Impact of diagnostic delay on seizure outcome in newly diagnosed focal epilepsy

Improving epilepsy diagnosis across the lifespan: approaches and innovations

Epilepsy diagnosis is often delayed or inaccurate, exposing people to ongoing seizures and their substantial consequences until effective treatment is initiated. Important factors contributing to this problem include delayed recognition of seizure symptoms by patients and eyewitnesses; cultural, geographical, and financial barriers to seeking health care; and missed or delayed diagnosis by health-care providers. Epilepsy diagnosis involves several steps. The first step is recognition of epileptic seizures; next is classification of epilepsy type and whether an epilepsy syndrome is present; finally, the underlying epilepsy-associated comorbidities and potential causes must be identified, which differ across the lifespan. Clinical history, elicited from patients and eyewitnesses, is a fundamental component of the diagnostic pathway. Recent technological advances, including smartphone videography and genetic testing, are increasingly used in routine practice. Innovations in technology, such as artificial intelligence, could provide new possibilities for directly and indirectly detecting epilepsy and might make valuable contributions to diagnostic algorithms in the future.

Which psychogenic nonepileptic seizure (PNES) patients are more likely to be treated with anti-seizure medications?

BACKGROUND

The average time for psychogenic nonepileptic seizures (PNES) diagnosis is about 7.5 years. Many patients receive inadequate treatment and sometimes even life-threatening treatments such as tracheal intubation during this time.

PURPOSE

To determine the risk factors for misdiagnosis of PNES as Epilepsy.

METHODS

The medical records of patients who underwent video-electroencephalogram (EEG) monitoring were reviewed retrospectively. Patients who had PNES without epileptic seizures (ES) were included in this study. Baseline personal and monitoring characteristics were collected. The patients were then divided into two groups based on their therapeutic status. Patients in the treatment group were again divided into two groups based on the number of anti-seizure medications (ASM) they were treated with.

RESULTS

Fifty-seven patients diagnosed with PNES were included in this study. Thirty-seven patients were under treatment, and 20 patients were not under treatment at the time of monitoring. Motor seizures, abnormal interictal EEG patterns, and pathological brain imaging findings were more frequent among patients in the treatment group (p<0.05). Patients with motor seizures were more likely to be treated with multiple ASM than patients with only dialeptic nonmotor seizures (p<0.05). Lastly, patients in the treatment group were monitored longer and had fewer seizures during monitoring (p<0.05).

CONCLUSION

PNES patients with abnormal EEG patterns and pathological brain imaging findings are more likely to be treated with ASM. The pure dialeptic nature of seizures is less likely to be misdiagnosed as ES. In addition, patients with such seizures are less likely to be treated with multiple treatment lines.

Referral odyssey plot to visualize causes of surgical delay in mesial temporal lobe epilepsy with hippocampal sclerosis

The "odyssey plot" was used to visualize referral delays in epilepsy surgery. Participants were 36 patients (19 males; 13-67 years, median 27 years) with mesial temporal lobe epilepsy with hippocampal sclerosis (HS) who underwent resection surgery. The "referral odyssey plot" included five clinical episodes: seizure onset (T1), first visits to a non-epileptologist (T2) and to an epileptologist (T3), first admission to our epilepsy monitoring unit (EMU) (T4), and resection surgery (T5). For each patient, we identified the first seizure type: the physician who first diagnosed focal aware seizure (FAS), focal impaired awareness seizure (FIAS), focal to bilateral tonic-clonic seizure (FBTCS), and radiologically suspected HS. Within the overall delay (T1-T5, median 18 years; interquartile range [IQR] 14), non-epileptologist's delay (T2-T3, 11.5 years; IQR 12.25) was far (p < 0.0001) longer than patient's (T1-T2, 0 year; IQR 2.25), epileptologist's (T3-T4, 1 year; IQR 4), or after-EMU delay (T4-T5, 1 year; IQR 1). FAS onset cases had significantly longer T1-T2 (N = 5, median 7 years; IQR 6) than FIAS (N = 22, 0 year; IQR 1, p < 0.005) or FBTCS onset cases (N = 9, 0 year; IQR 0, p < 0.001). FAS was correctly diagnosed first by non-epileptologists in 17.9%, by out-patient epileptologists in 35.7%, and at the EMU in 46.4%. FIAS was correctly diagnosed first by non-epileptologists in 94.4% and by out-patient epileptologists in 5.6%. Non-epileptologists diagnosed FBTCS in all cases. HS was diagnosed by non-epileptologists in 13.9%, by out-patient epileptologists in 47.2%, and at the EMU in 38.9%. Early referral to epileptologists is most critical for early surgery. Early utilization of the EMU is highly recommended because FAS is often overlooked by outpatient epileptologists. The odyssey plot will be useful to improve the healthcare system for other types of epilepsy.

Ambulatory video EEG extended to 10 days: A retrospective review of a large database of ictal events

OBJECTIVE

This work aims to determine the ambulatory video electroencephalography monitoring (AVEM) duration and number of captured seizures required to resolve different clinical questions, using a retrospective review of ictal recordings.

METHODS

Patients who underwent home-based AVEM had event data analyzed retrospectively. Studies were grouped by clinical indication: differential diagnosis, seizure type classification, or treatment assessment. The proportion of studies where the conclusion was changed after the first seizure was determined, as was the AVEM duration needed for at least 99% of studies to reach a diagnostic conclusion.

RESULTS

The referring clinical question was not answered entirely by the first event in 29.6% (n = 227) of studies. Diagnostic and classification indications required a minimum of 7 days for at least 99% of studies to be answered, whilst treatment-assessment required at least 6 days.

CONCLUSIONS

At least 7 days of monitoring, and potentially multiple events, are required to adequately answer these clinical questions in at least 99% of patients. The widely applied 72 h or single event recording cut-offs may be inadequate to adequately answer these three indications in a substantial proportion of patients.

SIGNIFICANCE

Extended duration of monitoring and capturing multiple events should be considered when attempting to capture seizures on video-EEG.

Automatic Detection of Abnormal EEG Signals Using WaveNet and LSTM

Neurological disorders have an extreme impact on global health, affecting an estimated one billion individuals worldwide. According to the World Health Organization (WHO), these neurological disorders contribute to approximately six million deaths annually, representing a significant burden. Early and accurate identification of brain pathological features in electroencephalogram (EEG) recordings is crucial for the diagnosis and management of these disorders. However, manual evaluation of EEG recordings is not only time-consuming but also requires specialized skills. This problem is exacerbated by the scarcity of trained neurologists in the healthcare sector, especially in low- and middle-income countries. These factors emphasize the necessity for automated diagnostic processes. With the advancement of machine learning algorithms, there is a great interest in automating the process of early diagnoses using EEGs. Therefore, this paper presents a novel deep learning model consisting of two distinct paths, WaveNet-Long Short-Term Memory (LSTM) and LSTM, for the automatic detection of abnormal raw EEG data. Through multiple ablation experiments, we demonstrated the effectiveness and importance of all parts of our proposed model. The performance of our proposed model was evaluated using TUH abnormal EEG Corpus V.2.0.0. (TUAB) and achieved a high classification accuracy of 88.76%, which is higher than in the existing state-of-the-art research studies. Moreover, we demonstrated the generalization of our proposed model by evaluating it on another independent dataset, TUEP, without any hyperparameter tuning or adjustment. The obtained accuracy was 97.45% for the classification between normal and abnormal EEG recordings, confirming the robustness of our proposed model.

Implementing WHO's Intersectoral Global Action Plan for epilepsy and other neurological disorders in Southeast Asia: a proposal

The World Health Assembly approved the Intersectoral Global Action Plan for epilepsy and neurological disorders. Member states, including those in Southeast Asia, must now prepare to achieve IGAP's strategic targets by embracing novel approaches and strengthening existing policies and practices. We propose and present evidence to support four such processes. The opening course should engage all stakeholders to develop people-centric instead of outcome-centric approaches. Rather than caring for convulsive epilepsy alone, as currently done, primary care providers should also be skilled in diagnosing and treating focal and non-motor seizures. This could reduce the diagnostic gap as over half of epilepsies present with focal seizures. Currently, primary care providers lack knowledge and skills to manage focal seizures. Technology-enabled aids can help overcome this limitation. Lastly, there is need to add newer "easy to use" epilepsy medicines to Essential Medicines lists in light of emerging evidence for better tolerability, safety and user-friendliness.

On epilepsy perception: Unravelling gaps and issues

Epilepsy is one of the most common neurological diseases, but it can sometimes be under-reported or have a time delay in diagnosis. This data is not surprising if we consider that a person often seeks medical attention only after presenting a generalized tonic-clonic seizure. Epilepsy diagnostic delay is caused by several factors: under-reporting by patients, under-diagnosed epileptic manifestations by inexperienced clinicians, and lack of time in the emergency setting. The consequences of this delay are increased accidents, a high rate of premature mortality, and economic expanses for the healthcare system. Moreover, people with epilepsy have a higher probability of comorbidities than the general population, such as mood disorders or cognitive problems. Along with recurrent seizures, these comorbid diseases promote isolation and stigmatization of people with epilepsy, who suffer from discrimination at school, in the workplace, and even in social relationships. Public awareness of epilepsy and its comorbidities is necessary to prevent diagnostic delays and overcome social and professional iniquities for people with epilepsy.

Treatment gaps in epilepsy

Over 50 million people around the world have epilepsy, and yet, epilepsy recognition and access to care are ongoing issues. Nearly 80% of people with epilepsy live in low-and middle-income countries and face the greatest barriers to quality care. However, there are substantial disparities in care within different communities in high-income countries as well. Across the world, under-recognition of seizures continues to be an issue, leading to diagnostic and treatment delays. This stems from issues surrounding stigma, public education, basic access to care, as well as healthcare worker education. In different regions, people may face language barriers, economic barriers, and technological barriers to timely diagnosis and treatment. Even once diagnosed, people with epilepsy often face gaps in optimal seizure control with the use of antiseizure medications. Additionally, nearly one-third of people with epilepsy may be candidates for epilepsy surgery, and many either do not have access to surgical centers or are not referred for surgical evaluation. Even those who do often experience delays in care. The purpose of this review is to highlight barriers to care for people with epilepsy, including issues surrounding seizure recognition, diagnosis of epilepsy, and the initiation and optimization of treatment.

Drivers of US health care spending for persons with seizures and/or epilepsies, 2010-2018

OBJECTIVE

This study was undertaken to characterize spending for persons classified with seizure or epilepsy and to determine whether spending has increased over time.

METHODS

In this cross-sectional study, we pooled data from the Medical Expenditure Panel Survey (MEPS) household component files for 2010-2018. We matched cases to controls on age and sex of a population-based sample of MEPS respondents (community-dwelling persons of all ages) with records associated with a medical event (e.g., outpatient visit, hospital inpatient) for seizure, epilepsy, or both. Outcomes were weighted to be representative of the civilian, noninstitutionalized population. We estimated the treated prevalence of epilepsy and seizure, health care spending overall and by site of care, and trends in spending growth.

RESULTS

We identified 1078 epilepsy cases and 2344 seizure cases. Treated prevalence was .38% (95% confidence interval [CI] = .34-.41) for epilepsy, .76% (95% CI = .71-.81) for seizure, and 1.14% (95% CI = 1.08-1.20) for epilepsy or seizure. The difference in annual spending for cases compared to controls was $4580 (95% CI = $3362-$5798) for epilepsy, $7935 (95% CI, $6237-$9634) for seizure, and $6853 (95% CI = $5623-$8084) for epilepsy or seizure, translating into aggregate costs of $5.4 billion, $19.0 billion, and $24.5 billion. From 2010 to 2018, the annual growth rate in total spending incurred for seizures and/or epilepsies was 7.6% compared to 3.6% among controls.

SIGNIFICANCE

US economic burden of seizures and/or epilepsies is substantial and warrants interventions focused on their unique and overlapping causes.

Canadian epilepsy priority-setting partnership: Toward a new national research agenda

BACKGROUND

Health research agendas are often set by researchers or by industry and may not reflect the needs and priorities of end users. This priority-setting partnership (PSP) for epilepsy was undertaken to identify the most pressing unanswered questions about epilepsy and seizures from the perspective of people with epilepsy (PWE) and their care providers.

METHODS

Using the methodology developed by the James Lind Alliance (JLA), evidence uncertainties were gathered via online surveys from stakeholders across Canada. Submissions were formed into summary questions and checked against existing evidence to determine if they were true uncertainties. Verified uncertainties were then ranked by patients, caregivers, and healthcare providers and a final workshop was held to reach a consensus on the top 10 priorities.

RESULTS

The final top 10 list reflects the priority areas of focus for research as identified by the Canadian epilepsy community, including genetic markers for diagnosis and treatment, concerns about living with the long-term effects of epilepsy, and addressing knowledge gaps in etiology and treatment approaches.

CONCLUSION

This project represents the first systematic evidence of patient- and clinician-centered research priorities for epilepsy. The results of this priority-setting exercise provide an opportunity for researchers and funding agencies to align their agendas with the values and needs of the epilepsy community in order to improve clinical outcomes and quality of life (QOL) for PWE.

Diagnostic Delay in Epilepsy: the Scope of the Problem

PURPOSE OF REVIEW

Diagnostic delay is an increasingly recognized issue in epilepsy. At the same time, there is a clear disparity between public awareness of epilepsy and that of other public health issues. A contributing factor for this seems to be a lack of studies testing interventions designed to improve seizure recognition. In this review, we summarize the main findings from recent studies investigating diagnostic delay in epilepsy, highlighting causes, consequences, and potential interventions in future research that may improve quality of care in this population.

RECENT FINDINGS

Building on prior evidence, diagnostic delay in patients with new-onset focal epilepsy has been identified as an important problem for patients with epilepsy. Such delay in diagnosis can lead to delayed treatment and potentially preventable morbidity and mortality including motor vehicle accidents. Nonmotor seizure semiology appears to be a major contributor for delay; such seizures are largely unrecognized when patients present to emergency departments for care. Improving recognition and diagnosis of recurrent nonmotor seizures in emergency departments represents a significant opportunity for improving time to diagnosis, particularly when patients present following a first lifetime motor seizure and meet diagnostic criteria for epilepsy. Diagnostic delay in epilepsy is a significant public health issue and recent studies have highlighted potential areas for intervention.

Missed, mistaken, stalled: Identifying components of delay to diagnosis in epilepsy

A substantial proportion of individuals with newly diagnosed epilepsy report prior seizures, suggesting a missed opportunity for early epilepsy care and management. Consideration of the causes and outcomes of diagnostic delay is needed to address this issue. We aimed to review the literature pertaining to delay to diagnosis of epilepsy, describing the components, characteristics, and risk factors for delay. We undertook a systematic search of the literature for full-length original research papers with a focus on diagnostic delay or seizures before diagnosis, published 1998-2020. Findings were collated, and a narrative review was undertaken. Seventeen papers met the inclusion criteria. Studies utilized two measures of diagnostic delay: seizures before diagnosis and/or a study-defined time between first seizure and presentation/diagnosis. The proportion of patients with diagnostic delay ranged from 16% to 77%; 75% of studies reported 38% or more to be affected. Delays of 1 year or more were reported in 13%-16% of patients. Seizures prior to diagnosis were predominantly nonconvulsive, and usually more than one seizure was reported. Prior seizures were often missed or mistaken for symptoms of other conditions. Key delays in the progression to specialist review and diagnosis were (1) "decision delay" (the patient's decision to seek/not seek medical review), (2) "referral delay" (delay by primary care/emergency physician referring to specialist), and (3) "attendance delay" (delay in attending specialist review). There were few data available relevant to risk factors and virtually none relevant to outcomes of diagnostic delay. This review found that diagnostic delay consists of several components, and progression to diagnosis can stall at several points. There is limited information relating to most aspects of delay apart from prevalence and seizure types. Risk factors and outcomes may differ according to delay characteristics and for each of the key delays, and recommendations for future research include examining each before consideration of interventions is made.