Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, U.S.A.
Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, U.S.A.
Epilepsia. 2014 Dec;55(12):2059-2068. doi: 10.1111/epi.12852. Epub 2014 Nov 10.
Because early etiologic identification is critical to select appropriate specific status epilepticus (SE) management, we aim to validate a clinical tool we developed that uses history and readily available investigations to guide prompt etiologic assessment.
This prospective multicenter study included all adult patients treated for SE of all but anoxic causes from four academic centers. The proposed tool is designed as a checklist covering frequent precipitating factors for SE. The study team completed the checklist at the time the patient was identified by electroencephalography (EEG) request. Only information available in the emergency department or at the time of in-hospital SE identification was used. Concordance between the etiology indicated by the tool and the determined etiology at hospital discharge was analyzed, together with interrater agreement.
Two hundred twelve patients were included. Concordance between the etiology hypothesis generated using the tool and the finally determined etiology was 88.7% (95% confidence interval (CI) 86.4-89.8) (κ = 0.88). Interrater agreement was 83.3% (95% CI 80.4-96) (κ = 0.81).
This tool is valid and reliable for identification early the etiology of an SE. Physicians managing patients in SE may benefit from using it to identify promptly the underlying etiology, thus facilitating selection of the appropriate treatment.
由于早期病因识别对于选择适当的特定癫痫持续状态(SE)管理至关重要,我们旨在验证我们开发的一种临床工具,该工具使用病史和现成的检查来指导快速病因评估。
这项前瞻性多中心研究纳入了来自四个学术中心的所有非缺氧性病因治疗的成年 SE 患者。该工具设计为一个检查表,涵盖了 SE 的常见诱发因素。研究团队在脑电图(EEG)请求确定患者时完成检查表。仅使用急诊科或住院 SE 识别时可用的信息。分析了工具提示的病因与出院时确定的病因之间的一致性,并分析了组内一致性。
共纳入 212 例患者。使用工具生成的病因假设与最终确定的病因之间的一致性为 88.7%(95%置信区间[CI] 86.4-89.8)(κ=0.88)。组内一致性为 83.3%(95%CI 80.4-96)(κ=0.81)。
该工具可有效可靠地识别 SE 的病因。管理 SE 患者的医生可能受益于使用它快速识别潜在病因,从而有助于选择适当的治疗方法。