Nonconvulsive status epilepticus is a commonly overlooked cause of altered mental status. This study assessed nonconvulsive status epilepticus prevalence in emergency department (ED) patients with acute neurologic presentations using limited electroencephalogram (EEG) coupled with artificial intelligence (AI)-enhanced seizure detection technology. We then compared the accuracy of the AI EEG interpretations to those performed by an epileptologist. In a prospective observational cohort analysis, adult patients with unexplained mental status changes identified by emergency physicians received expedited placement of a limited EEG. Data collected encompassed patient demographics, clinical history, EEG interpretations by the AI algorithm and epileptologists, treatments, and disposition determinations. There were 134 device applications on 132 patients (2 received the device twice) enrolled in the study, but 16 were missing data critical for identification or analysis and 9 did not meet the selection criteria. Of the 108 limited EEGs interpreted by an epileptologist, 69 were abnormal (diffuse slowing, highly epileptiform patterns, or spikes and sharps), 41 were normal, 5 were uninterpretable, and 3 captured episodes of seizure or status epilepticus. Limited EEG AI interpretation detected >90% seizure burden in 2 of 3 cases of seizure or status epilepticus as well as in 2 abnormal EEGs and 1 normal EEG, providing a sensitivity of 66.7% (95% confidence interval 9.4 to 99.2), a specificity of 97.0% (95% confidence interval 91.5 to 99.4), and a disease prevalence of 2.9%. Limited AI-enhanced EEG can detect nonconvulsive status epilepticus in the ED; however, the technology tended to overestimate seizure burden in our cohort. This study found a lower nonconvulsive status epilepticus prevalence compared to prior literature reports.

中文翻译：

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快速脑电图和人工智能在非惊厥性癫痫发作检测和管理中的应用


非惊厥性癫痫持续状态是导致精神状态改变的一个经常被忽视的原因。本研究使用有限脑电图 （EEG） 结合人工智能 （AI） 增强癫痫发作检测技术，评估了急性神经系统表现的急诊科 （ED） 患者的非惊厥癫痫持续状态患病率。然后，我们将 AI EEG 解释的准确性与癫痫科医生进行的准确性进行了比较。在一项前瞻性观察队列分析中，急诊医生发现的患有不明原因精神状态变化的成年患者接受了有限脑电图的快速放置。收集的数据包括患者人口统计学、临床病史、AI 算法和癫痫科医生的脑电图解释、治疗和处置确定。该研究对 132 名患者 （2 名接受了该设备进行了两次） 进行了 134 次设备应用，但 16 项缺少对识别或分析至关重要的数据，9 项不符合选择标准。在癫痫科医生解释的 108 例有限脑电图中，69 例异常（弥漫性慢速、高度癫痫样模式或尖峰和尖锐），41 例正常，5 例无法解释，3 例捕获癫痫发作或癫痫持续状态。有限的脑电图 AI 解释在 3 例癫痫发作或癫痫持续状态病例中的 2 例以及 2 例异常脑电图和 1 例正常脑电图中检测到 >90% 的癫痫发作负担，提供 66.7% 的敏感性（95% 置信区间 9.4 至 99.2），特异性为 97.0%（95% 置信区间 91.5 至 99.4），疾病患病率为 2.9%。有限的 AI 增强脑电图可以检测 ED 中的非惊厥性癫痫持续状态;然而，该技术往往高估了我们队列中的癫痫发作负担。 这项研究发现，与以前的文献报道相比，非惊厥性癫痫持续状态的患病率较低。