PT  - JOURNAL ARTICLE
AU  - Eric A. Kaiser
AU  - Aleksandra Igdalova
AU  - Geoffrey K. Aguirre
AU  - Brett Cucchiara
TI  - A web-based, branching logic questionnaire for the automated classification of migraine
AID  - 10.1101/369827
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 369827
4099  - http://biorxiv.org/content/early/2018/07/18/369827.short
4100  - http://biorxiv.org/content/early/2018/07/18/369827.full
AB  - 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 (POEM)—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, this result was compared to prior diagnostic classification by a neurologist following a direct interview.Results Of 118 subjects contacted, 90 (76%) completed the questionnaire; of these 31 were headache-free, 29 migraine without aura (MwoA), and 30 migraine with aura (MwA). 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. Sensitivity of the POEM tool was 42%, 59%, and 70%, and specificity was 100%, 84%, and 94% for headache-free, MwoA, and MwA, respectively. Sensitivity and specificity of the POEM tool for migraine overall (with or without aura), was 83% and 90%, respectively.Conclusions The POEM web-based questionnaire, and associated analysis routines, identifies headache-free and migraine subjects with good specificity. It may be useful for classifying subjects for large-scale research studies.Trial Registration: https://osf.io/sq9ef