Gauging seizure risk

Controversies on the network theory of epilepsy: Debates held during the ICTALS 2019 conference

Debates on six controversial topics on the network theory of epilepsy were held during two debate sessions, as part of the International Conference for Technology and Analysis of Seizures, 2019 (ICTALS 2019) convened at the University of Exeter, UK, September 2-5 2019. The debate topics were (1) From pathologic to physiologic: is the epileptic network part of an existing large-scale brain network? (2) Are micro scale recordings pertinent for defining the epileptic network? (3) From seconds to years: do we need all temporal scales to define an epileptic network? (4) Is it necessary to fully define the epileptic network to control it? (5) Is controlling seizures sufficient to control the epileptic network? (6) Does the epileptic network want to be controlled? This article, written by the organizing committee for the debate sessions and the debaters, summarizes the arguments presented during the debates on these six topics.

Incidence of seizure exacerbation and injury related to football participation in people with epilepsy

INTRODUCTION

There is scant evidence to quantify the risk of contact sports such as football to patients with epilepsy. This retrospective review was performed to evaluate the incidence of injuries or seizure exacerbation related to football participation in patients with epilepsy.

METHODS

Between the years 1994 and 2004, 157,709 consecutive clinic notes were searched for mention of "football" and "epilepsy" or "seizure". Resulting notes were reviewed to quantify the number of seizure exacerbations and the number of injuries in this cohort.

RESULTS

Seven of 44 subjects with epilepsy (15.9%) experienced injury while playing football. Four of 32 (12.5%) patients experienced seizure exacerbation during a time when they were concurrently participating in football though 3 of these patients stopped taking or were weaned off of their antiepileptic drugs (AEDs). One in 32 patients with epilepsy (3.1%) had an exacerbation of seizures while playing football and consistently taking AEDs.

CONCLUSION

The risk of injury and seizure exacerbation due to participation in football for patients with epilepsy is low. Clinicians should use their best judgment in deciding whether contact sports increase risks for a particular patient based on individual seizure frequency, concurrent neurological and medical issues, and medication adverse effects.

The role of devices in managing risk

Over the last few years, there has been significant expansion of wearable technologies and devices into the health sector, including for conditions such as epilepsy. Although there is significant potential to benefit patients, there is a paucity of well-conducted scientific research in order to inform patients and healthcare providers of the most appropriate technology. In addition to either directly or indirectly identifying seizure activity, the ideal device should improve quality of life and reduce the risk of sudden unexpected death in epilepsy (SUDEP). Devices typically monitor a number of parameters including electroencephalographic (EEG), cardiac, and respiratory patterns and can detect movement, changes in skin conductance, and muscle activity. Multimodal devices are emerging with improved seizure detection rates and reduced false positive alarms. While convulsive seizures are reliably identified by most unimodal and multimodal devices, seizures associated with no, or minimal, movement are frequently undetected. The vast majority of current devices detect but do not actively intervene. At best, therefore, they indicate the presence of seizure activity in order to accurately ascertain true seizure frequency or facilitate intervention by others, which may, nevertheless, impact the rate of SUDEP. Future devices are likely to both detect and intervene within an autonomous closed-loop system tailored to the individual and by self-learning from the analysis of patient-specific parameters. The formulation of standards for regulatory bodies to validate seizure detection devices is also of paramount importance in order to confidently ascertain the performance of a device; and this will be facilitated by the creation of a large, open database containing multimodal annotated data in order to test device algorithms. This paper is for the Special Issue: Prevent 21: SUDEP Summit - Time to Listen.

Seizure prediction and intervention

Epilepsy treatment is challenging due to a lack of essential diagnostic tools, including methods for reliable seizure detection in the ambulatory setting, to assess seizure risk over time and to monitor treatment efficacy. This lack of objective diagnostics constitutes a significant barrier to better treatments, raises methodological concerns about the antiseizure medication evaluation process and, to patients, is a main issue contributing to the disease burden. Recent years have seen rapid progress towards better diagnostics that meet these needs of epilepsy patients and clinicians. Availability of comprehensive data and the rise of more powerful computational analysis methods have driven progress in this area. Here, we provide an overview on data- and theory-driven approaches aimed at identifying methods to reliably detect and forecast seizures as well as to monitor brain excitability and treatment efficacy in epilepsy. We provide a particular account on neural criticality, the hypothesis that cortical networks may be poised in a critical state at the boundary between different types of dynamics, and discuss its role in informing diagnostics to track cortex excitability and seizure risk in recent experiments. With the further expansion of digitalization in medicine, tele-medicine and long-term, ambulatory monitoring, these computationally based methods may gain more relevance in epilepsy in the future. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.

Dealing with the storm: An overview of seizure precipitants and spontaneous seizure worsening in drug-resistant epilepsy

In drug-resistant epilepsy, periods of seizure stability may alternate with abrupt worsening, with frequent seizures limiting the individual's independence and physical, social, and psychological well-being. Here, we review the literature focusing on different clinical scenarios related to seizure aggravation in people with drug-resistant epilepsy. The role of antiseizure medication (ASM) changes is examined, especially focusing on paradoxical seizure aggravation after increased treatment. The external provocative factors that unbalance the brittle equilibrium of seizure control are reviewed, distinguishing between unspecific triggering factors, specific precipitants, and 'reflex' mechanisms. The chance of intervening surgical or medical conditions, including somatic comorbidities and epilepsy surgery failure, causing increased seizures is discussed. Spontaneous exacerbation is also explored, emphasizing recent findings on subject-specific circadian and ultradian rhythms. Awareness of external precipitants and understanding the subject-specific spontaneous epilepsy course may allow individuals to modify their lifestyles. It also allows clinicians to counsel appropriately and to institute suitable medical treatment to avoid sudden loss of seizure control.

Patient and caregiver preferences for the potential benefits and risks of a seizure forecasting device: A best-worst scaling

BACKGROUND

Epilepsy is the 4th most common neurological disorder and is characterized by recurrent, unpredictable seizures. The ability to forecast seizures is a significant unmet need and would have a transformative effect on the lives of people living with epilepsy. In an effort to address this need, the Epilepsy Foundation has committed effort and resources to promote the development of seizure forecasting devices (SFD).

OBJECTIVE

To promote user-centered design of future SFD, we sought to quantify patient and caregiver preferences for the potential benefits and risks of SFD.

METHODS

A community-centered approach was used to develop a survey incorporating a novel best-worst scaling (BWS) to assess preferences for SFD. A main-effect orthogonal array was used to design and generate 18 "prototypes" that systematically varied across six attributes: seizure forecasting probability, seizure forecasting range, inaccuracy of forecasting, amount of time required to use the device, how the device is worn, and cost. The dependent variable was the attributes that respondents selected the best and worst in each profile, and a choice model was estimated using conditional logistic regression, which was also stratified and compared across patients and caregivers. Respondents also indicated that they would accept each of the prototype SFDs if it were real. These acceptance data and net monetary benefits (relative to the least preferred SFD) were explored.

RESULTS

There were 633 eligible respondents; 493 (78%) completed at least one task. Responses indicated that 346 (68%) had epilepsy, and 147 (29%) were primary caregivers or family members of someone with epilepsy. The data show that short forecasting range is the most favored among experimental attributes, followed by mid forecasting range and notification of high chance of seizure. Having the device implanted is the least favorable attribute. Stated preferences differed between patients and caregivers (p < 0.001) for range of forecasting and inaccuracy of device. Caregivers preferred any range of forecasting, regardless of length, more than patients. Patients cared less about inaccuracy of the device compared to caregivers. The groups also differ in impact of fear of having seizures (versus actually having seizures) (p = 0.034) and on device acceptance. The acceptance of devices ranged from 42.3% to 95%, with caregivers being more likely to use a device (p < 0.05) for the majority of device profiles. Acceptance of devices varied with net monetary benefit of the best device being $717.44 more per month relative to the least preferred device.

CONCLUSION

Our finding extends previous calls for seizure forecasting devices by demonstrating the value that they might provide to patients and caregivers affected by epilepsy and the feature that might be most and least desirable. In addition to guiding device development, the data can help inform regulatory decisions makers.