Richard H. C. Lazeron

Seizure detection devices can improve the safety of children with epilepsy, yet high false alarms limit their clinical applicability. Here, we investigated whether specific time periods are disproportionately prone to false alarms. We analyzed 2876 NightWatch alarms occurring between 19:00 and 09:00 in 65 children (ages 3–16, 48% female). Temporal distributions differed significantly between true and false alarms ( p < 0.001), with a significant divergence in skewness ( p = 0.001); notably, 30% of false alarms occurred between 06:00 and 09:00. This suggests NightWatch performance is adversely affected by wakefulness and morning arousal. Our findings support exploring time‐ or state‐dependent detection thresholds to reduce false alarms. Trial Registration: The PROMISE (NCT03909984) and LICSENSE (NTR4115/NR395) trials were registered at the Dutch Trial Registry.

To assess thecost-effectiveness of cenobamate in epileptic people ith focal seizures in theNetherlands. A Markov model was used tosimulate lifetime costs and quality-adjusted life years (QALYs) for cenobamatecompared to perampanel, brivaracetam, and lacosamide from the Dutch societalperspective. Data from a randomized controlled trial and open-label extension wereused to determine the transition probability, efficacy and safety of treatmentwith cenobamate. Treatment, administration, routine monitoring, seizure eventmanagement, adverse events and productivity costs were included. Both one-wayand probabilistic sensitivity analyses were conducted to explore theuncertainty. Cenobamatewas associated with an average total cost of €466,560 and 9.922 QALY gained.Among the four drugs tested, treatment with cenobamate indicated lowest costand highest QALY gained, suggesting cenobamate dominates all comparators. One-waysensitivity analysisconfirms the robustness of our results. Probabilisticsensitivity analyses revealed that at the willingness to pay threshold of€50,000/QALY, the probability that cenobamate is cost-effective was 100%. With the acknowledgment of the limitations, weconcluded that cenobamate is less costly and more effective, which can beconsidered a cost-effective treatment option for patients with drug-resistantfocal seizures in the Netherlands. Future real-world data are needed to confirmour findings.

Objective: To describe the characteristics of psychogenic non‐epileptic (functional) seizures (PNES) in adults with epilepsy and intellectual disability (ID) and to establish differences and risk factors regarding psychosocial functioning between individuals with and without PNES.Methods: Adults with ID and epilepsy living in epilepsy care facilities in The Netherlands were screened for PNES by a neurologist. A control group consisting of people with epilepsy and ID, without PNES, was matched according to age, sex, and level of ID. Objective data were retrieved retrospectively from clinical notes of the resident. Standardized questionnaires and tests, adjusted for people with ID, were obtained from participants and their nursing staff. Differences were analyzed using paired t tests, Wilcoxon signed‐rank tests, or McNemar's tests, appropriate for matched case–control studies. Conditional logistic regression identified PNES risk factors.Results: Five hundred forty individuals were screened, of which 42 had PNES (point prevalence 7.8%). In total, 35 cases and 35 controls gave consent. Proxy reports indicated that PNES impacted daily life in 79% by adjusting the individual's schedule, and caused minor injuries in one‐third. Those with PNES were mainly female (69%); had a mild (46%) or moderate (37%) level of ID; showed more symptoms of depression (p = .024), anxiety (p = .030), self‐injurious behavior (p = .015); and experienced more negative life events (p < .001). Clinically relevant predictors of PNES were the number of negative life events (odds ratio [OR] 1.71, 95% confidence interval [CI] 1.12–2.53) and self‐injurious behaviors (OR 5.27, 95% CI .97–28.81).Significance: Previously, PNES in individuals with ID and epilepsy were described mainly as a reinforced behavioral pattern, due to limited associations with psychiatric disorders. Our results demonstrate that this population does show individual psychosocial vulnerabilities when measured with instruments adjusted for this population, as indicated by proxy reports from daily caregivers. Viewing PNES as an involuntary response, especially for stress‐prone individuals with ID, could reduce stigma and improve treatment.

Objective: There is a pressing need for reliable automated seizure detection in epilepsy care. Performance evidence on ambulatory non‐electroencephalography‐based seizure detection devices is low, and evidence on their effect on caregiver's stress, sleep, and quality of life (QoL) is still lacking. We aimed to determine the performance of NightWatch, a wearable nocturnal seizure detection device, in children with epilepsy in the family home setting and to assess its impact on caregiver burden.Methods: We conducted a phase 4, multicenter, prospective, video‐controlled, in‐home NightWatch implementation study (NCT03909984). We included children aged 4–16 years, with ≥1 weekly nocturnal major motor seizure, living at home. We compared a 2‐month baseline period with a 2‐month NightWatch intervention. The primary outcome was the detection performance of NightWatch for major motor seizures (focal to bilateral or generalized tonic–clonic [TC] seizures, focal to bilateral or generalized tonic seizures lasting >30 s, hyperkinetic seizures, and a remainder category of focal to bilateral or generalized clonic seizures and "TC‐like" seizures). Secondary outcomes included caregivers' stress (Caregiver Strain Index [CSI]), sleep (Pittsburgh Quality of Sleep Index), and QoL (EuroQol five‐dimension five‐level scale).Results: We included 53 children (55% male, mean age = 9.7 ± 3.6 years, 68% learning disability) and analyzed 2310 nights (28 173 h), including 552 major motor seizures. Nineteen participants did not experience any episode of interest during the trial. The median detection sensitivity per participant was 100% (range = 46%–100%), and the median individual false alarm rate was .04 per hour (range = 0–.53). Caregiver's stress decreased significantly (mean total CSI score = 8.0 vs. 7.1, p = .032), whereas caregiver's sleep and QoL did not change significantly during the trial.Significance: The NightWatch system demonstrated high sensitivity for detecting nocturnal major motor seizures in children in a family home setting and reduced caregiver stress.

Objective: To assess the performance of a multimodal seizure detection device, first tested in adults (sensitivity 86%, PPV 49%), in a pediatric cohort living at home or residential care.Methods: In this multicenter, prospective, video‐controlled cohort‐study, nocturnal seizures were detected by heartrate and movement changes in children with epilepsy and intellectual disability. Participants with a history of >1 monthly major motor seizure wore Nightwatch bracelet at night for 3 months. Major seizures were defined as tonic–clonic, generalized tonic >30 s, hyperkinetic, or clusters (>30 min) of short myoclonic or tonic seizures. The video of all events (alarms and nurse diaries) and about 10% of whole nights were reviewed to classify major seizures, and minor or no seizures.Results: Twenty‐three participants with focal or generalized epilepsy and nightly motor seizures were evaluated during 1511 nights, with 1710 major seizures. First 1014 nights, 4189 alarms occurred with average of 1.44/h, showing average sensitivity of 79.9% (median 75.4%) with mean PPV of 26.7% (median 11.1%) and false alarm rate of 0.2/hour. Over 90% of false alarms in children was due to heart rate (HR) part of the detection algorithm. To improve this rate, an adaptation was made such that the alarm was only triggered when the wearer was in horizontal position. For the remaining 497 nights, this was tested prospectively, 384 major seizures occurred. This resulted in mean PPV of 55.5% (median 58.1%) and a false alarm rate 0.08/h while maintaining a comparable mean sensitivity of 79.4% (median 93.2%).Significance: Seizure detection devices that are used in bed which depend on heartrate and movement show similar sensitivity in children and adults. However, children do show general higher false alarm rate, mostly triggered while awake. By correcting for body position, the false alarms can be limited to a level that comes close to that in adults.

Veel patiënten en familieleden van patiënten met epilepsie hebben zorgen over de risico’s van epilepsie, waaronder Sudden Unexpected Death in Epilepsy, maar ook over de gevolgen van aanvallen zoals verwondingen en status epilepticus. Aanvalsdetectie kan bij een deel van de patiënten worden gebruikt om te alarmeren bij het optreden van een epileptische aanval. Er zijn verschillende apparaten die aanvallen kunnen detecteren. In Kempenhaeghe begeleiden we patiënten bij de zoektocht naar het juiste apparaat.

Objective: Electroencephalography (EEG) interpretations through visual (by human raters) and automated (by computer technology) analysis were still not reliable for the diagnosis of nonconvulsive status epilepticus (NCSE). This study aimed to identify typical pitfalls in the EEG analysis and make suggestions as to how those pitfalls might be avoided. Methods: We analyzed the EEG recordings of individuals who had clinically confirmed or suspected NCSE. Epileptiform EEG activity during seizures (ictal discharges) was visually analyzed by 2 independent raters. We investigated whether unreliable EEG visual interpretations quantified by low interrater agreement can be predicted by the characteristics of ictal discharges and individuals’ clinical data. In addition, the EEG recordings were automatically analyzed by in-house algorithms. To further explore the causes of unreliable EEG interpretations, 2 epileptologists analyzed EEG patterns most likely misinterpreted as ictal discharges based on the differences between the EEG interpretations through the visual and automated analysis. Results: Short ictal discharges with a gradual onset (developing over 3 s in length) were liable to be misinterpreted. An extra 2 min of ictal discharges contributed to an increase in the kappa statistics of >0.1. Other problems were the misinterpretation of abnormal background activity (slow-wave activities, other abnormal brain activity, and the ictal-like movement artifacts), continuous interictal discharges, and continuous short ictal discharges. Conclusion: A longer duration criterion for NCSE-EEGs than 10 s that is commonly used in NCSE working criteria is recommended. Using knowledge of historical EEGs, individualized algorithms, and context-dependent alarm thresholds may also avoid the pitfalls.

Objective: Electroencephalography (EEG) interpretations through visual (by human raters) and automated (by computer technology) analysis are still not reliable for the diagnosis of non-convulsive status epilepticus (NCSE). This study aimed to identify typical pitfalls in the EEG analysis and make suggestions as to how those pitfalls might be avoided. Methods: We analyzed the EEG recordings of individuals who had clinically confirmed or suspected NCSE. Epileptiform EEG activity during seizures (ictal discharges) were visually analyzed by two independent raters. We investigated whether unreliable EEG visual interpretations quantified by low inter-rater agreement can be predicted by the characteristics of ictal discharges and individuals’ clinical data. In addition, the EEG recordings were automatically analyzed by in-house algorithms. To further explore the causes of unreliable EEG interpretations, two epileptologists analyzed EEG patterns most likely misinterpreted as ictal discharges based on the differences between the EEG interpretations through the visual and automated analysis. Results: Short ictal discharges with a gradual onset (developing over 3 seconds in length) were liable to be misinterpreted. An extra 2 minutes of ictal discharges contributed to an increase in the kappa statistics of > 0.1. Other problems were the misinterpretation of abnormal background activity (slow wave activities, other abnormal brain activity, and the ictal-like movement artifacts), continuous interictal discharges, and continuous short ictal discharges. Conclusion: A longer duration criterion for NCSE-EEGs than 10 seconds that commonly used in NCSE working criteria is needed. Using knowledge of historical EEGs, individualized algorithms, and context-dependent alarm thresholds may also avoid the pitfalls.