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Epilepsy & behavior : E&B · 2023

Predicting seizure clustering in the epilepsy monitoring unit: A multivariable analysis.

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Обработка статьи · этапы, ошибки и управление
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Maliekal Leya, Zutshi Deepti, Millis Scott, Basha Maysaa M

Аннотация

INTRODUCTION: Seizure clustering, is the most frequently reported adverse event in epilepsy monitoring unit (EMU) safety studies which, can also potentiate other adverse events, such as falls, status epilepticus, and increased length of stay. The purpose of this study is to determine variables associated with increased risk of seizure clustering among patients admitted to the EMU.

METHODS: A retrospective review of patients admitted to the EMU over a two-year period was completed. Data collected included patient demographics, types of epilepsy, seizure frequency, anti-seizure medications (ASMs) and hospital and EMU course including incidence of seizure clustering.

RESULTS: Two hundred seven patients were included in our study; of these, ninety patients experienced two or more seizures in a 24-hour period (24SC), and 68 patients experienced two or more seizures in a 4-hour period (4SC). Logistic regression analysis associated the absence of long-acting ASM with increased clustering within the 4SC group (p = 0.038). For every additional ASM taken by a patient at home, the odds of seizure clustering increased by 81% in the 4SC group (p = 0.009) and by 61% in the 24SC group (p = 0.022). In addition, patients with a diagnosis of temporal lobe epilepsy had some association with clustering in the 24SC group (p = 0.061).

CONCLUSION: Our data showed that long-acting ASMs can be protective against seizure clustering. Furthermore, patients with temporal lobe epilepsy, and those on increased numbers of ASMs, were more likely to experience seizure clustering when undergoing medication withdrawal during an EMU evaluation.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты