Interdepartmental Division of Critical Care, Li Ka Shing Knowledge Institute, 204 Victoria Street, 4th Floor, Room 411, Toronto, Ontario, M5B 1T8, Canada.
Department of Critical Care Medicine, Sunnybrook Health Sciences Center, Toronto, Ontario, Canada.
Syst Rev. 2020 Aug 10;9(1):175. doi: 10.1186/s13643-020-01439-x.
Use of electroencephalography (EEG) is currently recommended by the American Clinical Neurophysiology Society for a wide range of indications, including diagnosis of nonconvulsive status epilepticus and evaluation of unexplained disorders of consciousness. Data interpretation usually occurs by expert personnel (e.g., epileptologists, neurophysiologists), with information relayed to the primary care team. However, data cannot always be read in time-sensitive fashion, leading to potential delays in EEG interpretation and patient management. Multiple training programs have recently been described to enable non-experts to rapidly interpret EEG at the bedside. A comprehensive review of these training programs, including the tools used, outcomes obtained, and potential pitfalls, is currently lacking. Therefore, the optimum training program and implementation strategy remain unknown.
We will conduct a systematic review of descriptive studies, case series, cohort studies, and randomized controlled trials assessing training programs for EEG interpretation by non-experts. Our primary objective is to comprehensively review educational programs in this domain and report their structure, patterns of implementation, limitations, and trainee feedback. Our secondary objective will be to compare the performance of non-experts for EEG interpretation with a gold standard (e.g., interpretation by a certified electroencephalographers). Studies will be limited to those performed in acute care settings in both adult and pediatric populations (intensive care unit, emergency department, or post-anesthesia care units). Comprehensive search strategies will be developed for MEDLINE, EMBASE, WoS, CINAHL, and CENTRAL to identify studies for review. The gray literature will be scanned for further eligible studies. Two reviewers will independently screen the search results to identify studies for inclusion. A standardized data extraction form will be used to collect important data from each study. If possible, we will attempt to meta-analyze the quantitative data. If heterogeneity between studies is too high, we will present meaningful quantitative comparisons of secondary outcomes as per the synthesis without meta-analysis (SWiM) reporting guidelines.
We will aim to summarize the current literature in this domain to understand the structure, patterns, and pitfalls of EEG training programs for non-experts. This review is undertaken with a view to inform future education designs, potentially enabling rapid detection of EEG abnormalities, and timely intervention by the treating physician.
Submitted and undergoing review. Registration ID: CRD42020171208 .
目前,美国临床神经生理学会推荐广泛使用脑电图 (EEG),包括诊断非惊厥性癫痫持续状态和评估不明原因的意识障碍。数据解释通常由专家人员(例如癫痫专家、神经生理学家)进行,信息传达给初级保健团队。然而,数据并不总是能够及时读取,这导致 EEG 解释和患者管理可能出现延迟。最近已经描述了多个培训计划,以使非专家能够快速床边解读 EEG。目前,缺乏对这些培训计划的全面审查,包括所使用的工具、获得的结果和潜在的陷阱。因此,最佳的培训计划和实施策略仍不清楚。
我们将对描述性研究、病例系列、队列研究和评估非专家 EEG 解读培训计划的随机对照试验进行系统评价。我们的主要目标是全面审查该领域的教育计划,并报告其结构、实施模式、局限性和学员反馈。我们的次要目标是将非专家的 EEG 解读表现与黄金标准(例如,由认证脑电图专家进行的解读)进行比较。研究将限于成人和儿科人群(重症监护病房、急诊室或麻醉后护理单位)的急性护理环境中进行。将制定综合搜索策略,以查找 MEDLINE、EMBASE、WoS、CINAHL 和 CENTRAL 中的研究进行审查。将对灰色文献进行扫描,以查找其他合格的研究。两名评审员将独立筛选搜索结果,以确定纳入的研究。将使用标准化的数据提取表格从每项研究中收集重要数据。如果可能,我们将尝试对定量数据进行荟萃分析。如果研究之间存在高度异质性,我们将根据综合无荟萃分析 (SWiM) 报告指南,对次要结果进行有意义的定量比较。
我们的目标是总结该领域的现有文献,以了解非专家 EEG 培训计划的结构、模式和陷阱。进行这项审查是为了为未来的教育设计提供信息,有可能使医生能够更快地发现 EEG 异常并及时进行干预。
已提交并正在审查中。注册号:CRD42020171208。