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Record W2155916559 · doi:10.1136/bmj.38302.504063.8f

Risk of ischaemic stroke in people with migraine: systematic review and meta-analysis of observational studies

2004· review· en· W2155916559 on OpenAlexaff
Mahyar Etminan, Bahi Takkouche, Francisco Caamaño‐Isorna, Ali Samii

Bibliographic record

VenueBMJ · 2004
Typereview
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsObservational studyMeta-analysisIschaemic strokeMigraineStroke (engine)MedicineInternal medicineIschemiaEngineering

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the association between migraine and risk of ischaemic stroke. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Observational studies published between 1966 and June 2004 (identified through Medline and Embase) that examined the association between migraine and risk of ischaemic stroke. RESULTS: 14 studies (11 case-control studies and 3 cohort studies) were identified. These studies suggest that the risk of stroke is increased in people with migraine (relative risk 2.16, 95% confidence interval 1.89 to 2.48). This increase in risk was consistent in people who had migraine with aura (relative risk 2.27, 1.61 to 3.19) and migraine without aura (relative risk 1.83, 1.06 to 3.15), as well as in those taking oral contraceptives (relative risk 8.72, 5.05 to 15.05). CONCLUSIONS: Data from observational studies suggest that migraine may be a risk factor in developing stroke. More studies are needed to explore the mechanism of this potential association. In addition, the risk of migraine among users of oral contraceptives must be further investigated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.054
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0160.021
Bibliometrics0.0060.007
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.235
GPT teacher head0.441
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations660
Published2004
Admission routes1
Has abstractyes

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