The Ohio State University Wexner Medical Center Ringgold standard institution - Neurology 395 W. 12th Ave 7th floor, Columbus, Ohio 43210, USA.
Epileptic Disord. 2022 Feb 1;24(1):75-81. doi: 10.1684/epd.2021.1363.
We aimed to study the ictal EEG patterns in patients with non-convulsive seizures (NCS) and their relationship with underlying etiology and patient outcome. We conducted a retrospective review of EEG studies from patients undergoing continuous EEG (cEEG) monitoring for indication of altered mental status with a suspicion of NCS. Ictal EEG findings of NCS were categorized as three patterns: focal or generalized epileptiform discharges (EDs) at frequencies >2.5 Hz (Pattern 1); EDs at frequencies of ≤2.5 Hz or rhythmic activity >0.5 Hz with spatiotemporal evolution (Pattern 2); and EDs with ≤2.5 Hz with subtle clinical correlate during the ictal EEG or clinical and EEG improvement after a trial of IV anti-seizure drugs (Pattern 3). Patients with anoxic brain injury were excluded from the study. Associations between ictal EEG patterns and underlying etiology and their impact on in-hospital mortality was measured. Of 487 patients included in the study, NCS was recorded on cEEG monitoring in 57 (12%). The ictal EEG Pattern 2 was the most commonly seen ictal EEG finding in our cohort of patients with NCS (70%, n=40/57), followed by Pattern 3 (15%, n=9/57) and Pattern 1(14%, n=8/57). In patients with acute brain injury, Pattern 2 (67%, n=27/40) was a commonly seen ictal EEG finding, whereas Pattern 1 (62% n=5/8) was seen in patients with underlying acute medical illness. No statistically significant difference was found between ictal EEG patterns and underlying neurological versus medical etiologies (p=0.27) or in-hospital mortality (p=0.5). Spatiotemporal evolution of epileptiform discharges at a lower frequency was the most commonly recorded ictal EEG pattern in our cohort. Further prospective studies with a larger sample size of patients with NCS may provide valuable clinical data that could be used to evaluate the etiologic correlate of the various ictal EEG patterns and their effect on outcome.
我们旨在研究非惊厥性发作（NCS）患者的发作期脑电图（EEG）模式及其与潜在病因和患者结局的关系。我们对因精神状态改变而接受连续 EEG（cEEG）监测并怀疑发生 NCS 的患者进行了回顾性 EEG 研究。将 NCS 的发作期 EEG 发现分为三种模式：频率>2.5 Hz 的局灶性或全身性癫痫样放电（ED）（模式 1）；频率为≤2.5 Hz 或具有时空演变的节律性活动>0.5 Hz（模式 2）；以及发作期 EEG 期间具有≤2.5 Hz 的 ED 且临床相关性不明显或在静脉注射抗癫痫药物试验后临床和 EEG 改善（模式 3）。我们排除了因缺氧性脑损伤的患者。测量了发作期 EEG 模式与潜在病因之间的关联及其对住院死亡率的影响。在纳入的 487 例患者中，57 例（12%）在 cEEG 监测中记录到 NCS。在我们的 NCS 患者队列中，最常见的发作期 EEG 发现是模式 2（70%，n=40/57），其次是模式 3（15%，n=9/57）和模式 1（14%，n=8/57）。在急性脑损伤患者中，模式 2（67%，n=27/40）是常见的发作期 EEG 发现，而模式 1（62%，n=5/8）见于潜在的急性内科疾病患者。在发作期 EEG 模式与潜在的神经或内科病因之间未发现统计学上的显著差异（p=0.27）或住院死亡率（p=0.5）。在我们的队列中，最常见的发作期 EEG 记录是频率较低的癫痫样放电的时空演变。进一步的前瞻性研究可能会提供有价值的临床数据，这些数据可用于评估各种发作期 EEG 模式的病因学相关性及其对结局的影响，纳入更大样本量的 NCS 患者。
