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一个基于网络的、分支逻辑的问卷,用于自动分类偏头痛。

A web-based, branching logic questionnaire for the automated classification of migraine.

机构信息

Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

Cephalalgia. 2019 Sep;39(10):1257-1266. doi: 10.1177/0333102419847749. Epub 2019 May 1.

Abstract

OBJECTIVE

To identify migraineurs and headache-free individuals with an online questionnaire and automated analysis algorithm.

METHODS

We created a branching-logic, web-based questionnaire - the Penn Online Evaluation of Migraine - to obtain standardized headache history from a previously studied cohort. Responses were analyzed with an automated algorithm to assign subjects to one of several categories based on ICHD-3 (beta) criteria. Following a pre-registered protocol, the primary outcome was sensitivity and specificity for assignment of headache-free, migraine without aura, and migraine with aura labels, as compared to a prior classification by neurologist interview.

RESULTS

Of 118 subjects contacted, 90 (76%) completed the questionnaire; of these 31 were headache-free controls, 29 migraine without aura, and 30 migraine with aura. Mean age was 41 ± 6 years and 76% were female. There were no significant demographic differences between groups. The median time to complete the questionnaire was 2.5 minutes (IQR: 1.5-3.4 minutes). Sensitivity of the Penn Online Evaluation of Migraine tool was 42%, 59%, 70%, and 83%, and specificity was 100%, 84%, 93%, and 90% for headache-free controls, migraine without aura, migraine with aura, and migraine overall, respectively.

CONCLUSIONS

The Penn Online Evaluation of Migraine web-based questionnaire, and associated analysis routine, identifies headache-free and migraine subjects with good specificity. It may be useful for classifying subjects for large-scale research studies. https://osf.io/sq9ef The following research study is a not a clinical trial.

摘要

目的

通过在线问卷和自动化分析算法来识别偏头痛患者和无头痛者。

方法

我们创建了一个分支逻辑的网络问卷 - 宾夕法尼亚在线偏头痛评估问卷,以从先前研究的队列中获得标准化的头痛史。使用自动化算法分析回答,根据 ICHD-3(β)标准将受试者分配到几个类别之一。根据预先注册的方案,主要结果是将无头痛、无先兆偏头痛和有先兆偏头痛标签分配给头痛患者的敏感性和特异性,与神经病学家访谈的先前分类相比。

结果

联系了 118 名受试者,其中 90 名(76%)完成了问卷;其中 31 名是无头痛对照者,29 名是无先兆偏头痛患者,30 名是有先兆偏头痛患者。平均年龄为 41±6 岁,76%为女性。组间无显著的人口统计学差异。完成问卷的中位数时间为 2.5 分钟(IQR:1.5-3.4 分钟)。宾夕法尼亚在线偏头痛评估问卷工具的敏感性分别为 42%、59%、70%和 83%,特异性分别为 100%、84%、93%和 90%,用于无头痛对照者、无先兆偏头痛、有先兆偏头痛和偏头痛总体。

结论

宾夕法尼亚在线偏头痛问卷以及相关的分析程序,具有良好的特异性,可以识别无头痛和偏头痛患者。它可能对大规模研究研究中分类受试者有用。 https://osf.io/sq9ef 本研究不是临床试验。

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