Pan Yi, Laohathai Christopher, Weber Daniel J
Department of Neurology, Saint Louis University, SLUCare Academic Pavilion, 1008 S. Spring, St. Louis, MO 63110, USA.
Epilepsy Behav Rep. 2020 Nov 17;15:100408. doi: 10.1016/j.ebr.2020.100408. eCollection 2021.
EEG monitoring in the ICU is essential for diagnosing seizures in critically ill patients. Neurology residents are the frontline for rapid diagnosis of seizures. Residents received EEG training through didactic lectures and their epilepsy rotations. We hypothesized that seizure recognition was dependent on epilepsy rotation, not the seniority of the residency. Residents were taught ACNS Standardized Critical Care EEG Terminology, unified EEG terminology and criteria for non-convulsive status epilepticus. EEG segments were given to residents for seizure recognition, and explanations provided to residents after each test. Anonymous results with the postgraduate training year (PGY) and time spent in epilepsy rotation were collected. These tests were conducted 3 times, with total of 48 EEG segments, between October, 2017 and May, 2019. There were 43 participates, including 4 PGY-1 (9.3%), 20 PGY-2 (46.5%), 12 PGY-3 (27.9%), and 7 PGY-4 (16.3%) residents. The mean rate of seizure recognition was 57.1% in PGY-1, 63.8% in PGY-2, 58.4% in PGY-3, and 70.1% in PGY-4. Comparing the duration of epilepsy rotations, the mean correct scores of seizure recognition were 58.6%, 64.6%, 64.4%, and 67.3% for duration at 0, 0.5, 1, and 2 months respectively. There was no significant difference regarding the PGY or the time of epilepsy rotation statistically by ANOVA (p = 0.37). Seizure recognition in the EEG of a critically ill patient is not solely dependent time spent in epilepsy rotation or stage of residency training. EEG interpretation skill may require an alternate approach, and continuous training.
重症监护病房(ICU)中的脑电图(EEG)监测对于诊断重症患者的癫痫发作至关重要。神经内科住院医师是快速诊断癫痫发作的一线人员。住院医师通过理论讲座和癫痫轮转接受脑电图培训。我们假设癫痫发作的识别取决于癫痫轮转,而非住院医师培训的年限。向住院医师传授了美国临床神经生理学会(ACNS)标准化重症监护脑电图术语、统一的脑电图术语以及非惊厥性癫痫持续状态的标准。将脑电图片段提供给住院医师进行癫痫发作识别,并在每次测试后为住院医师提供解释。收集了匿名的研究生培训年份(PGY)和在癫痫轮转中花费的时间等结果。在2017年10月至2019年5月期间,这些测试进行了3次,共有48个脑电图片段。有43名参与者,包括4名PGY - 1(9.3%)、20名PGY - 2(46.5%)、12名PGY - 3(27.9%)和7名PGY - 4(16.3%)住院医师。PGY - 1的癫痫发作识别平均率为57.1%,PGY - 2为63.8%,PGY - 3为58.4%,PGY - 4为70.1%。比较癫痫轮转的时长,癫痫发作识别的平均正确分数在轮转时长为0、0.5、1和2个月时分别为58.6%、64.6%、64.4%和67.3%。通过方差分析(ANOVA),PGY或癫痫轮转时间在统计学上没有显著差异(p = 0.37)。重症患者脑电图中的癫痫发作识别不仅仅取决于在癫痫轮转中花费的时间或住院医师培训阶段。脑电图解读技能可能需要另一种方法以及持续培训。