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Record W2769086374 · doi:10.1186/s10194-017-0819-x

Experts’ opinion about the pediatric secondary headaches diagnostic criteria of the ICHD-3 beta

2017· article· en· W2769086374 on OpenAlexaff
Aynur Özge, Ishaq Abu‐Arafeh, Amy A. Gelfand, Peter J. Goadsby, Jean Christophe Cuvellier, Massimiliano Valeriani, А. В. Сергеев, Karen Barlow, Derya Uludüz, Osman Özgür Yalın, Noemi Faedda, Richard B. Lipton, Alan M. Rapoport, Vincenzo Guidetti

Bibliographic record

VenueThe Journal of Headache and Pain · 2017
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsUniversity of CalgaryAlberta Children's Hospital
Fundersnot available
KeywordsHeadachesInternational Classification of Headache DisordersMedicineFamily medicinePsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The 2013 International Classification of Headache Disorders-3 was published in a beta version to allow clinicians to confirm the validity of the criteria or suggest improvements based on field studies. The aim of this work was to review the Secondary Headache Disorders and Cranial Neuralgias and Other Headache Disorders sections of ICHD-3 beta data on children and adolescents (age 0-18 years) and to suggest changes, additions, and amendments. METHODS: Several experts in childhood headache across the world applied different aspects of ICHD-3 beta in their normal clinical practice. Based on their personal experience and the available literature on pediatric headache, they made observations and proposed suggestions for the mentioned headache disorders on children and adolescents. RESULTS: Some headache disorders in children have specific features, which are different from adults that should be acknowledged and considered. Some features in children were found to be age-dependent: clinical characteristics, risks factors and etiologies have a strong bio psychosocial basis in children and adolescents making primary headache disorders in children distinct from those in adults. CONCLUSIONS: Several recommendations are presented in order to make ICHD-3 more appropriate for use in children.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.330
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations36
Published2017
Admission routes1
Has abstractyes

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