Methods for Measuring Seizure Frequency and Severity

Long-term seizure diary tracking habits in clinical studies: Evidence from the Human Epilepsy Project

OBJECTIVE

To characterize seizure tracking patterns of people with focal epilepsy using electronic seizure diary entries, and to assess for risk factors associated with poor tracking.

METHODS

We analyzed electronic seizure diary data from 410 participants with newly diagnosed focal epilepsy in the Human Epilepsy Project 1 (HEP1). Each participant was expected to record data each day during the study, regardless of seizure occurrence. The primary outcome of this post-hoc analysis was whether each participant properly tracked a seizure diary entry each day during their study participation. Using finite mixture modeling, we grouped patient tracking trajectories into data-driven clusters. Once defined, we used multinomial modeling to test for independent risk factors of tracking group membership.

RESULTS

Using over up to three years of daily seizure diary data per subject, we found four distinct seizure tracking groups: consistent, frequent at study onset, occasional, and rare. Participants in the consistent tracking group tracked a median of 92% (interquartile range, IQR: 82%, 99%) of expected days, compared to 47% (IQR:34%, 60%) in the frequent at study onset group, 37% (IQR: 26%, 49%) in the occasional group, and 9% (IQR: 3%, 15%) in the rare group. In multivariable analysis, consistent trackers had lower rates of seizure days per tracked year during their study participation, compared to other groups.

SIGNIFICANCE

Future efforts need to focus on improving seizure diary tracking adherence to improve quality of outcome data, particularly in those with higher seizure burden. In addition, accounting for missing data when using seizure diary data as a primary outcome is important in research trials. If not properly accounted for, total seizure burden may be underestimated and biased, skewing results of clinical trials.

Ambulatory seizure detection

PURPOSE OF REVIEW

To review recent advances in the field of seizure detection in ambulatory patients with epilepsy.

RECENT FINDINGS

Recent studies have shown that wrist or arm wearable sensors, using 3D-accelerometry, electrodermal activity or photoplethysmography, in isolation or in combination, can reliably detect focal-to-bilateral and generalized tonic-clonic seizures (GTCS), with a sensitivity over 90%, and false alarm rates varying from 0.1 to 1.2 per day. A headband EEG has also demonstrated a high sensitivity for detecting and help monitoring generalized absence seizures. In contrast, no appropriate solution is yet available to detect focal seizures, though some promising findings were reported using ECG-based heart rate variability biomarkers and subcutaneous EEG.

SUMMARY

Several FDA and/or EU-certified solutions are available to detect GTCS and trigger an alarm with acceptable rates of false alarms. However, data are still missing regarding the impact of such intervention on patients' safety. Noninvasive solutions to reliably detect focal seizures in ambulatory patients, based on either EEG or non-EEG biosignals, remain to be developed. To this end, a number of challenges need to be addressed, including the performance, but also the transparency and interpretability of machine learning algorithms.

A scoping review on the use of consumer-grade EEG devices for research

BACKGROUND

Commercial electroencephalography (EEG) devices have become increasingly available over the last decade. These devices have been used in a wide variety of fields ranging from engineering to cognitive neuroscience.

PURPOSE

The aim of this study was to chart peer-review articles that used consumer-grade EEG devices to collect neural data. We provide an overview of the research conducted with these relatively more affordable and user-friendly devices. We also inform future research by exploring the current and potential scope of consumer-grade EEG.

METHODS

We followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following online databases: PsycINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, experimental research, validation, signal processing, and clinical) and location of use as indexed by the first author's country.

RESULTS

We identified 916 studies that used data recorded with consumer-grade EEG: 531 were reported in journal articles and 385 in conference papers. Emotiv devices were used most, followed by the NeuroSky MindWave, OpenBCI, interaXon Muse, and MyndPlay Mindband. The most common usage was for brain-computer interfaces, followed by experimental research, signal processing, validation, and clinical purposes.

CONCLUSIONS

Consumer-grade EEG is a useful tool for neuroscientific research and will likely continue to be used well into the future. Our study provides a comprehensive review of their application, as well as future directions for researchers who plan to use these devices.

Deep Brain Stimulation of the Centromedian Nucleus of the Thalamus for Lennox-Gastaut Syndrome: A Systematic Review and Individual Patient Data Analysis

BACKGROUND

Lennox-Gastaut syndrome (LGS) is a severe childhood-onset pharmacoresistant epilepsy. Deep brain stimulation (DBS) of the centromedian nucleus of the thalamus (CMN) has been utilized.

OBJECTIVE

To conduct a systematic review and individual patient data (IPD) analysis to characterize outcomes of DBS of CMN in LGS.

METHODS

PubMed, Embase, and Scopus were searched per Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Articles were screened by title/abstract then full text. Included articles were reviewed for bibliographic, demographic, and outcome data. IPD were extracted from studies providing IPD for all patients.

RESULTS

Of 72 resultant articles, 10 studies (114 patients) were included. Six of 7 studies reporting the outcome of ≥50% seizure reduction indicated that ≥50% of patients achieved this, with improved functional ability. Seizure freedom rate was generally <10%. Six studies with 47 patients provided IPD. The mean ages at epilepsy onset and CMN DBS were 3.9 ± 4.5 years and 17.4 ± 8.8 years, respectively. Nineteen of 41 (46.3%) patients had positive MRI findings. Seizure types included atypical absence in 39 (83.0%) patients, generalized tonic-clonic in 32 (68.1%), tonic in 22 (46.8%), and atonic in 20 (42.6%). Thirty-eight (80.9%) patients experienced ≥50% reduction in seizure frequency, and only 3 (6.4%) experienced seizure freedom. The mean seizure reduction was 62.9% ± 31.2% overall. Quality of life improved in 30/34 (88.2%) and was unchanged in the remainder (11.8%). The complication rate was 2/41 (4.9%). The mean length of follow-up was 19.8 ± 26.1 months (IQR: 4-18 months).

CONCLUSION

Limited data indicate that DBS of the CMN may be effective and safe for people with LGS.

Scoping review of disease-modifying effect of drugs in experimental epilepsy

Objective

Epilepsy affects ~50 million people worldwide causing significant medical, financial, and sociologic concerns for affected patients and their families. To date, treatment of epilepsy is primarily symptomatic management because few effective preventative or disease-modifying interventions exist. However, recent research has identified neurobiological mechanisms of epileptogenesis, providing new pharmacologic targets to investigate. The current scientific evidence remains scattered across multiple studies using different model and experimental designs. The review compiles different models of anti-epileptogenic investigation and highlights specific compounds with potential epileptogenesis-modifying experimental drugs. It provides a platform for standardization of future epilepsy research to allow a more robust compound analysis of compounds with potential for epilepsy prevention.

Methods

PubMed, Ovid MEDLINE, and Web of Science were searched from 2007 to 2021. Studies with murine models of epileptogenesis and explicitly detailed experimental procedures were included in the scoping review. In total, 51 articles were selected from 14,983 and then grouped by five core variables: (1) seizure frequency, (2) seizure severity, (3) spontaneous recurrent seizures (SRS), (4) seizure duration, and (5) mossy fiber sprouting (MFS). The variables were differentiated based on experimental models including methods of seizure induction, treatment schedule and timeline of data collection. Data was categorized by the five core variables and analyzed by converting original treatment values to units of percent of its respective control.

Results

Discrepancies in current epileptogenesis models significantly complicate inter-study comparison of potential anti-epileptogenic interventions. With our analysis, many compounds showed a potential to reduce epileptogenic characteristics defined by the five core variables. WIN55,212-2, aspirin, rapamycin, 1400W, and LEV + BQ788 were identified compounds with the potential of effective anti-epileptic properties.

Significance

Our review highlights the need for consistent methodology in epilepsy research and provides a novel approach for future research. Inconsistent experimental designs hinder study comparison, slowing the progression of treatments for epilepsy. If the research community can optimize and standardize parameters such as methods of seizure induction, administration schedule, sampling time, and aniMal models, more robust meta-analysis and collaborative research would follow. Additionally, some compounds such as rapamycin, WIN 55,212-2, aspirin, 1400W, and LEV + BQ788 showed anti-epileptogenic modulation across multiple variables. We believe they warrant further study both individually and synergistically.

Minimum standards for inpatient long-term video-EEG monitoring: A clinical practice guideline of the international league against epilepsy and international federation of clinical neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events (see Table S1). For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and establish its clinical utility.

Minimum standards for inpatient long-term video-electroencephalographic monitoring: A clinical practice guideline of the International League Against Epilepsy and International Federation of Clinical Neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events. For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and to establish its clinical utility.

Seizure documentation in people living with epilepsy

Seizure documentation is an essential component of epilepsy management. Not all persons with epilepsy choose to document their seizures, but many view the practice as essential to managing their disease. While seizure documentation is a valuable aspect of patient care, clinicians and patients must remain aware that seizure underreport and overreport commonly occur due to lack of seizure awareness. Additionally, in rare cases, persons with epilepsy may intentionally conceal their seizures from clinicians. The continued development of electronic seizure diaries and epilepsy self-management software provides patients with new and expanding options for seizure documentation and disease management. In order for these tools to be utilized most effectively, patient input must be central to their development. Given the limitations of seizure documentation, the development of accurate, non-invasive seizure detection devices is crucial for accurate seizure monitoring.

The Challenging Path to Developing a Mobile Health Device for Epilepsy: The Current Landscape and Where We Go From Here

Seizure detection, and more recently seizure forecasting, represent important avenues of clinical development in epilepsy, promoted by progress in wearable devices and mobile health (mHealth), which might help optimizing seizure control and prevention of seizure-related mortality and morbidity in persons with epilepsy. Yet, very long-term continuous monitoring of seizure-sensitive biosignals in the ambulatory setting presents a number of challenges. We herein provide an overview of these challenges and current technological landscape of mHealth devices for seizure detection. Specifically, we display, which types of sensor modalities and analytical methods are available, and give insight into current clinical practice guidelines, main outcomes of clinical validation studies, and discuss how to evaluate device performance at point-of-care facilities. We then address pitfalls which may arise in patient compliance and the need to design solutions adapted to user experience.

The Epworth Sleepiness Scale in epilepsy: Internal consistency and disease-related associations

BACKGROUND

The Epworth Sleepiness Scale (ESS) is the most common instrument for measuring subjective sleep propensity in people with epilepsy but has not yet been validated in this population.

STUDY OBJECTIVES

We aimed to systematically assess the validity, performance, and internal consistency of the ESS, as well as correlations between the ESS and disease-specific variables and patient-reported outcome measures in a cohort of adults with epilepsy (AWE).

METHODS

Ninety-five AWE completed sleep and seizure diaries, in-laboratory polysomnography (PSG) and patient-reported outcome measures, including the ESS, Insomnia Severity Index (ISI), and the Beck Depression Inventory (BDI). Demographic information and data from 95 matched controls referred for PSG for suspected obstructive sleep apnea (OSA) was taken from the electronic medical record. Frequencies of high ESS item ratings (item score ≥2) were calculated for each group. Cronbach's α and factor analysis were performed to assess the internal consistency and validity of the ESS within cases and controls. Multivariable linear models were used to assess the association between ESS and predictors of interest, adjusting for demographic and disease-specific variables, including seizure type, frequency, and anti-seizure medication (ASM) therapy.

RESULTS

While suspected OSA controls had significantly greater mean ESS total scores (9.9 vs 7.9, p = 0.004) and proportion with ESS >10 (42% vs 25%, p = 0.014), there were no significant differences in the severity of item responses, with the exception of "lying down to rest in the afternoon when circumstances permit," for which more controls rated as likely/very likely (79% vs 64%), p = 0.024). AWE with ESS >10 had higher mean standardized ASM dose (2.5 vs 1.7, p = 0.026). All ESS items were significantly correlated with the total score within each group. Cronbach's α was 0.75 for cases and 0.85 for controls, indicating good internal consistency of the ESS for both groups. After adjusting for demographic and sleep characteristics, higher ESS scores were associated with greater insomnia scores on the ISI (p = 0.024) and depressive symptoms on the BDI (p = 0.018).

CONCLUSIONS

This study provides validity for the use of the ESS in adult populations with epilepsy.

Use of an electronic seizure diary in a randomized, controlled trial of natalizumab in adult participants with drug-resistant focal epilepsy

OBJECTIVE

To analyze electronic diary (e-diary) use in a phase 2, randomized, controlled clinical trial (OPUS; NCT03283371) of natalizumab in adult participants with drug-resistant focal epilepsy.

METHODS

We developed an e-diary, which incorporated an episodic seizure diary and a daily diary reminder, for use as the primary source to record participants' daily seizure activity in the OPUS phase 2 clinical trial. Participants and/or their designated caregivers made e-diary entries by selecting seizure descriptions generated in the participants' and/or caregivers' own words at the time of screening. Seizures and seizure-free days were reported for the current day and for up to 5 and 4 retrospective days, respectively. A record of seizure symptoms entered within the prior 5-day period was displayed on accessing the diary. Changes were not permitted in the e-diary once a seizure record was saved unless a data change request was made. A paper backup diary was available.

RESULTS

E-diary entries (N = 15,176) from the 6-week baseline period and subsequent 24-week placebo-controlled period were analyzed for 66 adults who were randomized and dosed in the OPUS trial. The overall e-diary compliance, defined as the total number of days with any entry out of the total number of days in the baseline and placebo-controlled periods for all participants combined, was 83.6%. Caregivers made 190 (1.3%) e-diary entries. Day-of-event e-diary entries totaled 11,248 (74.1%). At least one paper backup diary was used by 36 (54.5%) participants.

SIGNIFICANCE

Our data highlight that good e-diary compliance can be achieved across participants in randomized clinical trials in adult focal epilepsy. In addition to identifying and addressing any barriers that may prevent a minority of participants from achieving good e-diary compliance, consideration of e-diary elements, such as recall period and reporting of seizure-free days, will facilitate the most accurate data capture in epilepsy clinical trials.

Interpreting deep learning models for epileptic seizure detection on EEG signals

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intel-ligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability of neural network models. We have approached this issue in the context of online detection of epileptic seizures by developing a DL model from EEG signals, and associating certain properties of the model behavior with the expert medical knowledge. This has conditioned the preparation of the input signals, the network architecture, and the post-processing of the output in line with the domain knowledge. Specifically, we focused the discussion on three main aspects: (1) how to aggregate the classification results on signal segments provided by the DL model into a larger time scale, at the seizure-level; (2) what are the relevant frequency patterns learned in the first convolutional layer of different models, and their relation with the delta, theta, alpha, beta and gamma frequency bands on which the visual interpretation of EEG is based; and (3) the identification of the signal waveforms with larger contribution towards the ictal class, according to the activation differences highlighted using the DeepLIFT method. Results show that the kernel size in the first layer determines the interpretability of the extracted features and the sensitivity of the trained models, even though the final performance is very similar after post-processing. Also, we found that amplitude is the main feature leading to an ictal prediction, suggesting that a larger patient population would be required to learn more complex frequency patterns. Still, our methodology was successfully able to generalize patient inter-variability for the majority of the studied population with a classification F1-score of 0.873 and detecting 90% of the seizures.

Translational medicine of the glutamate AMPA receptor

Psychiatric and neurological disorders severely hamper patient's quality of life. Despite their high unmet needs, the development of diagnostics and therapeutics has only made slow progress. This is due to limited evidence on the biological basis of these disorders in humans. Synapses are essential structural units of neurotransmission, and neuropsychiatric disorders are considered as "synapse diseases". Thus, a translational approach with synaptic physiology is crucial to tackle these disorders. Among a variety of synapses, excitatory glutamatergic synapses play central roles in neuronal functions. The glutamate α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) is a principal component of glutamatergic neurotransmission; therefore, it is considered to be a promising translational target. Here, we review the limitations of current diagnostics and therapeutics of neuropsychiatric disorders and advocate the urgent need for the promotion of translational medicine based on the synaptic physiology of AMPAR. Furthermore, we introduce our recent translational approach to these disorders by targeting at AMPARs.

Is the anticonvulsant activity of levetiracetam dose-dependent?

PURPOSE

Although levetiracetam (LEV) is globally established as a leading antiseizure medication (ASM) it is still a controversial matter whether dose increases correspond with an increased efficacy if LEV in the recommended dose range did not show satisfying efficacy. In our clinical perception we questioned the value of dose increases in such non-responders.

METHODS

In this retrospective monocenter study we analyzed the data of adult people with epilepsies (PWE) with focal-onset seizures who had been treated at the department of adults of the Kork Epilepsy Center between 2009 and 2019, who had been on a stable daily LEV dose and in whom LEV was further increased due to further seizures in spite of baseline LEV in a recommended daily dose range. For reasons of data homogeneity, we included only PWE with at least two definite seizures during the hospital stay under the baseline LEV dose who were treated and observed as in-patients after the increase of LEV for a period at least three-fold longer than the baseline interval before. Additional data acquisition comprised clinical data including adverse events, serum concentrations of LEV and other ASMs, and additional laboratory findings. The primary outcome variable was the change of seizure frequency prior to and after the increase of LEV.

RESULTS

Out of 518 PWE who had been on LEV during their hospital stay, a total of 61 PWE fulfilled the inclusion criteria. After a gradual dose increment, 91,8 % of PWE showed a reduced seizure frequency, 73,8 % had a reduction of seizures of 50 % or more, and 21,3 % were seizure-free during the observation period. A significant seizure reduction could be shown with a seizure count of 2,5/week prior to the increment and 0,7/week after dose increment (p < 0,00001). Seven PWE reported minor adverse events and ten PWE showed slight laboratory changes (within normal levels).

CONCLUSION

Contrary to our long-term clinical impression, LEV dose increments were reasonable and improved the seizure situation in PWE, usually without additional safety hazards.

Standard procedures for the diagnostic pathway of sleep-related epilepsies and comorbid sleep disorders: A European Academy of Neurology, European Sleep Research Society and International League against Epilepsy-Europe consensus review

BACKGROUND

Some epilepsy syndromes (sleep-related epilepsies [SRE]) have a strong link with sleep. Comorbid sleep disorders are common in patients with SRE and can exert a negative impact on seizure control and quality of life.

PURPOSES

To define the standard procedures for the diagnostic pathway of patients with possible SRE (scenario 1) and the general management of patients with SRE and comorbidity with sleep disorders (scenario 2).

METHODS

The project was conducted under the auspices of the European Academy of Neurology (EAN), the European Sleep Research Society (ESRS) and the International League against Epilepsy (ILAE) Europe. The framework of the document entailed the following phases: conception of the clinical scenarios; literature review; statements regarding the standard procedures. For literature search a step-wise approach starting from systematic reviews to primary studies was applied. Published studies were identified from the National Library of Medicine's MEDLINE database and Cochrane Library.

RESULTS

Scenario 1: despite a low quality of evidence, recommendations on anamnestic evaluation, tools for capturing the event at home or in the laboratory are provided for specific SRE. Scenario 2: Early diagnosis and treatment of sleep disorders (especially respiratory disorders) in patients with SRE are likely to be beneficial for seizures control.

CONCLUSIONS

Definitive procedures for evaluating patients with SRE are lacking. We provide advice that could be of help for standardising and improving the diagnostic approach of specific SRE. The importance of identifying and treating specific sleep disorders for the management and outcome of patients with SRE is underlined.

Standard procedures for the diagnostic pathway of sleep-related epilepsies and comorbid sleep disorders: an EAN, ESRS and ILAE-Europe consensus review

BACKGROUND AND PURPOSE

Some epilepsy syndromes (sleep-related epilepsies, SREs) have a strong link with sleep. Comorbid sleep disorders are common in patients with SRE and can exert a negative impact on seizure control and quality of life. Our purpose was to define the standard procedures for the diagnostic pathway of patients with possible SRE (scenario 1) and the general management of patients with SRE and comorbidity with sleep disorders (scenario 2).

METHODS

The project was conducted under the auspices of the European Academy of Neurology, the European Sleep Research Society and the International League Against Epilepsy Europe. The framework entailed the following phases: conception of the clinical scenarios; literature review; statements regarding the standard procedures. For the literature search a stepwise approach starting from systematic reviews to primary studies was applied. Published studies were identified from the National Library of Medicine's MEDLINE database and Cochrane Library.

RESULTS

Scenario 1: Despite a low quality of evidence, recommendations on anamnestic evaluation and tools for capturing the event at home or in the laboratory are provided for specific SREs. Scenario 2: Early diagnosis and treatment of sleep disorders (especially respiratory disorders) in patients with SRE are likely to be beneficial for seizure control.

CONCLUSIONS

Definitive procedures for evaluating patients with SRE are lacking. Advice is provided that could be of help for standardizing and improving the diagnostic approach of specific SREs. The importance of identifying and treating specific sleep disorders for the management and outcome of patients with SRE is underlined.

Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy

Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data.

Continued Gap in Seizure Frequency Documentation

Proper documentation during neurology clinic visits is essential. Medical providers that document precise and standardized findings aid other providers, nurses, and research personnel. The American Academy of Neurology (AAN) created standardized quality measures in order to improve delivery of care for patients with epilepsy, providers, and systems. In this article, we reviewed a total of 777 charts in order to find documentation on seizure frequency from the most recent clinical visit. Data was collected from electronic healthcare records. During initial chart review, the following information was noted: age, gender, seizure type(s), etiology type(s), provider (neurologist or epileptologist), whether seizure frequency was noted, and the reason for no documentation. The data review represented a sample of the epilepsy population seen at our institution. Of the 734 individuals, 475 patients had seizure frequency documented (65%). Two hundred and fifty-nine (259) people (35%) were missing seizure frequency data. For those individuals, we determined the reasoning behind why this data was not present in the chart note. Of those 259 charts, there were 65 (25%) charts missing seizure frequency, 161 (62%) charts that were vague, and 33 (13%) charts where seizure frequency could not be determined. Based on our findings, the documentation of seizure frequency is a gap in care.

Subjective and objective hypersomnia highly prevalent in adults with epilepsy

INTRODUCTION

Sleepiness is among the most common complaints of people with epilepsy, but objective documentation is lacking. We systematically investigated subjective and objective sleepiness in an observational cross-sectional cohort of adults with epilepsy (AWE).

METHODS

This is a prospective study of AWE consecutively recruited without foreknowledge of sleep/wake complaints. Polysomnography (PSG) with 18-channel electroencephalography (EEG) followed by multiple sleep latency testing (MSLT) was performed. Patients completed the Epworth Sleepiness Scale (ESS), a single-item question assessing excessive daytime sleepiness (EDS), and a 7-day sleep and seizure diary. Multivariable linear models were used to assess the association between MSLT mean sleep latency (MSL) and interests with adjustment of covariates of interest. Receiver operating characteristics (ROC) analysis was performed to evaluate the discrimination capability of ESS on MSL < 8 min and <5 min and investigate the optimal cutpoints.

RESULTS

Among 127 AWE (mean age: 38.7 ± 13.7 years), abnormal MSL (<8 min) was observed in 49.6% and MSL <5 min in 31.5%. While 78% reported feeling sleepy during the day on a single-item question, only 24% had elevated scores on the ESS (>10/24). The ESS score was associated with MSL even after adjusting for seizure frequency, antiseizure medication (ASM) standardized dose and number, age, gender, depression and insomnia symptom severity, and apnea-hypopnea index (HPI) and total sleep time on PSG (coefficients [95% confidence interval (CI)]: -0.26 [-0.48, -0.05], p = 0.018). The area under the curve (AUC) of the ESS ROC predicting MSL < 8 min and MSL < 5 min were similar: 0.62 (95%CI: 0.52-0.72) and 0.62 (95%CI: 0.51-0.74).

CONCLUSIONS

This is the largest prospective cross-sectional observational study to date using MSLT in AWE. We found subjective and objective daytime sleepiness highly prevalent in AWE and not explained by seizure frequency, ASM burden, symptoms of insomnia/depression, or PSG findings although those with MSL < 5 min were more likely to have obstructive sleep apnea (OSA). Pathologic sleepiness with MSL < 8 min was present in half of AWE. Nearly one-third of AWE unselected for sleep/wake complaints had MSL < 5 min, a range typical of narcolepsy.

Sounds of seizures

PURPOSE

A phase I feasibility study to determine the accuracy of identifying seizures based on audio recordings.

METHODS

We systematically generated 166 audio clips of 30 s duration from 83 patients admitted to an epilepsy monitoring unit between 1/2015 and 12/2016, with one clip during a seizure period and one clip during a non-seizure control period for each patient. Five epileptologists performed a blinded review of the audio clips and rated whether a seizure occurred or not, and indicated the confidence level (low or high) of their rating. The accuracy of individual and consensus ratings were calculated.

RESULTS

The overall performance of the consensus rating between the five epileptologists showed a positive predictive value (PPV) of 0.91 and a negative predictive value (NPV) of 0.66. The performance improved when confidence was high (PPV of 0.96, NPV of 0.70). The agreement between the epileptologists was moderate with a kappa of 0.584. Hyperkinetic (PPV 0.92, NPV 0.86) and tonic-clonic (PPV and NPV 1.00) seizures were most accurately identified. Seizures with automatisms only and non-motor seizures could not be accurately identified. Specific seizure-related sounds associated with accurate identification included disordered breathing (PPV and NPV 1.00), rhythmic sounds (PPV 0.93, NPV 0.80), and ictal vocalizations (PPV 1.00, NPV 0.97).

CONCLUSION

This phase I feasibility study shows that epileptologists are able to accurately identify certain seizure types from audio recordings when the seizures produce sounds. This provides guidance for the development of audio-based seizure detection devices and demonstrate which seizure types could potentially be detected.