Enhanced sensitivity of electrocorticography during awake craniotomy using a novel circular grid electrode.

PURPOSE: Awake craniotomy with intraoperative functional brain mapping (FBM) bedside neurological testing is an important technique used to optimize resective brain surgeries near eloquent cortex. Awake craniotomy performed with electrocorticography (ECoG) and direct electrical stimulation (DES) for FBM can delineate eloquent cortex from lesions and epileptogenic regions. However, current electrode technology demonstrates spatial limitations. Our group has developed a novel circular grid with the goal of improving spatial recording of ECoG to enhance detection of ictal and interictal activity. METHODS: This retrospective study was approved by the institutional review board at Mayo Clinic Florida. We analyzed patients undergoing awake craniotomy with ECoG and DES and compared ECoG data obtained using the 22 contact circular grid to standard 6 contact strip electrode. RESULTS: We included 144 cases of awake craniotomy with ECoG, 73 using circular grid and 71 with strip electrode. No significant differences were seen regarding preoperative clinical and demographic data, duration of ECoG recording (p = 0.676) and use of DES (p = 0.926). Circular grid was more sensitive in detecting periodic focal epileptiform discharges (PFEDs) (p = 0.004), PFEDs plus (p = 0.032), afterdischarges (ADs) per case (p = 0.022) at lower minimum (p = 0.012) and maximum (p < 0.0012) intensity stimulation, and seizures (p = 0.048). PFEDs (p < 0.001), PFEDs plus (p < 0.001), and HFOs (p < 0.001) but not ADs (p = 0.255) predicted electrographic seizures. CONCLUSION: We demonstrate higher sensitivity in detecting ictal and interictal activity on ECoG during awake craniotomy with a novel circular grid compared to strip electrode, likely due to better spatial sampling during ECoG. We also found association between PFEDs and intraoperative seizures.

Behavioral adverse events with brivaracetam, levetiracetam, perampanel, and topiramate: A systematic review.

PURPOSE: To understand the currently available post-marketing real-world evidence of the incidences of and discontinuations due to the BAEs of irritability, anger, and aggression in people with epilepsy (PWE) treated with the anti-seizure medications (ASMs) brivaracetam (BRV), levetiracetam (LEV), perampanel (PER), and topiramate (TPM), as well as behavioral adverse events (BAEs) in PWE switching from LEV to BRV. METHODS: A systematic review of published literature using the Cochrane Library, PubMed/MEDLINE, and Embase was performed to identify retrospective and prospective observational studies reporting the incidence of irritability, anger, or aggression with BRV, LEV, PER, or TPM in PWE. The incidences of these BAEs and the rates of discontinuation due to each were categorized by ASM, and where possible, weighted means were calculated but not statistically assessed. Behavioral and psychiatric adverse events in PWE switching from LEV to BRV were summarized descriptively. RESULTS: A total of 1500 records were identified in the searches. Of these, 44 published articles reporting 42 studies met the study criteria and were included in the data synthesis, 7 studies were identified in the clinical trial database, and 5 studies included PWE switching from LEV to BRV. Studies included a variety of methods, study populations, and definitions of BAEs. While a wide range of results was reported across studies, weighted mean incidences were 5.6% for BRV, 9.9% for LEV, 12.3% for PER, and 3.1% for TPM for irritability; 3.3%* for BRV, 2.5% for LEV, 2.0% for PER, and 0.2%* for TPM for anger; and 2.5% for BRV, 2.6% for LEV, 4.4% for PER, and 0.5%* for TPM for aggression. Weighted mean discontinuation rates were 0.8%* for BRV, 3.4% for LEV, 3.0% for PER, and 2.2% for TPM for irritability and 0.8%* for BRV, 2.4% for LEV, 9.2% for PER, and 1.2%* for TPM for aggression. There were no discontinuations for anger. Switching from LEV to BRV led to improvement in BAEs in 33.3% to 83.0% of patients (weighted mean, 66.6%). *Denotes only 1 study. CONCLUSIONS: This systematic review characterizes the incidences of irritability, anger, and aggression with BRV, LEV, PER, and TPM, and it provides robust real-world evidence demonstrating that switching from LEV to BRV may improve BAEs. While additional data remain valuable due to differences in methodology (which make comparisons difficult), these results improve understanding of the real-world incidences of discontinuations due to these BAEs in clinical practice and can aid in discussions and treatment decision-making with PWE.

Innovative approaches reaching underserved and rural communities to improve epilepsy care: A review of the methodology of the Connectors Project.

OBJECTIVE: The Connectors Project, a collaboration between the Epilepsy Foundation and UCB Pharma, was a multiyear project designed to improve epilepsy care in underserved communities. A core objective of the Connectors Project was to pilot new and innovative approaches to epilepsy awareness and education in rural and underserved areas, including standardized curricula for healthcare providers and patients. METHODS: A series of consensus conferences explored opportunities and barriers to epilepsy care throughout the United States including access to local Epilepsy Foundations, neurologists, and epilepsy centers. Data from QuintilesIMS™ were examined for access to newer antiepileptic drugs (AEDs)-a proxy for quality of epilepsy care-in different regions. State factors (e.g., local epilepsy foundation office, access to newer vs. older AEDs, and geographic density and diversity) were used in selecting four states as examples of rural and underserved areas to pilot the awareness and educational programs. For each state, a work team assessed challenges and opportunities, tailored educational curricula, and developed strategies for effective delivery of the educational programs. Interventions were held between June 2016 and June 2017. Interventions consisted of outreach and awareness programs, in-person health education to healthcare providers and patients/families, and digital health education. RESULTS: Michigan, Nevada, Oklahoma, and West Virginia were identified as pilot states representing geographically diverse areas, ranging from a state with a large high-density population center with several epilepsy centers and a local Epilepsy Foundation office (Michigan) to a state with predominately rural areas and a few small urban cores, two epilepsy centers, and no in-state Epilepsy Foundation office (West Virginia). State work teams tailored interventions and examined options for type, intent, ease of use, and impact. All states implemented outreach and awareness initiatives and in-person health education for patients and healthcare providers; use of digital health education was variable. Measurement of the interventions was agreed to be performed by the use of patient and physician surveys and reevaluation of data from QuintilesIMS for access to newer AEDs. CONCLUSION: Local Epilepsy Foundation offices successfully connected healthcare providers in rural and underserved areas to epilepsy education designed to enhance quality care in epilepsy. Educational opportunities for people with epilepsy and their families addressed critical gaps in accessing quality epilepsy care and self-management. Tailored and innovative educational approaches can be used to increase awareness levels and to overcome geographic challenges in reaching underserved populations. Relationship building and repeated, consistent engagement with healthcare providers and patients can assist in improving communication and self-management skills among patients with epilepsy.

Current state of the union of epilepsy care in the United States: Antiepileptic drugs - An introduction to the Connectors Project.

PURPOSE: How antiepileptic drugs (AEDs) are used in the United States (US) is one proxy public health indicator for the current state of epilepsy management. The use of phenytoin, other older AEDs, and newer AEDs may act as an indicator for the quality of epilepsy practice in addition to the current American Academy of Neurology quality measures. Data on AED used by states and populations can help identify which public health interventions are necessary to improve the status of epilepsy care. The Connectors Project, a collaboration between the Epilepsy Foundation and UCB Pharma, is a multiyear project designed to improve epilepsy awareness and management in underserved communities. The objective of the first phase of the Connectors Project was to assess geographic variation in epilepsy care and identify locations in need of improved epilepsy care by initially evaluating AED use in the US. METHODS: A retrospective cross-sectional administrative claim analysis was conducted using the QuintilesIMS™ database which included US longitudinal retail prescription and office medical claims data. Patients with a confirmed epilepsy diagnosis who were prescribed AEDs were identified. Patients with an AED prescription over a 3-year period from January 2013 to December 2015 were included if they had an epilepsy diagnosis in the 2-year period before their first AED prescription in the reporting period. The percentages of patients initially prescribed phenytoin, other older AEDs (carbamazepine and valproate), and newer AEDs (eslicarbazepine, lacosamide, lamotrigine, levetiracetam, oxcarbazepine, perampanel, topiramate) were calculated and stratified by US state and Washington, DC. Patients were considered newly treated if they had an epilepsy diagnosis code and had not received an epilepsy drug in the 1-year period preceding the first AED prescription in the reporting period. Data are reported using the moving annual total ending December 2015. RESULTS: Approximately 2.5 million US patients with epilepsy and their AED prescriptions were identified from 2013 to 2015. Predictably, states with the largest population had the highest number of patients with epilepsy who were prescribed an AED, including California, Texas, Florida, and New York. Regions with the highest total proportion of phenytoin use with a low proportion of newer AED use were Mississippi (24.4% and 53.1%, respectively) and Washington, DC (24.7% and 58.1%). Montana had the lowest proportion of phenytoin use with the highest proportion of newer AED use (7.9% and 70.4%). Among newly treated patients (N=237,347), Hawaii (39.1%) and Alaska (38.8%) had the highest percentage of phenytoin use compared with all other states. Idaho (86.1%) and Montana (84.4%) had the highest proportion of newer AED use. Washington, DC (50.9%) and Hawaii (60.9%) had the lowest proportion of patients treated with newer AEDs. North Dakota (29.6%) and Washington, DC (27.9%) had the highest rates of other older AEDs use. CONCLUSIONS: A substantial proportion of newly treated US patients with epilepsy are underserved regarding newer AED use with Mississippi and Washington, DC having the highest proportion of phenytoin use relative to newer AED use. Understanding the socioeconomic and demographic barriers for these observations is essential in planning interventions to improve the quality of life and care for patients with epilepsy, including newly treated patients. These data provide a baseline to target educational and clinical interventions for improving the quality of US epilepsy care.

Usage of EpiFinder clinical decision support in the assessment of epilepsy.

BACKGROUND: The diagnosis of epilepsy is at times elusive for both neurologists and nonneurologists, resulting in delays in diagnosis and therapy. The development of screening methods has been identified as a priority in response to this diagnostic and therapeutic gap. EpiFinder is a novel clinical decision support tool designed to enhance the process of information gathering and integration of patient/proxy respondent data. It is designed specifically to take key terms from a patient's history and incorporate them into a heuristic algorithm that dynamically produces differential diagnoses of epilepsy syndromes. OBJECTIVE: The objective of this study was to test the usability and diagnostic accuracy of the clinical decision support application EpiFinder in an adult population. METHODS: Fifty-seven patients were prospectively identified upon admission to the Epilepsy Monitoring Unit (EMU) for episode classification from January through June of 2017. Based on semiologic input, the application generates a list of epilepsy syndromes. The EpiFinder-generated diagnosis for each subject was compared to the final diagnosis obtained via continuous video electroencephalogram (cVEEG) monitoring. RESULTS: Fifty-three patients had habitual events recorded during their EMU stay. A diagnosis of epilepsy was confirmed (with cVEEG monitoring) in 26 patients while 27 patients were found to have a diagnosis other than epilepsy. The algorithm appropriately predicted differentiation between the presence of an epilepsy syndrome and an alternative diagnosis with 86.8% (46/53 participants) accuracy. EpiFinder correctly identified the presence of epilepsy with a sensitivity of 86.4% (95% confidence interval [CI]: 65.0-97.1) and specificity of 85.1% (95% CI: 70.2-96.4). CONCLUSION: The initial testing of the EpiFinder algorithm suggests possible utility in differentiating between an epilepsy syndrome and an alternative diagnosis in adult patients.

Diagnostic utility of the Minnesota Multiphasic Personality Inventory-2 Restructured Form in the epilepsy monitoring unit: Considering sex differences.

Psychological assessment measures are frequently used to evaluate patients in epilepsy monitoring units. One goal of that assessment is to contribute information that may help with differential diagnosis between epilepsy and psychogenic nonepileptic seizures (PNES). The Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) is one such measure. Del Bene et al. (2017) recently published an analysis that was the first to compare MMPI-2-RF scale elevations between diagnostic groups stratified by sex. The purpose of the present study was to replicate that analysis in a larger sample. Similar to previous work, we found that both men and women with PNES were more likely than men and women with epilepsy to report high levels of somatic complaints (2 to 5 times greater odds of somatic symptom reporting) and a variety of types of complaints. Mood disturbance scales were not significantly elevated in our PNES sample. Results contribute to the small body of research on sex differences in patients with PNES and suggest that somatization is a key characterization across sexes.

Social factors in marijuana use for medical and recreational purposes.

Of all the various treatment options for epilepsy, no other therapy comes close to the polarity that cannabis engenders. The rationale for this reaction is firmly rooted in the social factors that enshroud the use of marijuana for both medical and recreational purposes. In order to best understand how to approach this controversial treatment, it is essential to explore the social, demographic, and historical variables that have led to the current opinions on cannabis therapy and how this has converged on epilepsy treatment. Utilizing a sociological conceptual framework, this review discusses in depth the social, cultural, and historical dimensions of cannabis use in the US for medical purposes and its impact on epilepsy treatment. Moreover, it posits that cannabis therapy and the opinions surrounding its use are products of history and assesses this treatment option through the lens of our current times. This article is part of a Special Issue titled Cannabinoids and Epilepsy.

Historical perspective on the medical use of cannabis for epilepsy: Ancient times to the 1980s.

There has been a dramatic surge in the interest of utilizing cannabis for epilepsy treatment in the US. Yet, access to cannabis for research and therapy is mired in conflicting regulatory policies and shifting public opinion. Understanding the current state of affairs in the medical cannabis debate requires an examination of the history of medical cannabis use. From ancient Chinese pharmacopeias to the current Phase III trials of pharmaceutical grade cannabidiol, this review covers the time span of cannabis use for epilepsy therapy so as to better assess the issues surrounding the modern medical opinion of cannabis use. This article is part of a Special Issue titled Cannabinoids and Epilepsy.

Fall prevention and bathroom safety in the epilepsy monitoring unit.

Falls are one of the most common adverse events occurring in the epilepsy monitoring unit (EMU) and can result in significant injury. Protocols and procedures to reduce falls vary significantly between institutions as it is not yet known what interventions are effective in the EMU setting. This study retrospectively examined the frequency of falls and the impact of serial changes in fall prevention strategies utilized in the EMU between 2001 and 2014 at a single institution. Overall fall rate was 2.81 per 1000 patient days and varied annually from 0 to 9.02 per 1000 patient days. Both seizures and psychogenic nonepileptic events occurring in the bathroom were more likely to result in falls compared with events occurring elsewhere in the room. With initiation of increased patient education, hourly nurse rounding, nocturnal bed alarms, having two persons assisting for high fall risk patients when out of bed, and immediate postfall team review between 2001 and 2013, there was a trend of decreasing fall frequency; however, no specific intervention could be identified as having a particular high impact. In late 2013, a ceiling lift system extending into the bathroom was put in place for use in all EMU patients when out of bed. In the subsequent 15 months, there have been zero falls. The results reinforce both the need for diligent safety standards to prevent falls in the EMU as well as the challenges in identifying the most effective practices to achieve this goal.

Quality of life in psychogenic nonepileptic seizures and epilepsy: the role of somatization and alexithymia.

It is clear that many individuals with psychogenic nonepileptic seizures (PNESs) often present with poorer quality of life compared with those with epileptic seizures (ESs). However, the mechanisms linking seizure diagnosis to quality-of-life outcomes are much less clear. Alexithymia and somatization are emotional markers of psychological functioning that may explain these differences in quality of life. In the current study, patients from an epilepsy monitoring unit with vEEG-confirmed diagnosis of PNESs or ESs were compared on measures of alexithymia, somatization, quality of life, and a variety of demographic and medical variables. Two models using alexithymia and somatization individually as mediators of the relations between diagnosis and quality of life were tested. Results indicated that patients with PNESs had significantly poorer quality of life compared with those with ESs. Alexithymia was associated with poor quality of life in both groups but did not differentiate between diagnostic groups. Further, alexithymia did not mediate the relationship between diagnosis and quality of life. Somatization was associated with poor quality of life, and patients with PNESs reported greater somatization compared with patients with ESs. Somatization also significantly mediated the relationship between diagnosis and quality of life. In conclusion, somatization may be one mechanism affecting poor quality of life among patients with PNESs compared with ESs and should be a target of comprehensive treatments for PNESs. Alexithymia proved to be an important factor impacting quality of life in both groups and should also be targeted in treatment for patients with PNESs and patients with ESs.

Research implications of the Institute of Medicine Report, Epilepsy Across the Spectrum: Promoting Health and Understanding.

In March 2012 the Institute of Medicine (IOM) released the report, Epilepsy Across The Spectrum: Promoting Health and Understanding. This report examined the public health dimensions of the epilepsies with a focus on the following four areas: public health surveillance and data collection and integration; population and public health research; health policy, health care, and human services; and education for providers, people with epilepsy and their families, and the public. The report provided recommendations and research priorities for future work in the field of epilepsy that relate to increasing the power of data on epilepsy; prevention of epilepsy; improving health care for people with epilepsy; improving health professional education about epilepsy; improving quality of life for people with epilepsy; improving education about epilepsy for people with epilepsy and families; and raising public awareness about epilepsy. For this article, the authors selected one research priority from each of the major chapter themes in the IOM report: expanding and improving the quality of epidemiologic surveillance in epilepsy; developing improved interventions for people with epilepsy and depression; expanding early identification/screening for learning impairments in children with epilepsy; evaluating and promoting effective innovative teaching strategies; accelerating research on the identification of risk factors and interventions that increase employment and improve quality of life for people with epilepsy and their families; assessing the information needs of people with epilepsy and their families associated with epilepsy-related risks, specifically sudden unexpected death in epilepsy; and developing and conducting surveys to capture trends in knowledge, awareness, attitudes, and beliefs about epilepsy over time and in specific population subgroups. For each research priority selected, examples of research are provided that will advance the field of epilepsy and improve the lives of people with epilepsy. The IOM report has many other research priorities for researchers to consider developing to advance the field of epilepsy and better the lives of people with epilepsy.

The evolution of antiseizure medication therapy selection in adults: Is artificial intelligence -assisted antiseizure medication selection ready for prime time?

Antiseizure medications (ASMs) are the mainstay of symptomatic epilepsy treatment. The primary goal of pharmacotherapy with ASMs in epilepsy is to achieve complete seizure remission while minimizing therapy-related adverse events. Over the years, more ASMs have been introduced, with approximately 30 now in everyday use. With such a wide variety, much guidance is needed in choosing ASMs for initial therapy, subsequent replacement monotherapy, or adjunctive therapy. The specific ASMs are typically tailored by the patient's related factors, including epilepsy syndrome, age, sex, comorbidities, and ASM characteristics, including the spectrum of efficacy, pharmacokinetic properties, safety, and tolerability. Weighing these key clinical variables requires experience and expertise that may be limited. Furthermore, with this approach, patients may endure multiple trials of ineffective treatments before the most appropriate ASM is found. A more reliable way to predict response to different ASMs is needed so that the most effective and tolerated ASM can be selected. Soon, alternative approaches, such as deep machine learning (ML), could aid the individualized selection of the first and subsequent ASMs. The recognition of epilepsy as a network disorder and the integration of personalized epilepsy networks in future ML platforms can also facilitate the prediction of ASM response. Augmenting the conventional approach with artificial intelligence (AI) opens the door to personalized pharmacotherapy in epilepsy. However, more work is needed before these models are ready for primetime clinical practice.

Intraoperative electrocorticography during laser-interstitial thermal therapy predicts seizure outcome in mesial temporal lobe epilepsy.

OBJECTIVE: Magnetic resonance-guided laser interstitial thermal therapy (MRLiTT) for treating temporal lobe epilepsy has recently gained popularity. We aimed to investigate the predictive value of pre-and post-MRLiTT epileptiform discharges (EDs) on intraoperative electrocorticography (iECoG) in seizure outcomes for patients with mesial temporal lobe epilepsy (mTLE). METHODS: We conducted a pilot, prospective single-center cohort study on seven consecutive patients with mTLE that underwent MRLiTT. Pre- and post-MRLiTT iECoG was performed using a 1x8 contact depth electrode along the same trajectory used for the laser catheter. RESULTS: The responders had a robust reduction in ED frequency compared to pre-MRLiTT iECoG (86% vs 13%, p < 0.01). Clinical characteristics, including risk factors for epilepsy, duration of epilepsy, presence of mesial temporal lobe sclerosis, prior intracranial monitoring, the absolute frequency of pre- or post-MRLiTT EDs, and ablation volume were not significantly associated with responder status. CONCLUSIONS: This is the first demonstration that intraoperative reduction in EDs during mesial temporal lobe MRLiTT may potentially predict seizure outcomes and may serve as an intraoperative biomarker for satisfactory ablation. However, larger prospective studies are needed to confirm our findings and evaluate the utility of iECoG during MRLiTT. SIGNIFICANCE: iECoG during mesial temporal lobe MRLiTT may help assess seizure outcomes.

Risk factors for preoperative and postoperative seizures in patients with glioblastoma according to the 2021 World Health Organization classification.

OBJECTIVE: To identify risk factors for developing glioblastoma (GBM) related preoperative (PRS) and postoperative seizures (POS). Also, we aimed to analyze the impact of PRS and POS on survival in a GBM cohort according to the revised 2021 WHO glioma classification. METHODS: We performed a single-center retrospective cohort study of patients with GBM (according to the 2021 World Health Organization Classification) treated at Mayo Clinic Florida between January 2018 and July 2022. Seizures were stratified into preoperative seizures (PRS) and postoperative seizures (POS, >7 days after surgery). Associations between patients' characteristics and overall survival with PRS and POS were assessed. RESULTS: One hundred nineteen adults (mean =60.9 years), 49 (41.2 %) females, were identified. The rates of PRS and POS in the cohort were 35.3 % (n = 42) and 37.8 % (n = 45), respectively. Patients with PRS were younger (p = 0.035) and were likely to undergo intraoperative electrocorticography. The incidence of PRS (p = 0.049) and POS (p<0.001) was lower among patients with tumors located in the occipital location. PRS increased the risk of POS after adjusting for age and sex (RR: 2.59, CI = 1.44-4.65, p = 0.001). There was no association between PRS or POS and other patient-related factors, including several tumor molecular markers (TMMs) examined. PRS (p = 0.036), POS (p<0.001), and O6-Methylguanine-DNA Methyltransferase (MGMT) promotor methylation status (p = 0.032) were associated with longer survival time. CONCLUSIONS: PRS and POS are associated with non-occipital tumor location and longer survival time in patients with GBM. While younger ages predicted PRS, PRS predicted POS. Well-designed prospective studies with larger sample sizes are needed to clarify the influence of TMMs in the genesis of epileptic seizures in patients with GBM.

The influence of impression management scales on the Personality Assessment Inventory in the epilepsy monitoring unit.

The Somatic Complaints scale (SOM) and Conversion subscale (SOM-C) of the Personality Assessment Inventory perform best in classifying psychogenic non-epileptic seizures (PNES) from epileptic seizures (ES); however, the impact of positive impression management (PIM) and negative impression management (NIM) scales on SOM and SOM-C classification has not been examined. We studied 187 patients from an epilepsy monitoring unit with confirmed PNES or ES. On SOM, the best cut score was 72.5 T when PIM was elevated and 69.5 T when there was no bias. On SOM-C, when PIM was elevated, the best cut score was 67.5 T and 76.5 T when there was no bias. Negative impression management elevations (n=9) were too infrequent to analyze separately. Despite similarities in classification accuracy, there were differences in sensitivity and specificity with and without PIM, impacting positive and negative predictive values. The presence of PIM bias generally increases positive predictive power of SOM and SOM-C but decreases negative predictive power.

Association of intracranial abnormalities with the development of epilepsy and drug-resistant epilepsy in patients with Parry-Romberg syndrome.

BACKGROUND: Epilepsy represents an essential component of Parry Romberg syndrome (PRS). This study aimed to identify clinical factors that influence the development of epilepsy and drug-resistant epilepsy (DRE) in PRS. METHODS: We retrospectively reviewed the medical records of eighty patients with PRS. Data including the age of onset for PRS, history of seizures, use and timing of immunotherapy, antiseizure medication use, and EEG and brain imaging findings were reviewed. For comparison with the patients with epilepsy (PRSe+) group, we selected 18 age and sex-matched controls from the patient without epilepsy (PRSe-) cohort using propensity score matching. RESULTS: Eighteen (22.5%) had epilepsy: 12 were female, and the median age was 14.5 years (range = 6-48 years). Eleven patients developed DRE. The median latency between the onset of cutaneous manifestations and diagnosis and timing and use of immunotherapy was similar between the PRSe + and PRSe- groups. Intracranial abnormalities were commonly seen in the PRSe + group (16 vs. 2, p < 0.01). White matter disease and ipsilateral atrophy were common among the PRSe + group. Timing and use of immunotherapy, epileptiform discharges, and brain imaging abnormalities did not differ between those with DRE and without. CONCLUSIONS: The presence and degree of severity of ipsilateral brain abnormalities are risk factors for the development of epilepsy in PRS but not factors in predicting drug resistance. The timing of immunotherapy did not influence the development of PRSe + or DRE. Prospective studies are needed to identify biomarkers for epilepsy and assess the role of immunotherapy on seizure outcomes in PRSe + .

Iatrogenic seizures during intracranial EEG monitoring.

Cerebral edema with declining neurologic status is a known complication of intracranial electroencephalography (EEG) monitoring. The frequency and consequences of iatrogenic edema that is not clinically evident are presently poorly defined. We investigated the potential for intracranial electrodes to cause subclinical cerebral edema, and for such edema to cause iatrogenic seizures. In a retrospective review of 33 adults who had head magnetic resonance imaging (MRI) while undergoing epilepsy surgery evaluation with intracranial EEG, 28% (6 of 21) depth electrode implantations had subclinical vasogenic edema. Of these, 50% (3 of 6) had nonhabitual electrographic seizures that appear to result from iatrogenic edema. No long-term adverse sequelae were noted, however, if unrecognized, iatrogenic seizures could lead to unnecessary exclusion from definitive surgical intervention for refractory epilepsy.

Code blue: seizures.

Eyewitnesses frequently perceive seizures as life threatening. If an event occurs on the hospital premises, a "code blue" can be called which consumes considerable resources. The purpose of this study was to determine the frequency and characteristics of code blue calls for seizures and seizure mimickers. A retrospective review of a code blue log from 2001 through 2008 identified 50 seizure-like events, representing 5.3% of all codes. Twenty-eight (54%) occurred in inpatients; the other 22 (44%) events involved visitors or employees on the hospital premises. Eighty-six percent of the events were epileptic seizures. Seizure mimickers, particularly psychogenic nonepileptic seizures, were more common in the nonhospitalized group. Only five (17.9%) inpatients had a known diagnosis of epilepsy, compared with 17 (77.3%) of the nonhospitalized patients. This retrospective survey provides insights into how code blues are called on hospitalized versus nonhospitalized patients for seizure-like events.

Randomized comparison of the Personality Assessment Inventory and the Minnesota Multiphasic Personality Inventory-2 in the epilepsy monitoring unit.

The two most common personality measures used in evaluation of patients on epilepsy monitoring units (EMUs) are the Personality Assessment Inventory (PAI) and the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Both have been evaluated separately for their ability to distinguish patients with epilepsy from patients with psychogenic events, but they have never been compared directly. The primary aim of this study was to provide comparison data in an EMU population between the PAI, MMPI-2, and the MMPI-2-RF (MMPI-2 Restructured Form). Results show that the PAI Somatic Complaints (SOM) scale and the Conversion subscale (SOM-C), with classification rates of 79%, outperform other indicators from the PAI and indicators from the MMPI-2 and the MMPI-2-RF. Given its other strengths combined with better diagnostic validity performance, the PAI may be the better personality assessment measure for use in distinguishing patients with epilepsy from those with psychogenic seizures in the EMU.

Indeterminate EMU admissions: does repeating the admission help?

Epilepsy monitoring unit (EMU) admissions during 2007-2009 at Mayo Clinic Hospital Arizona were reviewed. Of the 106 indeterminate admissions, 13 (12%) went on to have a second admission. During the second admission, 8 (62%) were diagnosed. Five patients went on to have a third or fourth admission, with none of them receiving a diagnosis. Nineteen (18%) patients had ambulatory EEG monitoring after an indeterminate admission, with only one (5%) receiving a diagnosis after ambulatory EEG monitoring. Even in patients who were initially indeterminate, medication management changed 37% of the time. Admission to the EMU was helpful for spell classification, with 80% of the patients receiving a diagnosis after the first admission. Based on this study, a second admission should be considered if no diagnosis is reached after the first admission. If no diagnosis is made after the second EMU admission, subsequent admissions are unlikely to produce a definitive diagnosis.