs reduced in EMU (66.7% vs 30.3%, p = 0.028). Similarly, those with ASM reduction had more unknown (non-generalized, non-focal) seizures (33.3 vs 3.7%, p = 0.029). On hierarchical regression analysis, a higher level of education and absence of generalized epilepsy remain as positive predictors of PNES reduction (p = 0.042, 0.015), while the presence of some other neurological disorder besides epilepsy (p = 0.04) and being on more ASMs at EMU admission (p = 0.03) were positive predictors of ASM reduction by final follow-up. SIGNIFICANCE: Patients with PNES and epilepsy have distinct demographic predictors of PNES frequency and ASM reduction by final follow-up. Patients with PNES reduction and resolution had higher level education, less generalized epileptic seizures, younger age at EMU admission, more likely to have presence of a neurological disorder besides epilepsy, and a greater proportion of patients had a reduction in the number of ASMs in the EMU. Similarly, patients with ASM reduction and discontinuation were on more ASMs at initial EMU admission and also were more likely to have a neurological disorder besides epilepsy. The positive relationship between reduction in psychogenic nonepileptic seizure frequency and discontinuation of ASMs at final follow-up elucidates that tapering medication in a safe environment may reinforce psychogenic nonepileptic seizure diagnosis. This can be reassuring to both patients and clinicians, resulting in the observed improvements at the final follow-up.

Does the duration of video-EEG recording influence diagnostic yield in pediatric epilepsy: Results from a single center study.

AIM: This exploratory study examines the association of the duration of electroencephalography (EEG) recordings to diagnostic yield in children undergoing evaluation for seizures. METHOD: Clinical and EEG data on three hundred and ten patients (167 males and 143 females) were reviewed retrospectively. 134 (43.2%) children with focal-onset seizures, and 59 (19%) children with generalized-onset seizures. The mean duration of recordings in studies interpreted as "diagnostic" was compared to studies that were interpreted as "non-diagnostic". EMU recordings were also compared to routine EEG studies to identify the relationship between routine EEG and diagnostic studies. RESULTS: The principal finding of this study indicates that a longer duration of monitoring is more likely to be associated with a positive diagnostic yield. Mean duration of recording in children with a "non-diagnostic study" was 31.05 hours versus 44.27 hours; p < 0.001 in a "diagnostic study". EMU recordings are likely to be diagnostic with longer epilepsy duration (2.6 years vs 3.7 years; p < 0.01). A diagnostic EEG from a prolonged recording is more likely to be achieved in children with abnormal routine EEG and focal-onset seizures. p < 0.001. INTERPRETATION: Tailoring the optimal duration of EEG recordings and factoring in confounding variables will reduce the need for repeated studies, improving diagnostic utility and permitting efficient utilization of resources.

Predicting seizure clustering in the epilepsy monitoring unit: A multivariable analysis.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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). CONCLUSION: 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.

The impact of the time to last seizure before admission to the epilepsy monitoring unit (EMU) on epilepsy classifications.

INTRODUCTION AND BACKGROUND: The impact of the timing of the last seizure (TTLS) prior to admission to the epilepsy monitoring unit (EMU) on epilepsy classification is unclear for which we conducted this study. METHODS: We reviewed patients with epilepsy admitted to EMU between January 2021 and April 2022 and identified TTLS before EMU admission. We considered EMU yield as whether; it confirmed epilepsy classification, added new knowledge to the classification, or failed to classify epilepsy. RESULTS: We studied 156 patients. There were 72 (46%) men, with a mean age of 30. TTLS was divided according to a one- or three-month cutoff. We confirmed the pre-EMU epilepsy classification in 52 (33%) patients, learned new findings on epilepsy classification in 80 (51%) patients, and failed to classify epilepsy in 24 (15%) patients. Patients with "confirmed epilepsy classifications" reported seizures sooner to EMU admission than other groups (0.7 vs. 2.3 months, p-value = 0.02, 95% CI; -1.8, -1.3). Also, the odds of confirming epilepsy classification were more than two times in patients with TTLS within a month compared to those with TTLS of more than a month (OR = 2.4, p-value = 0.04, 95% CI; 1.1, 5.9). The odds were also higher when the 3-month TTLS cutoff was considered (OR = 6.2, p-value = 0.002, 95% CI; 1.6, 40.2). Confirming epilepsy classification was also associated with earlier seizures recorded at one- or three-month cutoff (OR = 2.1 and OR = 2.3, respectively, p-value = 0.05). We did not observe similar findings when we modified the classification or failed to reach a classification. CONCLUSIONS: The timing of the last seizure before EMU admission appeared to influence the yield of EMU and enhanced the confirmation of epilepsy classifications. Such findings can improve the utilization of EMU in the presurgical evaluation of patients with epilepsy.

Retrospective analysis of nurse-administered fall assessment scales in the Epilepsy Monitoring Unit.

INTRODUCTION: Inpatient falls within the Epilepsy Monitoring Unit (EMU) are a common, and potentially preventable adverse event contributing to morbidity for patients living with epilepsy. Accurate fall risk screening is important to identify and efficiently allocate proper safety measures to high-risk patients, especially in EMUs with limited resources. We sought to compare existing screening tools for the ability to predict falls in the EMU. METHODS: This is a retrospective, single-center, case-controlled, comparative analysis of 7 nurse-administered fall risk assessment tools (NAFRAT) of patients admitted to the Vanderbilt University Medical Center (VUMC) EMU. Analysis of categorical data was compared using chi-square analysis while quantitative distributions were compared using student's t-test. RESULTS: A total of 56 patient records (28 falls and 28 controls) were included in the analysis. Epilepsy Monitoring Unit falls were most common within the first 3 days of admission (p = .0094). Pre-admission documentation of falls was a strong predictor of falls within the EMU (p < .0001). Epilepsy Monitoring Unit falls were associated with documented falls after EMU discharge (p = .011). The John Hopkins fall risk assessment tool (JHFRAT) accurately stratified fall risk in the fall group compared to the control (p = .008), however, none of the 7 NAFRATs demonstrated significant categorical differences among the epilepsy subgroups. There was a significant difference in the distribution of quantitative scores, higher in the fall group according to the Morse Fall Scale (MFS) (p = 0.012), JHFRAT (p = 0.003), Schmid Fall Risk Assessment Scale (p = 0.029) and Hester-Davis Scale (p = 0.049). The modified Conley (p = 0.03) and Morse scale (p = 0.025) demonstrated differences in the distribution of quantitative scores in the epilepsy subgroups. CONCLUSION: The findings of this study demonstrate variable accuracy of NAFRATs in assessing fall risk among patients admitted to the EMU, particularly among patients with epilepsy. The findings underscore the need for a validated, EMU-specific, fall assessment tool that accurately stratifies fall risk and inform efficient use of patient-specific fall prevention resources and protocols.

Strategic and principled approach to the ethical challenges of epilepsy monitoring unit triage.

Electroencephalographic monitoring provides critical diagnostic and management information about patients with epilepsy and seizure mimics. Admission to an epilepsy monitoring unit (EMU) is the gold standard for such monitoring in major medical facilities worldwide. In many countries, access can be challenged by limited resources compared to need. Today, triaging admission to such units is generally approached by unwritten protocols that vary by institution. In the absence of explicit guidance, decisions can be ethically taxing and are easy to challenge. In an effort to address this gap, we propose a two-component approach to EMU triage that takes into account the unique landscape of epilepsy monitoring informed by triage literature from other areas of medicine. Through the strategic component, we focus on the EMU wait list management infrastructure at the institutional level. Through the principled component, we apply a combination of the ethical principles of prioritarianism, utilitarianism and justice to triage; and we use individual case examples to illustrate how they apply. The effective implementation of this approach to specific epilepsy centres will need to be customised to the nuances of different settings, including diverse practice patterns, patient populations and constraints on resource distribution, but the conceptual consolidation of its components can alleviate some of the pressures imposed by the complex decisions involved in EMU triage.

[Non-epileptic psychogenic seizures]. / Les crises non épileptiques psychogènes.

Psychogenic non-epileptic seizures resemble epileptic seizures but their pathophysiological mechanisms differ. Despite being quite frequent, they are often misunderstood, regularly leading to a misdiagnosis and therapeutic errors. The objective of this article is to provide a short review of the current knowledge about this pathology. We will detail the main epidemiological data of psychogenic non-epileptic seizures. We will then discuss the diagnostic approach, emphasizing the semiological differences that exist between psychogenic non-epileptic seizures and epileptic seizures. Then, we will detail the main therapeutic actions and discuss the importance of communication between clinicians, the patient and his/her family. Finally, we will discuss the long-term prognosis of this pathology, which remains quite poor.

Les crises non épileptiques psychogènes ressemblent à des crises d'épilepsie, mais leurs mécanismes physiopathologiques diffèrent. Elles sont fréquentes, mais souvent méconnues, menant régulièrement à des erreurs diagnostiques et thérapeutiques. L'objectif de cet article est de dresser une synthèse des connaissances actuelles de cette pathologie. Nous y détaillerons les principales données épidémiologiques des crises non épileptiques psychogènes. Nous aborderons ensuite la démarche diagnostique en insistant sur les différences sémiologiques qui existent entre les crises non épileptiques psychogènes et les crises épileptiques. Nous présenterons ensuite les principales actions thérapeutiques existantes et parlerons de l'importance de la communication entre les cliniciens, le patient et son entourage. Enfin, nous discuterons du pronostic à long terme de cette pathologie, qui reste assez péjoratif.

Seizure count forecasting to aid diagnostic testing in epilepsy.

OBJECTIVE: Epilepsy monitoring unit (EMU) admissions are critical for presurgical evaluation of drug-resistant epilepsy but may be nondiagnostic if an insufficient number of seizures are recorded. Seizure forecasting algorithms have shown promise for estimating the likelihood of seizures as a binary event in individual patients, but methods to predict how many seizures will occur remain elusive. Such methods could increase the diagnostic yield of EMU admissions and help patients mitigate seizure-related morbidity. Here, we evaluated the performance of a state-space method that uses prior seizure count data to predict future counts. METHODS: A Bayesian negative-binomial dynamic linear model (DLM) was developed to forecast daily electrographic seizure counts in 19 patients implanted with a responsive neurostimulation (RNS) device. Holdout validation was used to evaluate performance in predicting the number of electrographic seizures for forecast horizons ranging 1-7 days ahead. RESULTS: One-day-ahead prediction of the number of electrographic seizures using a negative-binomial DLM resulted in improvement over chance in 73.1% of time segments compared to a random chance forecaster and remained >50% for forecast horizons of up to 7 days. Superior performance (mean error = .99) was obtained in predicting the number of electrographic seizures in the next day compared to three traditional methods for count forecasting (integer-valued generalized autoregressive conditional heteroskedasticity model or INGARCH, 1.10; Croston, 1.06; generalized linear autoregressive moving average model or GLARMA, 2.00). Number of electrographic seizures in the preceding day and laterality of electrographic pattern detections had highest predictive value, with greater number of electrographic seizures and RNS magnet swipes in the preceding day associated with a higher number of electrographic seizures the next day. SIGNIFICANCE: This study demonstrates that DLMs can predict the number of electrographic seizures a patient will experience days in advance with above chance accuracy. This study represents an important step toward the translation of seizure forecasting methods into the optimization of EMU admissions.

Epileptic seizures and Epilepsy Monitoring Unit admission disclose latent cardiac electrical instability.

BACKGROUND: Sudden cardiac arrest results from cardiac electrical instability and is 3-fold more frequent in patients with chronic epilepsy than in the general population. We hypothesized that focal to bilateral tonic-clonic seizures (FTBTCS) would acutely impact T-wave alternans (TWA), a marker of cardiac electrical instability linked to an elevated risk for sudden cardiac death, more than focal seizures (FS) [focal aware seizures (FAS) and focal with impaired awareness seizures (FIAS)], due to their greater sympathetic stimulation of the heart. Since stress has been shown to cause significant TWA elevations in patients with heart disease, we also hypothesized that the early days of an inpatient admission to an epilepsy monitoring unit (EMU) would be associated with higher TWA levels compared to later hospital days in patients with chronic epilepsy, presumably due to stress. DESIGN/METHODS: We analyzed the acute effects of seizures [FAS, FIAS, FTBTCS, and nonepileptic seizures (NES)] and day of hospital stay on TWA in 18 patients admitted to the EMU using high-resolution wireless electrocardiographic (ECG) patch monitors. RESULTS: A total of 5 patients had FTBTCS, 7 patients had FS (2 FAS, 5 FIAS), and 3 patients had NES only during the index hospital stay. Four patients did not have any electroclinical seizures or NES. FTBTCS resulted in marked acute increases in ictal TWA from baseline (2 ± 0.3 µV) to ictal maximum (70 ± 6.1 µV, p < 0.0001), the latter exceeding the 60 µV cut point defined as severely abnormal. By comparison, while FAS and FIAS also provoked significant increases in TWA (from 2 ± 0.5 µV to 30 ± 3.3 µV, p < 0.0001), maximum ictal TWA levels did not reach the 47 µV cut point defined as abnormal. Heart rate increases during FTBTCS from baseline (62 ± 5.8 beats/min) to ictal maximum (134 ± 8.6 beats/min, an increase of 72 ± 7.2 beats/min, p < 0.02) were also greater (p = 0.014) than heart rate increases during FS (from 70 ± 5.2 beats/min to 118 ± 6.2 beats/min, an increase of 48 ± 2.6 beats/min, p < 0.03). In 3 patients with NES, TWA rose mildly during the patients' typical episodes (from 2 ± 0.6 µV to 14 ± 2.6 µV, p < 0.0004), well below the cut point of abnormality, while heart rate increases were observed (from 75 ± 1.3 to 112 ± 8.7 beats/min, an increase of 37 ± 8.9 beats/min, p = 0.03). Patients with EEG-confirmed electroclinical seizures recorded while in the EMU exhibited significantly elevated interictal TWA maxima (61 ± 3.4 µV) on EMU admission day which were similar in magnitude to ictal maxima seen during FTBTCS (70 ± 6.1 µV, p = 0.21). During subsequent days of hospitalization, daily interictal TWA maxima showed gradual habituation in patients with both FS and FTBTCS but not in patients with NES only. CONCLUSIONS: This is the first study to our knowledge demonstrating that FTBTCS acutely provoke highly significant increases in TWA to levels that have been associated with heightened risk for sudden cardiac death in other patient populations. We speculate that mortality temporally associated with FTBTCS may, in some cases, be due to sudden cardiac death rather than respiratory failure. In patients with EEG-confirmed epilepsy, hospital admission is associated with interictal TWA maxima that approach those seen during FTBTCS, presumably related to stress during the early phase of hospitalization compared to later in the hospitalization, indicating cardiac electrical instability and potential vulnerability to sudden cardiac death related to stress independent of temporal relationships to seizures. The elevated heart rates observed acutely with seizures and on hospital Day 1 are consistent with a hyperadrenergic state and the effect of elevated sympathetic output on a vulnerable cardiac substrate, a phenomenon termed "the Epileptic Heart."

Characterizing the driving dilemma among patients with psychogenic nonepileptic seizures: A single-center prospective cohort study.

OBJECTIVE: Driving is a critical topic to counsel among patients with epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES), with significant legal and public health implications. This prospective cohort study examined the frequency of ES and PNES in a single institution's Epilepsy Monitoring Unit (EMU) and assessed driving-related issues between each group. METHODS: Adult patients from the Mayo Clinic Arizona Epilepsy Monitoring Unit (EMU) were given comprehensive surveys addressing driving history. Descriptive analysis and statistics were used to summarize differences between patients with ES and PNES. Differences between patients with epilepsy and PNES were determined by Pearson chi-square. RESULTS: Nearly half (n = 75/163) of all patients admitted to the EMU were diagnosed with PNES. Although the PNES group had a statistically significant higher frequency of events (p = 0.01), 87.7% of these patients reported compliance with the driving law recommendations, suggesting a trend that patients who have been counseled regarding fitness-to-drive are likely to follow the recommendation. One-third of patients with PNES reported an event while operating a motor vehicle and 8% (n = 2/25) resulted in a motor vehicle collision severe enough to require hospitalization. In contrast to those with ES, 25% of patients reported a typical event while driving and 25% (n = 2/8) of those resulted in a collision requiring hospitalization. The incidence of habitual events while driving is higher in the population with PNES (n = 25) when compared to those with ES (n = 8); however, it appears that patients with PNES were less likely to become involved in an accident resulting in seriously bodily injury than in ES. CONCLUSIONS: Compared to patients with PNES, patients with ES have less frequent events but more severe collisions. This study reinforces the need for diligent driving counseling to help prevent driving-related injuries in patients with PNES and ES.

Duration of postictal impaired awareness after bilateral tonic-clonic seizures: EEG and patient characteristics.

OBJECTIVE: Ictal and postictal phenomena that may impact the duration of postictal impaired awareness have not been well studied. Postictal unresponsiveness invariably occurs following bilateral tonic-clonic seizures (BTCS). Bilateral tonic-clonic seizures are a major risk factor for sudden unexpected death in epilepsy (SUDEP). We quantify the effects of seizure characteristics on postictal recovery of awareness following BTCS. Factors include: the total seizure duration, the duration of the tonic phase of a BTCS, presence of postictal generalized EEG suppression (PGES), duration of postictal tonic electromyographic discharge, peri-ictal respiratory dysfunction, patient age, duration of epilepsy, and gender. METHODS: Fifty-eight patients admitted to the epilepsy monitoring unit with BTCS were studied. Forty-one had unilateral onset temporal seizures. The remainder had bitemporal onsets, extratemporal onsets, undetermined onsets, or were generalized at onset. Following the first BTCS, time to initial recovery of awareness and its possible association with patient and seizure characteristics as well as peri-ictal respiratory dysfunction were evaluated. The presence or absence of postictal agitation was noted. RESULTS: The severity of respiratory dysfunction and seizure characteristics were not associated with time to initial recovery of awareness. A shorter time to recovery of awareness was significantly associated with a younger age (p = 0.007). Postictal agitation was more common in males (p = 0.023). SIGNIFICANCE: Focal seizures may impair awareness by active inhibition of subcortical arousal mechanisms. Focal seizures progressing to bilateral tonic-clonic seizures (BTCS) result in further widespread cerebral dysfunction impacting postictal awareness. MRI studies show accelerated brain aging in patients with temporal lobe epilepsy. Our findings suggest that patient age, as a surrogate marker for the lifetime burden of seizures, results in a progressive worsening in time to recovery after BTCS by an increasing negative impact on networks involved in arousal.

Do all patients in the epilepsy monitoring unit experience the same level of comfort? A quantitative exploratory secondary analysis.

AIMS: To find out which variables may be associated with comfort of patients in an epilepsy monitoring unit. DESIGN: Exploratory, quantitative study design. METHODS: Data were collected from October 2018 to November 2019 in Austria and Southern Germany. A total of 267 patients of 10 epilepsy centres completed the Epilepsy Monitoring Unit Comfort Questionnaire which is based on Kolcaba's General Comfort Questionnaire. Secondary data analysis were conducted by using descriptive statistics and an exploratory model building approach, including different linear regression models and several sensitivity analyses. RESULTS: Total comfort scores ranged from 83 to 235 points. Gender, occupation and centre turned out to be possible influential variables. On average, women had a total comfort score 4.69 points higher than men, and retired persons 28.2 points higher than high school students ≥18 years. Comfort scores of younger patients were lower than those of older patients. However, age did not show a statistically significant effect. The same could be observed in marital status and educational levels. CONCLUSION: When implementing comfort measures, nurses must be aware of variables which could influence the intervention negatively. Especially, high school students ≥18 years should be supported by epilepsy specialist nurses, in order to reduce uncertainty, anxiety and discomfort. But, since the identified variables account only for a small proportion of the inter-individual variability in comfort scores, further studies are needed to find out additional relevant aspects and to examine centre-specific effects more closely. IMPACT: Nurses ensure patient comfort during a hospital stay. However, there are variables that may impair the effectiveness of the nursing measures. Our study showed that the experience of comfort was highly individual and could be explained by sociodemographic variables only to a limited extent. Nurses must be aware that additional factors, such as the situation in the individual setting, may be relevant.

Emergency department visits and readmissions in patients with psychogenic nonepileptic seizures (PNES) at a safety net hospital.

INTRODUCTION: Readmissions and emergency department (ED) visits after an index admission have been become a quality measure due to associations with poor outcomes and increased healthcare costs. Readmissions and ED encounters have been studied in a variety of conditions including epilepsy but have not been examined exclusively in psychogenic nonepileptic seizures (PNES). In this study we examined the rate of readmissions and ED visits after a discharge from an Epilepsy Monitoring Unit (EMU) in a safety net hospital. We also determined patient phenotypes that are associated with readmissions. MATERIAL AND METHODS: This was a retrospective chart review study with index admission being a discharge from an EMU between January 1 and December 31 2016 with follow-up until August 31 2020. We obtained data regarding demographics, medical and psychiatric history, and social history and treatment interventions. Our outcome variables were both all-cause and seizure-related hospital readmissions and ED visits 30 days following the index discharge and readmissions and ED visits 30 days thereafter. RESULTS: Eleven of 122 patients (9%) had a non-seizure-related ED visit and/or hospitalization within 30 days of index discharge while 45 (37%) had re-contact with the health system thereafter for non-seizure-related issues. Seven of 122 patients (6%) had a seizure-related ED visit or hospital readmission within 30 days of discharge. Twenty-eight (23%) had a seizure-related readmission or ED visit after 30 days. Of these 28, 4 patients had been to an ER within 7 days of EMU discharge. The majority of subsequent encounters with the healthcare system were through the ED (n = 38) as compared to hospital (n = 10) and EMU readmissions (n = 9). On bivariate statistical analysis, charity or self-pay insurance status (p < 0.01), homelessness (p < 0.01), emergent EMU admission on index admission (p < 0.01), history of a psychiatric diagnosis (p < 0.02), and ED encounters 12 months prior to admission (p < 0.01) were significantly associated with readmission; however, on multivariate analysis only charity insurance status was a significant predictor. CONCLUSIONS: In this study of readmissions and ED visits after discharge with a diagnosis of PNES at a safety net hospital, we found a seizure-related readmission rate of approximately 6% in 30 days and 23% thereafter with the majority of re-contact with the hospital being in the ED. On multi-variate analysis insurance status was a significant factor associated with readmission and ED visits. Our future research directions include examining referrals and treatment completion at the hospital's PNES clinic as well as creating a risk score to better identify patients with PNES at risk of readmission.

The safety and efficacy of modifying the admission protocol to the epilepsy monitoring unit in response to the COVID-19 pandemic.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has impacted admission to epilepsy monitoring units (EMUs) for classification and presurgical evaluation of patients with refractory epilepsy. We modified the EMU admission protocol via anti-seizure medications (ASM) withdrawal implemented one day before admission; thus, we aimed to evaluate the efficacy and safety of this modified protocol. METHODS: In January 2021, we initiated ASM tapering 24 h before-rather than on the first day after-EMU admission, contrasting with the previous protocol. We retrospectively reviewed EMU admissions between January and April of 2018, 2019, and 2021, and identified the time required to record the first seizure, and EMU yield to confirm or change the epilepsy classification. We also evaluated the safety of the modified protocol, by monitoring the seizure frequency for up to 5 months after the discharge from the hospital. RESULTS: One hundred four patients were included (mean age: 30 years, men: 43%); excluding a longer disease duration and abundance of normal routine electro-encephalogram (EEG) in patients admitted before the pandemic, no differences were observed in patients' characteristics. On average, it took 41 h and 21 h to record the first seizure using the standard and modified protocols, respectively (p < 0.001, 95% CI: 10-30). Other characteristics were investigated both before and after the COVID-19 pandemic, and epilepsy classifications were confirmed twice using the modified protocol (OR = 2.4, p = 0.04, 95% CI: 1.1-5.5). Multivariate regression analysis confirmed the shorter time to record the first seizure using the modified admission protocol (23 h less, p < 0.001; 95% CI: 12-34). Finally, 36 (86%) patients admitted during the pandemic exhibited no increase in seizure frequency after the discharge from the hospital. CONCLUSIONS: Initiating ASM withdrawal one day before EMU admission was deemed to be an efficient and safe way to confirm epilepsy classification and significantly decrease the length of hospital stay. Ultimately, this will shorten the long waiting list for EMU admission created by the COVID-19 pandemic.