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OBJECTIVE: The aim of this study was to determine whether selection of treatment for children with infantile spasms (IS) varies by race/ethnicity. METHODS: The prospective US National Infantile Spasms Consortium database includes children with IS treated from 2012 to 2018. We examined the relationship between race/ethnicity and receipt of standard IS therapy (prednisolone, adrenocorticotropic hormone, vigabatrin), adjusting for demographic and clinical variables using logistic regression. Our primary outcome was treatment course, which considered therapy prescribed for the first and, when needed, the second IS treatment together. RESULTS: Of 555 children, 324 (58%) were non-Hispanic white, 55 (10%) non-Hispanic Black, 24 (4%) non-Hispanic Asian, 80 (14%) Hispanic, and 72 (13%) other/unknown. Most (398, 72%) received a standard treatment course. Insurance type, geographic location, history of prematurity, prior seizures, developmental delay or regression, abnormal head circumference, hypsarrhythmia, and IS etiologies were associated with standard therapy. In adjusted models, non-Hispanic Black children had lower odds of receiving a standard treatment course compared with non-Hispanic white children (odds ratio [OR], 0.42; 95% confidence interval [CI], 0.20-0.89; p = 0.02). Adjusted models also showed that children with public (vs. private) insurance had lower odds of receiving standard therapy for treatment 1 (OR, 0.42; CI, 0.21-0.84; p = 0.01). INTERPRETATION: Non-Hispanic Black children were more often treated with non-standard IS therapies than non-Hispanic white children. Likewise, children with public (vs. private) insurance were less likely to receive standard therapies. Investigating drivers of inequities, and understanding the impact of racism on treatment decisions, are critical next steps to improve care for patients with IS. ANN NEUROL 2022;92:32-44.

ObjectiveTo compare the effectiveness of initial treatment for infantile spasms.MethodsThe National Infantile Spasms Consortium prospectively followed up children with new-onset infantile spasms that began at age 2 to 24 months at 23 US centers (2012-2018). Freedom from treatment failure at 60 days required no second treatment for infantile spasms and no clinical spasms after 30 days of treatment initiation. We managed treatment selection bias with propensity score weighting and within-center correlation with generalized estimating equations.ResultsFreedom from treatment failure rates were as follows: adrenocorticotropic hormone (ACTH) 88 of 190 (46%), oral steroids 42 of 95 (44%), vigabatrin 32 of 87 (37%), and nonstandard therapy 4 of 51 (8%). Changing from oral steroids to ACTH was not estimated to affect response (observed 44% estimated to change to 44% [95% confidence interval 34%-54%]). Changing from nonstandard therapy to ACTH would improve response from 8% to 39% (17%-67%), and changing to oral steroids would improve response from 8% to 38% (15%-68%). There were large but not statistically significant estimated effects of changing from vigabatrin to ACTH (29% to 42% [15%-75%]), from vigabatrin to oral steroids (29% to 42% [28%-57%]), and from nonstandard therapy to vigabatrin (8% to 20% [6%-50%]). Among children treated with vigabatrin, those with tuberous sclerosis complex (TSC) responded more often than others (62% vs 29%; p < 0.05).DiscussionCompared to nonstandard therapy, ACTH and oral steroids are superior for initial treatment of infantile spasms. The estimated effectiveness of vigabatrin is between that of ACTH/oral steroids and nonstandard therapy, although the sample was underpowered for statistical confidence. When used, vigabatrin worked best for TSC.Classification of evidenceThis study provides Class III evidence that for children with new-onset infantile spasms, ACTH or oral steroids were superior to nonstandard therapies.

ObjectiveCommon data elements (CDEs) are currently unavailable for mobile health (mHealth) in epilepsy devices and related applications. As a result, despite expansive growth of new digital services for people with epilepsy, information collected is often not interoperable or directly comparable. We aim to correct this problem through development of industry-wide standards for mHealth epilepsy data.MethodsUsing a group of stakeholders from industry, academia, and patient advocacy organizations, we offer a consensus statement for the elements that may facilitate communication among different systems.ResultsA consensus statement is presented for epilepsy mHealth CDEs.SignificanceAlthough it is not exclusive, we believe that the use of a minimal common information denominator, specifically these CDEs, will promote innovation, accelerate scientific discovery, and enhance clinical usage across applications and devices in the epilepsy mHealth space. As a consequence, people with epilepsy will have greater flexibility and ultimately more powerful tools to improve their lives.

ObjectiveInfantile spasms (IS) represent a severe epileptic encephalopathy presenting in the first 2 years of life. Recommended first-line therapies (hormonal therapy or vigabatrin) often fail. We evaluated response to second treatment for IS in children in whom the initial therapy failed to produce both clinical remission and electrographic resolution of hypsarhythmia and whether time to treatment was related to outcome.MethodsThe National Infantile Spasms Consortium established a multicenter, prospective database enrolling infants with new diagnosis of IS. Children were considered nonresponders to first treatment if there was no clinical remission or persistence of hypsarhythmia. Treatment was evaluated as hormonal therapy (adrenocorticotropic hormone [ACTH] or oral corticosteroids), vigabatrin, or "other." Standard treatments (hormonal and vigabatrin) were compared to all other nonstandard treatments. We compared response rates using chi-square tests and multivariable logistic regression models.ResultsOne hundred eighteen infants were included from 19 centers. Overall response rate to a second treatment was 37% (n = 44). Children who received standard medications with differing mechanisms for first and second treatment had higher response rates than other sequences (27/49 [55%] vs. 17/69 [25%], p < 0.001). Children receiving first treatment within 4 weeks of IS onset had a higher response rate to second treatment than those initially treated later (36/82 [44%] vs. 8/34 [24%], p = 0.040).SignificanceGreater than one third of children with IS will respond to a second medication. Choosing a standard medication (ACTH, oral corticosteroids, or vigabatrin) that has a different mechanism of action appears to be more effective. Rapid initial treatment increases the likelihood of response to the second treatment.

Objective: Epilepsy management employs self‐reported seizure diaries, despite evidence of seizure underreporting. Wearable and implantable seizure detection devices are now becoming more widely available. There are no clear guidelines about what levels of accuracy are sufficient. This study aimed to simulate clinical use cases and identify the necessary level of accuracy for each. Methods: Using a realistic seizure simulator (CHOCOLATES), a ground truth was produced, which was then sampled to generate signals from simulated seizure detectors of various capabilities. Five use cases were evaluated: (1) randomized clinical trials (RCTs), (2) medication adjustment in clinic, (3) injury prevention, (4) sudden unexpected death in epilepsy (SUDEP) prevention, and (5) treatment of seizure clusters. We considered sensitivity (0%–100%), false alarm rate (FAR; 0–2/day), and device type (external wearable vs. implant) in each scenario. Results: The RCT case was efficient for a wide range of wearable parameters, though implantable devices were preferred. Lower accuracy wearables resulted in subtle changes in the distribution of patients enrolled in RCTs, and therefore higher sensitivity and lower FAR values were preferred. In the clinic case, a wide range of sensitivity, FAR, and device type yielded similar results. For injury prevention, SUDEP prevention, and seizure cluster treatment, each scenario required high sensitivity and yet was minimally influenced by FAR. Significance: The choice of use case is paramount in determining acceptable accuracy levels for a wearable seizure detection device. We offer simulation results for determining and verifying utility for specific use case and specific wearable parameters. [ABSTRACT FROM AUTHOR]

Objective: Wrist‐ or ankle‐worn devices are less intrusive than the widely used electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom‐developed deep‐learning seizure detection models, we demonstrate the detection of a broad range of seizure types by wearable signals. Methods: Patients admitted to the epilepsy monitoring unit were enrolled and asked to wear wearable sensors on either wrists or ankles. We collected patients' electrodermal activity, accelerometry (ACC), and photoplethysmography, from which blood volume pulse (BVP) is derived. Board‐certified epileptologists determined seizure onset, offset, and types using video and EEG recordings per the International League Against Epilepsy 2017 classification. We applied three neural network models—a convolutional neural network (CNN) and a CNN–long short‐term memory (LSTM)‐based generalized detection model and an autoencoder‐based personalized detection model—to the raw time‐series sensor data to detect seizures and utilized performance measures, including sensitivity, false positive rate (the number of false alarms divided by the total number of nonseizure segments), number of false alarms per day, and detection delay. We applied a 10‐fold patientwise cross‐validation scheme to the multisignal biosensor data and evaluated model performance on 28 seizure types. Results: We analyzed 166 patients (47.6% female, median age = 10.0 years) and 900 seizures (13 254 h of sensor data) for 28 seizure types. With a CNN‐LSTM‐based seizure detection model, ACC, BVP, and their fusion performed better than chance; ACC and BVP data fusion reached the best detection performance of 83.9% sensitivity and 35.3% false positive rate. Nineteen of 28 seizure types could be detected by at least one data modality with area under receiver operating characteristic curve >.8 performance. Significance: Results from this in‐hospital study contribute to a paradigm shift in epilepsy care that entails noninvasive seizure detection, provides time‐sensitive and accurate data on additional clinical seizure types, and proposes a novel combination of an out‐of‐the‐box monitoring algorithm with an individualized person‐oriented seizure detection approach. [ABSTRACT FROM AUTHOR]