连续脑电图（cEEG）监测的适应证：它们能告诉我们什么？

Indications for continuous electroencephalographic (cEEG) monitoring: What do they tell us?

机构信息

Department of Neurology, Epilepsy Division, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.

Department of Public Health Sciences, Division of Biostatistics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.

出版信息

Epilepsy Res. 2023 Feb;190:107088. doi: 10.1016/j.eplepsyres.2023.107088. Epub 2023 Jan 20.

DOI:10.1016/j.eplepsyres.2023.107088

PMID:36731271

Abstract

OBJECTIVE

While studies have explored clinical and EEG predictors of seizures on continuous EEG (cEEG), the role of cEEG indications as predictors of seizures has not been studied. Our study aims to fill this knowledge gap.

METHODS

We used the prospective cEEG database at Cleveland Clinic for the 2016 calendar year. Patients ≥ 18 years who underwent cEEG for the indication of altered mental status (AMS) and seizure-like events (SLE: motor or patient-reported events) were included. Baseline characteristics and EEG findings were compared between the two groups. Multivariable regression was used to compare the two groups and identify seizure detection risk factors.

RESULTS

Of 2227 patients (mean age 59.4 years) who met the inclusion criteria, 882 (50% females) underwent cEEG for AMS and 1345(51% females) for SLE. SLE patients were younger(OR: 0.988, CI: 0.98-0.99, p < 0.001), had longer monitoring(OR:1.04, CI:1.00-1.07, p = 0.033), were more likely to have epilepsy-related-breakthrough seizures(OR:25.9, CI:0.5.89-115, p < 0.001), psychogenic non-epileptic spells (OR:6.85, CI:1.60-29.3, p = 0.008), were more awake (p < 0.001) and more likely to be on anti-seizure medications(OR:1.60, CI:1.29-1.98, p < 0.001). On multivariable analysis, SLE was an independent predictor of seizure detection (OR: 2.60, CI: 1.77-3.88, p < 0.001).

SIGNIFICANCE

Our findings highlight the differences in patients undergoing cEEG for AMS vs. SLE. SLE as a cEEG indication represents an independent predictor of seizures on cEEG and, therefore, deserves special attention. Future multicenter studies are needed to validate our findings.

摘要

目的

虽然已有研究探讨了连续脑电图（cEEG）中癫痫发作的临床和脑电图预测因素，但 cEEG 指征作为癫痫发作预测因素的作用尚未得到研究。我们的研究旨在填补这一知识空白。

方法

我们使用克利夫兰诊所 2016 年的前瞻性 cEEG 数据库。纳入接受 cEEG 检查以明确意识状态改变（AMS）和癫痫样事件（SLE：运动或患者报告的事件）指征的≥18 岁患者。比较两组患者的基线特征和脑电图发现。采用多变量回归比较两组患者并确定癫痫检测的危险因素。

结果

符合纳入标准的 2227 例患者（平均年龄 59.4 岁）中，882 例（50%为女性）因 AMS 接受 cEEG 检查，1345 例（51%为女性）因 SLE 接受 cEEG 检查。SLE 患者年龄更小（OR：0.988，95%CI：0.98-0.99，p<0.001），监测时间更长（OR：1.04，95%CI：1.00-1.07，p=0.033），更有可能发生与癫痫相关的突破性发作（OR：25.9，95%CI：0.5.89-115，p<0.001）、心因性非癫痫性发作（OR：6.85，95%CI：1.60-29.3，p=0.008），更清醒（p<0.001），更有可能使用抗癫痫药物（OR：1.60，95%CI：1.29-1.98，p<0.001）。多变量分析显示，SLE 是癫痫发作检测的独立预测因素（OR：2.60，95%CI：1.77-3.88，p<0.001）。