Karanjia P N, Nelson J J, Lefkowitz D S, Dick A R, Toole J F, Chambless L E, Hayes R, Howard V J
Department of Neurology, Marshfield Clinic, WI, USA.
Neurology. 1997 Feb;48(2):346-51. doi: 10.1212/wnl.48.2.346.
An easily administered questionnaire and algorithm classifying transient ischemic attacks (TIAs) or strokes, and also their distribution, could be invaluable for identifying endpoints in epidemiologic studies or clinical trials of prevention and therapy of cerebral ischemia. The Asymptomatic Carotid Atherosclerosis Study (ACAS) devised a symptom-based questionnaire and algorithm for detecting events in the trial. The purpose of this study was to determine sensitivity, specificity, and agreement rates of the questionnaire and algorithm against diagnoses of a panel of cerebrovascular disease authorities.
Three hundred eighty-one men and women at eight medical centers reported symptoms of stroke, TIA, or other neurologic illness. The questionnaire was administered by trained interviewers and the responses were analyzed using the algorithm. A standardized neurologic examination was performed by a neurologist. Data were submitted to two or more external reviewers. Sensitivity, specificity, and the kappa statistic (kappa) were used to evaluate the relationship between the algorithm and the external reviewers' diagnosis.
Of the 381 reviews, 196 were diagnosed as TIA or stroke by the external panel. The algorithm's agreement with the diagnosis of TIA or stroke was 80.1%, and kappa was 0.60. Sensitivity was 87.8%, and specificity was 71.9%.
While statistical agreement rates depend on the method of sample selection, the algorithm has a high agreement with an external panel of experts and is a sensitive tool for event detection. The lower specificity indicates that careful neurologic evaluation may be required to confirm or refute events identified by the screening algorithm.
一份易于实施的用于对短暂性脑缺血发作（TIA）或中风及其分布进行分类的问卷和算法，对于在脑缺血预防和治疗的流行病学研究或临床试验中确定终点可能具有极高价值。无症状颈动脉粥样硬化研究（ACAS）设计了一份基于症状的问卷和算法来检测试验中的事件。本研究的目的是确定该问卷和算法相对于一组脑血管疾病权威诊断的敏感性、特异性和符合率。
八个医疗中心的381名男性和女性报告了中风、TIA或其他神经系统疾病的症状。问卷由经过培训的访谈者进行发放，其回答使用该算法进行分析。由一名神经科医生进行标准化的神经系统检查。数据提交给两名或更多外部评审员。敏感性、特异性和kappa统计量（kappa）用于评估该算法与外部评审员诊断之间的关系。
在381份评审中，外部评审小组将196份诊断为TIA或中风。该算法与TIA或中风诊断的符合率为80.1%，kappa为0.60。敏感性为87.8%，特异性为71.9%。
虽然统计符合率取决于样本选择方法，但该算法与外部专家小组的符合度较高，是一种用于事件检测的敏感工具。较低的特异性表明可能需要进行仔细的神经系统评估，以证实或反驳筛查算法所确定的事件。
