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BACKGROUND AND OBJECTIVES: Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as “ictal-interictal-injury continuum” (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns. METHODS: We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes. RESULTS: SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and “other” classes, SPaRCNet exceeds the following percentages of 20 experts—ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively. DISCUSSION: SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

BACKGROUND AND OBJECTIVES: The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as “ictal-interictal-injury continuum” (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC. METHODS: This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as “seizure (SZ),” “lateralized periodic discharges (LPDs),” “generalized periodic discharges (GPDs),” “lateralized rhythmic delta activity (LRDA),” “generalized rhythmic delta activity (GRDA),” or “other.” EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability. RESULTS: Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Image: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Image: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds. DISCUSSION: Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

ObjectiveTo examine the relationship between scalp EEG biomarkers of hyperexcitability in Alzheimer disease (AD) and to determine how these electric biomarkers relate to the clinical expression of seizures in AD.MethodsIn this cross-sectional study, we performed 24-hour ambulatory scalp EEGs on 43 cognitively normal elderly healthy controls (HC), 41 participants with early-stage AD with no history or risk factors for epilepsy (AD-NoEp), and 15 participants with early-stage AD with late-onset epilepsy related to AD (AD-Ep). Two epileptologists blinded to diagnosis visually reviewed all EEGs and annotated all potential epileptiform abnormalities. A panel of 9 epileptologists blinded to diagnosis was then surveyed to generate a consensus interpretation of epileptiform abnormalities in each EEG.ResultsEpileptiform abnormalities were seen in 53% of AD-Ep, 22% of AD-NoEp, and 4.7% of HC. Specific features of epileptiform discharges, including high frequency, robust morphology, right temporal location, and occurrence during wakefulness and REM, were associated with clinical seizures in AD. Multiple EEG biomarkers concordantly demonstrated a pattern of left temporal lobe hyperexcitability in early stages of AD, whereas clinical seizures in AD were often associated with bitemporal hyperexcitability. Frequent small sharp spikes were specifically associated with epileptiform EEGs and thus identified as a potential biomarker of hyperexcitability in AD.ConclusionEpileptiform abnormalities are common in AD but not all equivalent. Specific features of epileptiform discharges are associated with clinical seizures in AD. Given the difficulty recognizing clinical seizures in AD, these EEG features could provide guidance on which patients with AD are at high risk for clinical seizures.

ObjectiveTo incorporate standardized documentation into an epilepsy clinic and to use these standardized data to compare patients' perception of epilepsy diagnosis to provider documentation.MethodsUsing quality improvement methodology, we implemented interventions to increase documentation of epilepsy diagnosis, seizure frequency, and type from 49.8% to 70% of adult nonemployee patients seen by 6 providers over 5 months of routine clinical care. The main intervention consisted of an interactive SmartPhrase that mirrored a documentation template developed by the Epilepsy Learning Healthcare System. We assessed the weekly proportion of complete SmartPhrases among eligible patient encounters with a statistical process control chart. We used a subset of patients with established epilepsy care linked to existing patient-reported survey data to examine the proportion of patient-to-provider agreement on epilepsy diagnosis (yes vs no/unsure). We also examined sociodemographic and clinical characteristics of patients who disagreed vs agreed with provider's documentation of epilepsy diagnosis.ResultsThe median SmartPhrase weekly completion rate was 78%. Established patients disagreed with providers with respect to epilepsy diagnosis in 18.5% of encounters (κ = 0.13), indicating that they did not have or were unsure if they had epilepsy despite having a provider-documented epilepsy diagnosis. Patients who disagreed with providers were similar to those who agreed with respect to age, sex, ethnicity, marital status, seizure frequency, type, and other quality-of-life measures.ConclusionThis project supports the feasibility of implementing standardized documentation of data relevant to epilepsy care in a tertiary epilepsy clinic and highlights an opportunity for improvement in patient-provider communication.

Background and purposeEpilepsy is most common in lower-income settings where access to electroencephalography (EEG) is generally poor. A low-cost tablet-based EEG device may be valuable, but the quality and reproducibility of the EEG output are not established.MethodsTablet-based EEG was deployed in a heterogeneous epilepsy cohort in the Republic of Guinea (2018-2019), consisting of a tablet wirelessly connected to a 14-electrode cap. Participants underwent EEG twice (EEG1 and EEG2), separated by a variable time interval. Recordings were scored remotely by experts in clinical neurophysiology as to data quality and clinical utility.ResultsThere were 149 participants (41% female; median age 17.9years; 66.6% ≤21years of age; mean seizures per month 5.7±SD 15.5). The mean duration of EEG1 was 53±12.3min and that of EEG2 was 29.6±12.8min. The mean quality scores of EEG1 and EEG2 were 6.4 [range, 1 (low) to 10 (high); both medians 7.0]. A total of 44 (29.5%) participants had epileptiform discharges (EDs) at EEG1 and 25 (16.8%) had EDs at EEG2. EDs were focal/multifocal (rather than generalized) in 70.1% of EEG1 and 72.5% of EEG2 interpretations. A total of 39 (26.2%) were recommended for neuroimaging after EEG1 and 22 (14.8%) after EEG2. Of participants without EDs at EEG1 (n=53, 55.8%), seven (13.2%) had EDs at EEG2. Of participants with detectable EDs on EEG1 (n=23, 24.2%), 12 (52.1%) did not have EDs at EEG2.ConclusionsTablet-based EEG had a reproducible quality level on repeat testing and was useful for the detection of EDs. The incremental yield of a second EEG in this setting was ~13%. The need for neuroimaging access was evident.

Routine outpatient epilepsy care has shifted from in-person to telemedicine visits in response to safety concerns posed by the coronavirus disease 2019 (COVID-19) pandemic. But whether telemedicine can support and maintain standardized documentation of high-quality epilepsy care remains unknown. In response, the authors conducted a quality improvement study at a level 4 epilepsy center between January 20, 2019, and May 31, 2020. Weekly average completion proportion of standardized documentation used by a team of neurologists for adult patients for the diagnosis of epilepsy, seizure classification, and frequency were analyzed. By December 15, 2019, a 94% average weekly completion proportion of standardized epilepsy care documentation was achieved that was maintained through May 31, 2020. Moreover, during the period of predominately telemedicine encounters in response to the pandemic, the completion proportion was 90%. This study indicates that high completion of standardized documentation of seizure-related information can be sustained during telemedicine appointments for routine outpatient epilepsy care at a level 4 epilepsy center.

SummaryObjective To evaluate published algorithms for the identification of epilepsy cases in medical claims data using a unique linked dataset with both clinical and claims data. Methods Using data from a large, regional health delivery system, we identified all patients contributing biologic samples to the health system's Biobank (n = 36K). We identified all subjects with at least one diagnosis potentially consistent with epilepsy, for example, epilepsy, convulsions, syncope, or collapse, between 2014 and 2015, or who were seen at the epilepsy clinic (n = 1,217), plus a random sample of subjects with neither claims nor clinic visits (n = 435); we then performed a medical chart review in a random subsample of 1,377 to assess the epilepsy diagnosis status. Using the chart review as the reference standard, we evaluated the test characteristics of six published algorithms. Results The best-performing algorithm used diagnostic and prescription drug data (sensitivity = 70%, 95% confidence interval [CI] 66–73%; specificity = 77%, 95% CI 73–81%; and area under the curve [AUC] = 0.73, 95%CI 0.71–0.76) when applied to patients age 18 years or older. Restricting the sample to adults aged 18–64 years resulted in a mild improvement in accuracy (AUC = 0.75,95%CI 0.73–0.78). Adding information about current antiepileptic drug use to the algorithm increased test performance (AUC = 0.78, 95%CI 0.76–0.80). Other algorithms varied in their included data types and performed worse. Significance Current approaches for identifying patients with epilepsy in insurance claims have important limitations when applied to the general population. Approaches incorporating a range of information, for example, diagnoses, treatments, and site of care/specialty of physician, improve the performance of identification and could be useful in epilepsy studies using large datasets.

Purpose : Children with epilepsy in low-income countries often go undiagnosed and untreated. We examine a portable, low-cost smartphone-based EEG technology in a heterogeneous pediatric epilepsy cohort in the West African Republic of Guinea. Methods : Children with epilepsy were recruited at the Ignace Deen Hospital in Conakry, 2017. Participants underwent sequential EEG recordings with an app-based EEG, the Smartphone Brain Scanner-2 (SBS2) and a standard Xltek EEG. Raw EEG data were transmitted via Bluetooth™ connection to an Android™ tablet and uploaded for remote EEG specialist review and reporting via a new, secure web-based reading platform, crowdEEG. The results were compared to same-visit Xltek 10–20 EEG recordings for identification of epileptiform and non-epileptiform abnormalities. Results : 97 children meeting the International League Against Epilepsy’s definition of epilepsy (49 male; mean age 10.3 years, 29 untreated with an antiepileptic drug; 0 with a prior EEG) were enrolled. Epileptiform discharges were detected on 21 (25.3%) SBS2 and 31 (37.3%) standard EEG recordings. The SBS2 had a sensitivity of 51.6% (95%CI 32.4%, 70.8%) and a specificity of 90.4% (95%CI 81.4%, 94.4%) for all types of epileptiform discharges, with positive and negative predictive values of 76.2% and 75.8% respectively. For generalized discharges, the SBS2 had a sensitivity of 43.5% with a specificity of 96.2%. Conclusions : The SBS2 has a moderate sensitivity and high specificity for the detection of epileptiform abnormalities in children with epilepsy in this low-income setting. Use of the SBS2+crowdEEG platform permits specialist input for patients with previously poor access to clinical neurophysiology expertise.

ObjectiveTo see if systematic collection of patient-reported epilepsy quality measures can identify opportunities to improve care, and to examine the associations between these measures and physical and mental health.MethodsWe developed a patient-reported questionnaire for medication adherence, seizure frequency, medication side effects, and driving that included the Patient-Reported Outcome Measurement Information System–10 (PROMIS-10) (physical and mental health). We offered it to all adult patients seen twice in an epilepsy clinic (January 2017–January 2018). The questionnaire was available on the web as well as a tablet provided at appointment check-in. We used the first completed questionnaire to explore the relationship between patient-reported care quality and measures of physical and mental health.ResultsA total of 610 unique patients (15% of the total encounters) completed a survey. Respondents were comparable to nonrespondents. Respondents reported gaps in care or opportunities for quality improvement in 48.4% (n = 295) of the encounters. Of patients who reported at least 1 seizure per month over the previous 3 months, 55.2% (n = 100) reported problems with adherence, 30.0% (n = 131) reported having problems believed to be adverse reactions to anticonvulsants, and 15.2% (n = 41) reported driving. In addition, respondents who reported either seizures over the recent 3 months, nonadherence to treatment due to cost, or anticonvulsant-associated adverse effects had consistently worse physical and mental health (all p < 0.05).ConclusionsSystematic collection of epilepsy quality measures endorsed by the American Academy of Neurology can identify opportunities for quality improvement. Measures of epilepsy care quality predict outcomes that matter to patients.

Background:Delayed access to specialty care may increase inappropriate emergency department (ED) visits. However, the details of this relationship after referral to a specialist are unknown.Methods:The correlations in an academic medical center between time to new neurology patient appointments and nonurgent ED use are explored in this study. Access was measured as the number of days between the scheduling and outpatient appointment dates. A series of statistical analyses including correlation analysis, regressions, and hypothesis tests were conducted to investigate possible associations between delayed access to specialty care and ED visits, as well as the effect of ED visits on specialty care cancellation and no-show rates.Results:Of 19,505 new neurology patients, 310 visited an ED prior to their appointment, 95.2% (295) of whom had poor access (defined here as exceeding 21 days). Patients with access >21 days for new visits were 6.6 times more likely to visit the ED before their appointment date, 19% within the first week after scheduling. Patients who visited the ED between their booking and appointment dates were 2.3 times more likely to cancel or fail to attend their appointment.Conclusion:These results suggest that long access delays in specialty referrals can significantly increase ED costs and congestion. Further studies in other specialties to explore this relationship are warranted.

Lidia M V R Moura,1 Thiago S Carneiro,1 Andrew J Cole,1 John Hsu,2,3 Barbara G Vickrey,4 Daniel B Hoch1 1Department of Neurology, 2Mongan Institute for Health Policy, Department of Medicine, Massachusetts General Hospital, 3Department of Health Care Policy, Harvard Medical School, Boston, MA, 4Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA Background and aim: Adherence to treatment is a critical component of epilepsy management. This study examines whether addressing antiepileptic drug (AED) side effects at every visit is associated with increased patient-reported medication adherence.Patients and methods: This study identified 243 adults with epilepsy who were seen at two academic outpatient neurology settings and had at least two visits over a 3-year period. Demographic and clinical characteristics were abstracted. Evidence that AED side effects were addressed was measured through 1) phone interview (patient-reported) and 2) medical records abstraction (physician-documented). Medication adherence was assessed using the validated Morisky Medication Adherence Scale-4. Complete adherence was determined as answering “no” to all questions.Results: Sixty-two (25%) patients completed the interviews. Participants and nonparticipants were comparable with respect to demographic and clinical characteristics; however, a smaller proportion of participants had a history of drug-resistant epilepsy than nonparticipants (17.7% vs 30.9%, P=0.04). Among the participants, evidence that AED side effects were addressed was present in 48 (77%) medical records and reported by 51 (82%) patients. Twenty-eight (45%) patients reported complete medication adherence. The most common reason for incomplete adherence was missed medication due to forgetfulness (n=31, 91%). There was no association between addressing AED side effects (neither physician-documented nor patient-reported) and complete medication adherence (P=0.22 and 0.20).Discussion and conclusion: Among patients with epilepsy, addressing medication side effects at every visit does not appear to increase patient-reported medication adherence. Keywords: epilepsy, antiepileptic drug side effects, medication adherence&nbsp

The aim of this study was to compare physician encounter documentation with patient perceptions of quality of epilepsy care and examine the association between quality and patient assessment of provider communication.We identified 505 adult patients with epilepsy aged 18years or older over a 3-year period in two large academic medical centers. We abstracted individual, clinical, and care measures from 2723 electronic clinical notes written by physicians. We then randomly selected 245 patients for a phone interview. We compared patient perceptions of care with the documented care for several established epilepsy quality measures. We also explored the association of patient's perception of provider communication with provider documentation of key encounter interventions.There were 88 patients (36%) who completed the interviews. Fifty-seven (24%) refused to participate, and 100 (40%) could not be contacted. Participants and nonparticipants were comparable in their demographic and clinical characteristics; however, participants were more often seen by epilepsy specialists than nonparticipants (75% vs. 61.9%, p0.01). Quality scores based on patient perceptions differed from those determined by assessing the documentation in the medical record for several quality measures, e.g., documentation of side effects of antiseizure therapy (p=0.05), safety counseling (p0.01), and counseling for women of childbearing potential with epilepsy (McNemar's p=0.03; intraclass correlation coefficient, ICC=0.07). There was a significant, positive association between patient-reported counseling during the encounter (e.g., personalized safety counseling) and patient-reported scores of provider communication (p=0.05).The association between the patient's recollection of counseling during the visit and his/her positive perception of the provider's communication skills highlights the importance of spending time counseling patients about their epilepsy and not just determining if seizures are controlled.

Objective To evaluate the accuracy of ICD-10-CM claims-based definitions for epilepsy and classifying seizure types in the outpatient setting. Methods We reviewed electronic health records (EHR) for a cohort of adults aged 18+ years seen by six neurologists who had an outpatient visit at a level 4 epilepsy center between 01/2019−09/2019. The neurologists used a standardized documentation template to capture the diagnosis of epilepsy (yes/no/unsure), seizure type (focal/generalized/unknown), and seizure frequency in the EHR. Using linked ICD-10-CM codes assigned by the provider, we assessed the accuracy of claims-based definitions for epilepsy, focal seizure type, and generalized seizure type against the reference-standard EHR documentation by estimating sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV). Results There were 673 eligible outpatient encounters. After review of EHRs for standardized documentation, an analytic sample consisted of 520 encounters representing 402 unique patients. In the EHR documentation, 93.5 % (n = 486/520) of encounters were with patients with a diagnosis of epilepsy. Of those, 66.0 % (n = 321/486) had ≥1 focal seizure, 41.6 % (n = 202/486) had ≥1 generalized seizure, and 7% (n = 34/486) had ≥1 unknown seizure. An ICD-10-CM definition for epilepsy (i.e., ICD-10 G40.X) achieved Sn = 84.4 % (95 % CI 80.8−87.5%), Sp = 79.4 % (95 % CI 62.1−91.3%), PPV = 98.3 % (95 % CI 96.6−99.3%), and NPV = 26.2 % (95 % CI 18.0−35.8%). The classification of focal vs generalized/unknown seizures achieved Sn = 69.8 % (95 % CI 64.4−74.8%), Sp = 79.4 % (95 % CI 72.4−85.3%), PPV = 86.8 % (95 % CI 82.1−90.7%), and NPV = 57.5 % (95 % CI 50.8−64.0%). Conclusions Claims-based definitions using groups of ICD-10-CM codes assigned by neurologists in routine outpatient clinic visits at a level 4 epilepsy center performed well in discriminating between patients with and without a diagnosis of epilepsy and between seizure types.

Importance The validity of using electroencephalograms (EEGs) to diagnose epilepsy requires reliable detection of interictal epileptiform discharges (IEDs). Prior interrater reliability (IRR) studies are limited by small samples and selection bias. Objective To assess the reliability of experts in detecting IEDs in routine EEGs. Design, Setting, and Participants This prospective analysis conducted in 2 phases included as participants physicians with at least 1 year of subspecialty training in clinical neurophysiology. In phase 1, 9 experts independently identified candidate IEDs in 991 EEGs (1 expert per EEG) reported in the medical record to contain at least 1 IED, yielding 87 636 candidate IEDs. In phase 2, the candidate IEDs were clustered into groups with distinct morphological features, yielding 12 602 clusters, and a representative candidate IED was selected from each cluster. We added 660 waveforms (11 random samples each from 60 randomly selected EEGs reported as being free of IEDs) as negative controls. Eight experts independently scored all 13 262 candidates as IEDs or non-IEDs. The 1051 EEGs in the study were recorded at the Massachusetts General Hospital between 2012 and 2016. Main Outcomes and Measures Primary outcome measures were percentage of agreement (PA) and beyond-chance agreement (Gwet κ) for individual IEDs (IED-wise IRR) and for whether an EEG contained any IEDs (EEG-wise IRR). Secondary outcomes were the correlations between numbers of IEDs marked by experts across cases, calibration of expert scoring to group consensus, and receiver operating characteristic analysis of how well multivariate logistic regression models may account for differences in the IED scoring behavior between experts. Results Among the 1051 EEGs assessed in the study, 540 (51.4%) were those of females and 511 (48.6%) were those of males. In phase 1, 9 experts each marked potential IEDs in a median of 65 (interquartile range [IQR], 28-332) EEGs. The total number of IED candidates marked was 87 636. Expert IRR for the 13 262 individually annotated IED candidates was fair, with the mean PA being 72.4% (95% CI, 67.0%-77.8%) and mean κ being 48.7% (95% CI, 37.3%-60.1%). The EEG-wise IRR was substantial, with the mean PA being 80.9% (95% CI, 76.2%-85.7%) and mean κ being 69.4% (95% CI, 60.3%-78.5%). A statistical model based on waveform morphological features, when provided with individualized thresholds, explained the median binary scores of all experts with a high degree of accuracy of 80% (range, 73%-88%). Conclusions and Relevance This study’s findings suggest that experts can identify whether EEGs contain IEDs with substantial reliability. Lower reliability regarding individual IEDs may be largely explained by various experts applying different thresholds to a common underlying statistical model.

ObjectiveTo compare the expected quality-adjusted life-years (QALYs) in adult patients undergoing immediate vs deferred antiepileptic drug (AED) treatment after a first unprovoked seizure.MethodsWe constructed a simulated clinical trial (Markov decision model) to compare immediate vs deferred AED treatment after a first unprovoked seizure in adults. Three base cases were considered, representing patients with varying degrees of seizure recurrence risk and effect of seizures on quality of life (QOL). Cohort simulation was performed to determine which treatment strategy would maximize the patient's expected QALYs. Sensitivity analyses were guided by clinical data to define decision thresholds across plausible measurement ranges, including seizure recurrence rate, effect of seizure recurrence on QOL, and efficacy of AEDs.ResultsFor patients with a moderate risk of recurrent seizures (52.0% over 10 years after first seizure), immediate AED treatment maximized QALYs compared to deferred treatment. Sensitivity analyses showed that for the preferred choice to change to deferred AED treatment, key clinical measures needed to reach implausible values were 10-year seizure recurrence rate ≤38.0%, QOL reduction with recurrent seizures ≤0.06, and efficacy of AEDs on lowering seizure recurrence rate ≤16.3%.ConclusionOur model determined that immediate AED treatment is preferable to deferred treatment in adult first-seizure patients over a wide and clinically relevant range of variables. Furthermore, our analysis suggests that the 10-year seizure recurrence rate that justifies AED treatment (38.0%) is substantially lower than the 60% threshold used in the current definition of epilepsy.

OBJECTIVEForamen ovale electrodes (FOEs) are a minimally invasive method to localize mesial temporal seizures in cases in which noninvasive methods are inconclusive. The objective of this study was to identify factors predicting the ability of FOEs to yield a diagnosis in order to determine optimal candidates for this procedure.METHODSAll cases of diagnostic investigations performed with FOEs at the authors’ institution between 2005 and 2017 were reviewed. FOE investigation was defined as diagnostic if it led to a treatment decision. Demographic and clinical variables for diagnostic and nondiagnostic investigations were compared using a Wilcoxon rank-sum test for continuous variables and Fisher’s exact test for categorical variables.RESULTSNinety-three patients underwent investigations performed with FOEs during the study period and were included in the study. FOE investigation was diagnostic in 75.3% of cases. Of patients who underwent anterior temporal lobectomy following diagnostic FOE evaluation, 75.9% were Engel class I at last follow-up (average 40.1 months). When the diagnostic and nondiagnostic FOE groups were compared, patients who had diagnostic investigations were more likely to be male (57.1% male vs 26.1% in the nondiagnostic group, p = 0.015). They were also more likely to have temporal lesions on preoperative MRI (p = 0.018).CONCLUSIONSFOEs are a useful, minimally invasive diagnostic modality resulting in a treatment decision in 75% of cases. Male patients and patients with temporal lesions on MRI may be most likely to benefit from FOE investigation.

Objective Delayed cerebral ischemia (DCI) is a common, disabling complication of subarachnoid hemorrhage (SAH). Preventing DCI is a key focus of neurocritical care, but interventions carry risk and cannot be applied indiscriminately. Although retrospective studies have identified continuous electroencephalographic (cEEG) measures associated with DCI, no study has characterized the accuracy of cEEG with sufficient rigor to justify using it to triage patients to interventions or clinical trials. We therefore prospectively assessed the accuracy of cEEG for predicting DCI, following the Standards for Reporting Diagnostic Accuracy Studies. Methods We prospectively performed cEEG in nontraumatic, high-grade SAH patients at a single institution. The index test consisted of clinical neurophysiologists prospectively reporting prespecified EEG alarms: (1) decreasing relative alpha variability, (2) decreasing alpha-delta ratio, (3) worsening focal slowing, or (4) late appearing epileptiform abnormalities. The diagnostic reference standard was DCI determined by blinded, adjudicated review. Primary outcome measures were sensitivity and specificity of cEEG for subsequent DCI, determined by multistate survival analysis, adjusted for baseline risk. Results One hundred three of 227 consecutive patients were eligible and underwent cEEG monitoring (7.7-day mean duration). EEG alarms occurred in 96.2% of patients with and 19.6% without subsequent DCI (1.9-day median latency, interquartile range = 0.9-4.1). Among alarm subtypes, late onset epileptiform abnormalities had the highest predictive value. Prespecified EEG findings predicted DCI among patients with low (91% sensitivity, 83% specificity) and high (95% sensitivity, 77% specificity) baseline risk. Interpretation cEEG accurately predicts DCI following SAH and may help target therapies to patients at highest risk of secondary brain injury. Ann Neurol 2018;83:958-969.

Objective We assessed the relationship between adherence to epilepsy quality measures (EQM) and seizure control over 2–3 years in a retrospective cohort study. Methods 6150 patients were identified at two large academic medical centers with a primary or secondary diagnosis of epilepsy, were 18–85 years old and seen in outpatient general neurology or epilepsy units between June 2011 and May 2014. Patients were included if: their initial visit was between June 2011 and June 2012, treatment was with ≥1 anti-seizure drug, there was ≥1 visit per year during the timeframe, and seizure frequency was documented at initial and final visits, yielding 162 patients/1055 visits from which socio-demographic, clinical and care quality data were abstracted. Quality care was assessed as (1) percent adherence to up to 8 eligible EQM, and (2) defect-free care (DFC: adherence to all eligible EQM). Seizure control (SC) was defined as ≥50% reduction in average seizures/month between initial and final visits. Chi-square and t-test compared care quality with seizure control. Logistic regression was used to assess the relationships between SC, quality of care and subspecialist involvement. Results Care quality, reflected by documentation of seizure frequency, addressing therapeutic interventions, and referral to a comprehensive epilepsy center, all exceeded 80% adherence. Care quality as reflected by documentation of seizure type, etiology or syndrome; assessment of side effects, counseling about epilepsy safety and women's issues, and screening for psychiatric disorders ranged from 40 to 57%. Mean EQM adherence across all applicable measures was associated with greater seizure control (p = 0.0098). DFC was low (=8%) and did not covary with seizure control (p = 0.55). The SC and non-SC groups only differed on epilepsy etiology (p = 0.04). Exploratory analysis showed that mean quality scores are associated with seizure control (OR = 4.9 [1.3–18.5], p = 0.017) while controlling for the effect of subspecialty involvement as a possible confounding variable. Conclusions Average quality of care but not defect-free care was associated with seizure control in this retrospective cohort.

Objective This study aimed to determine if annual counseling about contraception and pregnancy in the setting of treatment for epilepsy is associated with increased recommending or prescribing of folate. Methods This is a retrospective cohort study with medical record abstraction. We selected records from 77 women of childbearing age who had two or more visits for epilepsy at a neurology clinic. The assessment included a review of documentation from the first three visits for epilepsy within a 24-month follow-up window. We defined perfect adherence to annual counseling about the impact of epilepsy treatment on contraception or pregnancy as defect-free care for women (DFCW). A recommendation that the patient take over-the-counter folate or a prescription for folate was independently abstracted from the chart at each visit. Results The group of patients who received DFCW (N = 28, 36.36%) and the group who did not receive DFCW (N = 49, 63.63%) were comparable with respect to age, disease duration, baseline history of drug-resistant epilepsy (DRE), presence of concurrent psychiatric disease, epileptologist involvement, number of antiepileptic drugs (AEDs) prescribed, seizure type, and etiology. Twenty (71.4%) patients in the DFCW group and 42 (85.7%) in the non-DFCW group were not recommended or prescribed folic acid (p = 0.12). Conclusions Even with annual documentation of counseling about how epilepsy treatment may affect contraception and pregnancy, the “action” of prescribing or recommending folic acid during the ensuing 24 months is frequently omitted.

Objective Excitotoxic injury involving N-methyl-d-aspartate (NMDA) receptor hyperactivity contributes to epilepsy-related memory dysfunction (ERMD). Current treatment strategies for ERMD have limited efficacy and fail to target the underlying pathophysiology. The present pilot study evaluated the efficacy of memantine, an NMDA receptor antagonist, for the treatment of ERMD in adults with focal-onset seizures. Methods Subjects underwent cognitive testing at baseline, after a 13-week randomized, parallel-group, double-blinded phase (of memantine titrated to 10 mg bid or placebo), and following a 13-week open-label extension phase (of memantine titrated to 10 mg bid). The selective reminding test (SRT) continuous long-term retrieval (CLTR) score and 7/24 Spatial Recall Test learning score served as the primary outcome measures. Secondary measures included tests of attention span, fluency, visual construction, and response inhibition, as well as assessments of quality of life, depression, sleepiness, and side effects. Results Seventeen subjects contributed data to the blinded phase (n = 8 memantine, n = 9 placebo). No significant differences were seen between groups on the primary or secondary outcome measures. Pooled data at the end of the open-label phase from 10 subjects (initially randomized to memantine n = 3 or placebo n = 7) demonstrated statistically significant improvement from baseline in CLTR score, memory-related quality of life, spatial span, and response inhibition. No significant changes were evident in depression, sleepiness, side effects, or seizure frequency throughout the trial. Significance Results demonstrated no significant effect of memantine on cognition when assessed at the end of the blinded period. Pooled data at the end of the open-label phase showed significant improvement over baseline performance in measures of verbal memory, frontal-executive function, and memory-related quality of life. These improvements, however, may be due to practice effects and should be interpreted cautiously. Findings suggest a favorable safety profile of memantine in the setting of epilepsy.

Background:Pressure ulcers resulting from continuous EEG (cEEG) monitoring in hospitalized patients have gained attention as a preventable medical complication. We measured their incidence and risk factors.Methods:We performed an observational investigation of cEEG-electrode-related pressure ulcers (EERPU) among acutely ill patients over a 22-month period. Variables analyzed included age, sex, monitoring duration, hospital location, application methods, vasopressor usage, nutritional status, skin allergies, fever, and presence/severity of EERPU. We examined risk for pressure ulcers vs monitoring duration using Kaplan-Meyer survival analysis, and performed multivariate risk assessment using Cox proportional hazard model.Results:Among 1,519 patients, EERPU occurred in 118 (7.8%). Most (n = 109, 92.3%) consisted of hyperemia only without skin breakdown. A major predictor was monitoring duration, with 3-, 5-, and 10-day risks of 16%, 32%, and 60%, respectively. Risk factors included older age (mean age 60.65 vs 50.3, p < 0.01), care in an intensive care unit (9.37% vs 5.32%, p < 0.01), lack of a head wrap (8.31% vs 27.3%, p = 0.02), use of vasopressors (16.7% vs 9.64%, p < 0.01), enteral feeding (11.7% vs 5.45%, p = 0.04), and fever (18.4% vs 9.3%, p < 0.01). Elderly patients (71–80 years) were at higher risk (hazard ratio 6.84 [1.95–24], p < 0.01), even after accounting for monitoring time and other pertinent variables in multivariate analysis.Conclusions:EERPU are uncommon and generally mild. Elderly patients and those with more severe illness have higher risk of developing EERPU, and the risk increases as a function of monitoring duration.

Quantitatively evaluate whether screening with compressed spectral arrays (CSAs) is a practical and time-effective protocol for assisting expert review of continuous EEG (cEEG) studies in hospitalized adults.Three neurophysiologists reviewed the reported findings of the first 30 minutes of 118 cEEGs, then used CSA to guide subsequent review ("CSA-guided review" protocol). Reviewers viewed 120 seconds of raw EEG data surrounding suspicious CSA segments. The same neurophysiologists performed independent page-by-page visual interpretation ("conventional review") of all cEEGs. Independent conventional review by 2 additional, more experienced neurophysiologists served as a gold standard. We compared review times and detection rates for seizures and other pathologic patterns relative to conventional review.A total of 2,092 hours of cEEG data were reviewed. Average times to review 24 hours of cEEG data were 8 (±4) minutes for CSA-guided review vs 38 (±17) minutes for conventional review (p0.005). Studies containing seizures required longer review: 10 (±4) minutes for CSA-guided review vs 44 (±20) minutes for conventional review (p0.005). CSA-guided review was sensitive for seizures (87.3%), periodic epileptiform discharges (100%), rhythmic delta activity (97.1%), focal slowing (98.7%), generalized slowing (100%), and epileptiform discharges (88.5%).CSA-guided review reduces cEEG review time by 78% with minimal loss of sensitivity compared with conventional review.This study provides Class IV evidence that screening of cEEG with CSAs efficiently and accurately identifies seizures and other EEG abnormalities as compared with standard cEEG visual interpretation.

Recent health policy initiatives designed to improve care coordination have stimulated the resurgence of the patient-centered medical home (PCMH) model. The details of how primary and specialty care are coordinated within the PCMH model are of interest to specialists. A good medical home “neighbor” must adhere to principles that complement the PCMH team-based approach and personal relationship to the patient. One issue for neurologists considering participation in this model is whether they will function as the principal physician for some patients, only in the role of a consultant, or take some new role. It is too early to suggest any one payment method as superior, or establish the appropriate capitation fees for practicing neurologists. Recommendations are provided for neurologists considering participation in a PCMH neighborhood.

Routine EEGs remain a cornerstone test in caring for people with epilepsy. Although rare, a self-limited seizure (clinical or electrographic only) may be observed during such brief EEGs. The implications of observing a seizure in this situation, especially with respect to inferring the underlying seizure frequency, are unclear. The issue is complicated by the inaccuracy of patient-reported estimations of seizure frequency. The treating clinician is often left to wonder whether the single seizure indicates very frequent seizures, or if it is of lesser significance. We applied standard concepts of probabilistic inference to a simple model of seizure incidence to provide some guidance for clinicians facing this situation. Our analysis establishes upper and lower bounds on the seizure rate implied by observing a single seizure during routine EEG. Not surprisingly, with additional information regarding the expected seizure rate, these bounds can be further constrained. This framework should aid the clinician in applying a more principled approach toward decision making in the setting of a single seizure on a routine EEG.

Lidia MVR Moura,1 Eli L Schwamm,1 Valdery Moura Junior,1 Michael P Seitz,1 Daniel B Hoch,1 John Hsu,2,3 Lee H Schwamm1 1Department of Neurology, 2Mongan Institute for Health Policy, Massachusetts General Hospital, 3Department of Medicine and Department of Health Care Policy, Harvard Medical School, Boston, MA,USA Objective: Many effective medical therapies are available for treating neurological diseases, but these therapies tend to be expensive and adherence is critical to their effectiveness. We used patient-reported data to examine the frequency and determinants of financial barriers to medication adherence among individuals treated for neurological disorders. Patients and methods: Patients completed cross-sectional surveys on iPads as part of routine outpatient care in a neurology clinic. Survey responses from a 3-month period were collected and merged with administrative sources of demographic and clinical information (eg, insurance type). We explored the association between patient characteristics and patient-reported failure to refill prescription medication due to cost in the previous 12months, termed here as “nonadherence”. Results: The population studied comprised 6075 adults who were presented between July and September 2015 for outpatient neurology appointments. The mean age of participants was 56 (standard deviation: 18) years, and 1613 (54%) were females. The patients who participated in the surveys (2992, 49%) were comparable to nonparticipants with respect to gender and ethnicity but more often identified English as their preferred language (94% vs 6%, p

Objective To compare postoperative seizure-free survival between older and younger adults. Methods A retrospective cohort of 107 temporal lobe epilepsy patients with a diagnosis of mesial temporal sclerosis (MTS) received anterior temporal lobectomy (ATL) between 1993 and 2014. We divided the lower three quartiles (younger) and top quartile (older, all 47+ years) of patients, then reviewed patient registry and electronic medical records to determine time to first self-reported seizure after ATL, the primary outcome (mean = 3.5 years of follow-up, SD = 3.6). We also assessed Engel classifications, intraoperative and postoperative treatment complications, and social disability. We used Cox proportional hazard models to assess the association between individual traits and time of seizure recurrence. Results During follow-up, 35/107 (32.7%) patients had post-operative seizure(s). After adjustment for potential confounders there were no significant differences in the probability of post-operative seizures between the older and younger groups, though we had limited precision (hazard ratio of 0.67 [0.28–1.59]), (p = 0.36). There were more treatment complications and disability in older patients (18% vs. 1.3% for any complications, 84.62% vs. 58.23% for driving disability, and 84.6% vs. 60.7% for work disability, p Conclusion Older patients appear to have more complications after ATL, compared with younger patients. Age, however, does not appear to have a large independent association with seizure recurrence.

To determine whether 1) combined oral contraceptive (COC) use affects serum levels of valproate (VPA) as well as lamotrigine (LTG) and 2) the naturally occurring high (mid-luteal) and low (early-mid follicular) reproductive steroid level phases of the menstrual cycle might affect antiepileptic drug levels as well.This investigation compared serum antiepileptic drug levels at two timepoints during a single menstrual cycle in four groups of women with epilepsy: 12 on VPA, 12 on VPA plus COC (VPA-COC), 12 on LTG, and 12 on LTG plus COC (LTG-COC).Both VPA and LTG levels were lower (p0.01) on active COC than on inactive pill with median declines of 23.4% for the VPA-COC group and 32.6% for the LTG-COC group. Serum LTG levels showed a notable but not significant 31.3% median decline during the mid-luteal phase compared to the early-mid follicular phase in the non-COC group. The non-COC valproate group showed the least change of any group between the two measured timepoints with a decline of 8.3% (p = NS).The findings suggest that valproate (VPA), like lamotrigine (LTG), has substantially and significantly lower serum levels while women take active combined oral contraceptives as compared to inactive pills. Larger sample sizes will be required to determine whether LTG levels may drop significantly also during the luteal (high steroid) phase of natural menstrual cycles and whether VPA levels may show greater stability in levels across the phases of the menstrual cycle.

New technologies, such as online networking tools, offer innovative ways to engage patients in their diabetes care. Second Life (SL) is one such virtual world that allows patients to interact in a 3D environment with peers and healthcare providers. This article presents a framework that demonstrates how applications within SL can be constructed to meet the needs of patients with diabetes, allowing them to attend group visits, learn more about lifestyle changes, and foster a sense of support and emotional well-being. This experiential approach to education may prove more engaging, and therefore successful, than existing strategies. Addressing concerns relating to privacy and liability is a necessary first step to engage providers in this new approach to patient care.

A working understanding of antiepileptic drug development, critical appraisal of drug trial design, and interpretation of study results are fundamental for the neurologist and epileptologist, to incorporate newer anticonvulsant medications into clinical practice. In this Journal Club, we evaluate a phase III study by Krauss et al.1 that demonstrates efficacy and safety of adjunctive perampanel for refractory partial-onset seizures.

[This corrects the article DOI: 10.1371/journal.pone.0033843.].

To characterize the risk for seizures over time in relation to EEG findings in hospitalized adults undergoing continuous EEG monitoring (cEEG).Retrospective analysis of cEEG data and medical records from 625 consecutive adult inpatients monitored at a tertiary medical center. Using survival analysis methods, we estimated the time-dependent probability that a seizure will occur within the next 72-h, if no seizure has occurred yet, as a function of EEG abnormalities detected so far.Seizures occurred in 27% (168/625). The first seizure occurred early (30min of monitoring) in 58% (98/168). In 527 patients without early seizures, 159 (30%) had early epileptiform abnormalities, versus 368 (70%) without. Seizures were eventually detected in 25% of patients with early epileptiform discharges, versus 8% without early discharges. The 72-h risk of seizures declined below 5% if no epileptiform abnormalities were present in the first two hours, whereas 16h of monitoring were required when epileptiform discharges were present. 20% (74/388) of patients without early epileptiform abnormalities later developed them; 23% (17/74) of these ultimately had seizures. Only 4% (12/294) experienced a seizure without preceding epileptiform abnormalities.Seizure risk in acute neurological illness decays rapidly, at a rate dependent on abnormalities detected early during monitoring. This study demonstrates that substantial risk stratification is possible based on early EEG abnormalities.These findings have implications for patient-specific determination of the required duration of cEEG monitoring in hospitalized patients.

The Partners Healthcare Epilepsy Service hosts an epilepsy ‘Webforum'. In this paper, we describe our observations regarding who uses it, what kind of information is exchanged, how much misinformation is present and how we can better serve our patients. We examined a sample of 155 posts to the forum and 342 responses to those posts. The individual making the post and the type of questions were categorized. We also determined whether any information was objectively inaccurate. The principal users were care-givers (49%) and patients (34%). Eighty percent of the primary posts were questions. Answers were given largely by patients (38%) and care-givers (34%). The most commonly asked questions were about treatment options (31%) and the natural history of the illness (28%). In 20% of the questions, the user incidentally remarked that a health-care provider had not met their information needs. Six percent of the information was objectively inaccurate. The Web can serve as an effective means for the exchange of information between individuals with a common medical condition. We found that a small amount of misinformation is exchanged and that health-care providers are sometimes perceived as unable or unwilling to supply important health-relatedinformation.

The presentation and treatment of a patient with extra-temporal non-lesional partial epilepsy is discussed herein. His clinical semiology was consistent with supplementary motor area seizures; however, MR imaging did not demonstrate a lesion. A region of stable cortical glucose hypermetabolism in the left frontal region was noted with 2-fluoro-2-deoxy-D-glucose (FDG)-PET. This was consistent with the frequent interictal discharges evident over the left fronto-temporal region and the stereotypic high amplitude ictal discharges arising with highest amplitude from the left frontal region. Epileptiform activity evident on an intracranial 64-point subdural recording grid placed over the left dorsolateral frontal cortex confirmed a distribution concordant with FDG-PET findings. The subsequent resection was guided by the PET and EEG findings rather than structural MR imaging, and a limited cortical resection led to an immediate and substantial reduction in seizure frequency.

Stroke-associated seizures and epilepsy provide an excellent clinical model to study both acute hyperexcitability after stroke and long-term tissue changes responsible for epileptogenic scar formation. The authors critically review the literature regarding stroke and seizures, to define the clinical spectrum of the association between stroke and seizures. Unfortunately, most of the studies performed in the past were either retrospective and heterogeneous or not designed to address this important issue. Constant improvements and advances in technology, including computerized tomography, magnetic resonance imaging, cerebral angiography and ultrasound, have made possible increasing sophistication in our investigation of patients with stroke and stroke-related seizures and emphasize the need for reassessment of this relationship. Part I gives an overview of the incidence of stroke-associated seizures, their phenomenology and dynamics, and attempts to identify specific risk factors for this association such as stroke subtypes starting with hemorrhagic conditions.

Patients and their care givers have created an impressive array of online health resources. Can healthcare professionals tap into them? In 1994, as a part of an initiative by the department of neurology of the Massachusetts General Hospital to develop promising new ways of using information technology, we began to study how patients with neurological concerns were using online health resources. To our surprise, we found that thousands of patients and their care givers had already created an impressive variety of online health resources. The online support groups, each devoted to a single neurological condition, were especially intriguing. The opportunities that these electronic groups offered for meeting members' needs were more convenient, powerful, and complex than anything we had seen in face to face support groups. For example, patients attending medical centres around the world could compare the treatments their clinicians had recommended. Participants found it easy to send complex medical information (medical journal articles, research reports, etc) to other patients, complete with links to yet other sources. But the groups we observed were scattered and uncoordinated. And although groups existed for most of the common neurological concerns, patients with uncommon conditions had no way of finding one another. We decided that our team of e-health researchers might be able to help—by providing better “homes” for existing support groups, and by encouraging the formation of needed groups. So in March 1995 the hospital's neurology service instituted a family of online groups called the Brain Talk Communities (http://www.braintalk.org/) to support e-patients with neurological concerns. Most medical professionals who have set out to develop online resources for patients have created applications and content in a “top down” manner, directed by health professionals. Within such systems, end users (patients, their care givers, and their family members) usually have little or no input or …

We report on inter-rater agreement in assessing the types of seizures exhibited by one hundred mothers ascertained in a study of the teratogenicity of maternal epilepsy and antiepileptic drugs. A summary of each woman's medical record and a one-page report of her responses to questions about her epilepsy were reviewed independently by six neurologists, three in pediatric neurology and three in adult neurology. Agreement was measured by the kappa statistic and log-linear modeling techniques. The adult neurologists agreed with each other 59% of the time, with the agreement higher when all three used information from the patients' records, such as an EEG, rather than when depending on the patients' responses to questions about their epilepsy. The pediatric neurologists agreed with each other 44% of the time and tended to rely more heavily on information in the patients' records, such as an EEG or a prior diagnosis, compared with the adult neurologists.

To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients.We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG.Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording.In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary.

Experience with prolonged seizures in animal models and humans teaches that cellular injury and cognitive impairment can occur in epilepsy. Status epilepticus probably causes cerebral injury and cognitive dysfunction if it is of long duration; however, studies of electroconvulsive therapy do not support the idea that repeated seizures alone produce a decline in cognitive function. Although many factors related to seizures may correlate with cognitive impairment in certain groups of patients with epilepsy, prospective studies do not support the premise that cognitive impairment develops or progresses in a population of epilepsy patients. When impairment is present, its origin appears to be multifactorial. In addition to the seizures and associated seizure variables (including anticonvulsant medications), interictal epileptiform discharges and the perceptions of the patients and others also may play major roles.

Non-epileptic paroxysmal movement disorders are rare extrapyramidal diseases. The clinical signs are often excluded from differential diagnosis due to their paucity on clinical examination and low prevalence. The paroxysmal, stereotypical nature of non-epileptic paroxysmal movement disorders, as well as the potential response to benzodiazepines, renders these disorders susceptible to misdiagnosis as epileptic seizures. We report a case of paroxysmal non-kinesigenic dyskinesia which was misdiagnosed and treated as epilepsy for decades. The major pathophysiological, diagnostic and therapeutic hallmarks of the disease are summarised. Familiarity and inclusion of the disease in the list of conditions that mimic epilepsy, as well as prolonged video-EEG recordings, may prevent diagnostic delays and unnecessary or belated treatments. [Published with video sequences].

Decision algorithms are developed that use periods of intracranial non-seizure (interictal) EEG to localize epileptogenic networks. Depth and surface recordings are considered from 5 and 6 patients respectively. The proposed algorithms combine spectral and multivariate statistics in a decision-theoretic framework to automatically delineate the seizure onset area. In the case of depth recordings, we apply standard binary classification algorithms, including linear and quadratic discriminative analysis. For the surface recordings, novel decision algorithms are developed, based upon graphical models. The outcomes from the algorithms for both depth and surface recordings are in good agreement with the determination of the seizure focus by clinicians from ictal EEG. In the long term, the proposed approach may lead to shorter hospitalization of intractable-epilepsy patients, since it does not rely on ictal EEG.