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Record W2916270006 · doi:10.31636/pmjua.v3i4.2

Modern approaches to diagnostics and treatment of migraine in children

2019· article· en· W2916270006 on OpenAlexaboutno aff
P V Kovalchuk, Oleksandr Katilov, S O Panenko

Bibliographic record

VenuePain medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMigraineMedicineIntensive care medicineIncidence (geometry)Medical diagnosisPediatricsPsychiatryPathology

Abstract

fetched live from OpenAlex

This article reviews modern approaches to diagnostics and treatment of a very common and simultaneously underestimated and often maltreated disorder in children. It is fallacious management of migraine masked behind the diagnoses such as autonomic vessel dysfunction and vascular headache here in Ukraine. This is a tremendous problem and it should be solved with appropriate information spread across the medical community.
 Up-to-date classification according to the International Headache Society, diagnostic criteria, differential diagnosis, investigation and treatment strategies are presented in the article. All supported data are com-pliant with guidelines of developed countries with evidence-based medicine (US, Canada, Great Britain, Japan, Australia, New Zealand) enhanced with new trials and approved methods. Migraine management is a rapidly evolving concept, where major changes were done during recent years (transcranial Deep Brain Stimulation, vagus stimulation, CGRP-receptor mono-clonal antibodies).
 Considering disorder incidence and its impact on life quality and the existence of options for alleviating symptoms, this information is important for physicians who work with children, especially for general practitioners, pediatrics, pediatric and adult neurologists.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.069
GPT teacher head0.271
Teacher spread0.201 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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