Evidence map›Paper›PMID 35657603›Full record

Trial reportHeadache2022

Diagnostic accuracy of an artificial intelligence online engine in migraine: A multi-center study.

Robert P Cowan, Alan M Rapoport, Jim Blythe, John Rothrock, Kerry Knievel, Addie M Peretz, Elizabeth Ekpo, Bharati M Sanjanwala, Yohannes W Woldeamanuel

Open access · hybridAbstract readMulticenter StudyRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Headache, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
5.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Pooled it
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  13. Application of Artificial Intelligence in the Headache Field.Current pain and headache reports · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 1 country.

Robert P CowanDivision of Headache and Facial Pain, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.
Alan M RapoportNeurology, University of California, Los Angeles, California, USA.
Jim BlytheInformation Sciences Institute, University of Southern California, Los Angeles, California, USA.
John RothrockNeurology, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA.
Kerry KnievelNeurology, Barrow Neurological Institute, Phoenix, Arizona, USA.
Addie M PeretzDivision of Headache and Facial Pain, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.
Elizabeth EkpoNeurology, University of California Davis, Davis, California, USA.
Bharati M SanjanwalaDivision of Headache and Facial Pain, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.
Yohannes W WoldeamanuelDivision of Headache and Facial Pain, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.ORCID 0000-0003-4879-6098
Stanford Medicine · USBarrow Neurological Institute · USGeorge Washington University · USUniversity of California, Davis · USUniversity of California, Los Angeles · USUniversity of Southern California · US

Funding

Research in Anesthesia Training Program (ReAP)T32GM089626 · NIGMS · STANFORD UNIVERSITY · PI Vivianne L Tawfik · 2010 to 2026
$5.2M
Feasibility, Acceptability, and Pilot Testing of a Behavioral Intervention for Chronic MigraineK01NS124911 · NINDS · STANFORD UNIVERSITY · PI WOLDEAMANUEL, YOHANNES WOUBISHET · 2021 to 2025
$1.2M
NIGMS NIH HHS T32 GM089626NINDS NIH HHS K01 NS124911
6 · The paper itself

Abstract

objectiveThis study assesses the concordance in migraine diagnosis between an online, self-administered, Computer-based, Diagnostic Engine (CDE) and semi-structured interview (SSI) by a headache specialist, both using International Classification of Headache Disorders, 3rd edition (ICHD-3) criteria.

backgroundDelay in accurate diagnosis is a major barrier to headache care. Accurate computer-based algorithms may help reduce the need for SSI-based encounters to arrive at correct ICHD-3 diagnosis.

methodsBetween March 2018 and August 2019, adult participants were recruited from three academic headache centers and the community via advertising to our cross-sectional study. Participants completed two evaluations: phone interview conducted by headache specialists using the SSI and a web-based expert questionnaire and analytics, CDE. Participants were randomly assigned to either the SSI followed by the web-based questionnaire or the web-based questionnaire followed by the SSI. Participants completed protocols a few minutes apart. The concordance in migraine/probable migraine (M/PM) diagnosis between SSI and CDE was measured using Cohen's kappa statistics. The diagnostic accuracy of CDE was assessed using the SSI as reference standard.

resultsOf the 276 participants consented, 212 completed both SSI and CDE (study completion rate = 77%; median age = 32 years [interquartile range: 28-40], female:male ratio = 3:1). Concordance in M/PM diagnosis between SSI and CDE was: κ = 0.83 (95% confidence interval [CI]: 0.75-0.91). CDE diagnostic accuracy: sensitivity = 90.1% (118/131), 95% CI: 83.6%-94.6%; specificity = 95.8% (68/71), 95% CI: 88.1%-99.1%. Positive and negative predictive values = 97.0% (95% CI: 91.3%-99.0%) and 86.6% (95% CI: 79.3%-91.5%), respectively, using identified migraine prevalence of 60%. Assuming a general migraine population prevalence of 10%, positive and negative predictive values were 70.3% (95% CI: 43.9%-87.8%) and 98.9% (95% CI: 98.1%-99.3%), respectively.

conclusionThe SSI and CDE have excellent concordance in diagnosing M/PM. Positive CDE helps rule in M/PM, through high specificity and positive likelihood ratio. A negative CDE helps rule out M/PM through high sensitivity and low negative likelihood ratio. CDE that mimics SSI logic is a valid tool for migraine diagnosis.

Indexed as

Headache DisordersMigraine DisordersAdultArtificial IntelligenceCross-Sectional StudiesFemaleHeadacheHumansMaleSensitivity and SpecificitySurveys and Questionnairesartificial intelligencediagnosisdiagnostic accuracy studymigraineonline enginesemi-structured interview

Identifiers

PMID35657603
PMCPMC9378575
OpenAlexW4281738498

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.