Bellini Anna, Curti Davide Gusmeo, Cursi Marco, Cecchetti Giordano, Agosta Federica, Fanelli Giovanna F, Filippi Massimo
Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
J Neurol. 2024 Aug;271(8):5137-5145. doi: 10.1007/s00415-024-12464-4. Epub 2024 May 31.
Epileptic seizures pose challenges in emergency departments (ED), affecting up to 10% of admitted patients. This study aimed to assess emergency electroencephalogram (EmEEG) utilization, identifying factors predicting seizure detection and its influence on clinical decisions.
A retrospective review of 1135 EmEEGs on 1017 patients at a tertiary teaching hospital between June 2022 and June 2023 was conducted. Data included demographics, medical history, EmEEG indications, neuroimaging findings, and clinical outcomes. Statistical analyses utilized Fisher's exact tests and logistic regression models.
EmEEG detected status epilepticus-related seizures in 5.40% of cases, seizures without status epilepticus in 3.05%, and status epilepticus without discrete seizures in 3.74%. Epileptiform abnormalities were noted in 22.12% of EmEEGs. EmEEG influenced initial diagnoses (21.24%), antiseizure medication changes (20.85%), and discharge decisions (39.04%). Predictors for seizures/status epilepticus included previous neurosurgery, seizures in the ED, and cognitive/behavioral impairment (p < 0.001). EmEEG significantly altered initial diagnoses based on witnessed seizures, involuntary movements, epileptiform abnormalities, and 1-2 Hz generalized periodic discharges (p < 0.001). Changes in antiseizure medications correlated with seizure occurrence, neuroimaging results, epileptiform abnormalities, and EEG background slowing (p < 0.001). Factors influencing discharge decisions included previous neurosurgery, consciousness impairment, acute neuroimaging pathology, EEG focal slowing, and EEG background slowing (p < 0.001).
The study clarifies EmEEG's role in modifying initial diagnoses, treatment approaches, and discharge decisions. The study provides insights into the nuanced impact of EmEEG in different clinical scenarios, offering valuable guidance for clinicians in selecting patients for EmEEG, particularly in conditions of limited EEG availability.
癫痫发作给急诊科带来了挑战，影响高达10%的住院患者。本研究旨在评估急诊脑电图（EmEEG）的使用情况，确定预测癫痫检测的因素及其对临床决策的影响。
对2022年6月至2023年6月期间一家三级教学医院1017例患者的1135份EmEEG进行回顾性研究。数据包括人口统计学、病史、EmEEG指征、神经影像学检查结果和临床结局。统计分析采用Fisher精确检验和逻辑回归模型。
EmEEG在5.40%的病例中检测到与癫痫持续状态相关的发作，在3.05%的病例中检测到无癫痫持续状态的发作，在3.74%的病例中检测到无离散发作的癫痫持续状态。22.12%的EmEEG记录到癫痫样异常。EmEEG影响初始诊断（21.24%）、抗癫痫药物的改变（20.85%）和出院决策（39.04%）。癫痫发作/癫痫持续状态的预测因素包括既往神经外科手术、急诊科发作以及认知/行为障碍（p<0.001）。基于目击发作、不自主运动、癫痫样异常和1-2Hz广泛性周期性放电，EmEEG显著改变了初始诊断（p<0.001）。抗癫痫药物的改变与癫痫发作、神经影像学结果、癫痫样异常和脑电图背景减慢相关（p<0.001）。影响出院决策的因素包括既往神经外科手术、意识障碍、急性神经影像学病变、脑电图局灶性减慢和脑电图背景减慢（p<0.001）。
该研究阐明了EmEEG在改变初始诊断、治疗方法和出院决策方面的作用。该研究深入探讨了EmEEG在不同临床场景中的细微影响，为临床医生选择进行EmEEG检查的患者提供了有价值的指导，尤其是在脑电图资源有限的情况下。
