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

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.