Literature DB >> 31042063

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

Eric A Kaiser1, Aleksandra Igdalova1, Geoffrey K Aguirre1, Brett Cucchiara1.   

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. Research study pre-registration: https://osf.io/sq9ef The following research study is a not a clinical trial.

Entities:  

Keywords:  Migraine; classification; headache; screening

Year:  2019        PMID: 31042063     DOI: 10.1177/0333102419847749

Source DB:  PubMed          Journal:  Cephalalgia        ISSN: 0333-1024            Impact factor:   6.292


  8 in total

1.  Selective amplification of ipRGC signals accounts for interictal photophobia in migraine.

Authors:  Harrison McAdams; Eric A Kaiser; Aleksandra Igdalova; Edda B Haggerty; Brett Cucchiara; David H Brainard; Geoffrey K Aguirre
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-06       Impact factor: 11.205

2.  Reflexive Eye Closure in Response to Cone and Melanopsin Stimulation: A Study of Implicit Measures of Light Sensitivity in Migraine.

Authors:  Eric A Kaiser; Harrison McAdams; Aleksandra Igdalova; Edda B Haggerty; Brett L Cucchiara; David H Brainard; Geoffrey K Aguirre
Journal:  Neurology       Date:  2021-09-07       Impact factor: 9.910

3.  A neural correlate of visual discomfort from flicker.

Authors:  Carlyn Patterson Gentile; Geoffrey Karl Aguirre
Journal:  J Vis       Date:  2020-07-01       Impact factor: 2.240

4.  Computerized migraine diagnostic tools: a systematic review.

Authors:  Yohannes W Woldeamanuel; Robert P Cowan
Journal:  Ther Adv Chronic Dis       Date:  2022-01-24       Impact factor: 5.091

5.  Development and validation of a web-based headache diagnosis questionnaire.

Authors:  Kyung Min Kim; A Ra Kim; Wonwoo Lee; Bo Hyun Jang; Kyoung Heo; Min Kyung Chu
Journal:  Sci Rep       Date:  2022-04-29       Impact factor: 4.996

6.  Epidemiology, work and economic impact of migraine in a large hospital cohort: time to raise awareness and promote sustainability.

Authors:  Edoardo Caronna; Victor José Gallardo; Alicia Alpuente; Marta Torres-Ferrus; Patricia Pozo-Rosich
Journal:  J Neurol       Date:  2021-07-20       Impact factor: 4.849

7.  Validation of an algorithm for automated classification of migraine and tension-type headache attacks in an electronic headache diary.

Authors:  Aaron Roesch; Markus A Dahlem; Lars Neeb; Tobias Kurth
Journal:  J Headache Pain       Date:  2020-06-12       Impact factor: 7.277

8.  Migraine aura, a predictor of near-death experiences in a crowdsourced study.

Authors:  Daniel Kondziella; Markus Harboe Olsen; Coline L Lemale; Jens P Dreier
Journal:  PeerJ       Date:  2019-12-04       Impact factor: 2.984

  8 in total

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