Endothelial function in migraine: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Migraine has been associated with cardiovascular disorders. Endothelial dysfunction may be a mechanism underlying this association. The present study tested the hypothesis that endothelium-dependent vasodilation, basal endothelial nitric oxide release and endothelial fibrinolytic capacity are impaired in migraine patients. METHODS: Graded doses of sodium nitroprusside (SNP, 0.2 to 0.8 μg x min(-1) x dL(-1) forearm), substance P (0.2 to 0.8 pmol x min(-1) x dL(-1) forearm) and N(G)-monomethyl-L-arginine (L-NMMA, 0.1 to 0.4 μmol x min(-1) x dL(-1) forearm) were infused into the brachial artery of 16 migraine patients with or without aura during a headache-free interval and 16 age- and sex-matched subjects without a history of migraine. Forearm blood flow (FBF) was measured by strain-gauge venous occlusion plethysmography. Local forearm release of tissue plasminogen activator (t-PA) in response to substance P infusion was assessed using the arteriovenous plasma concentration gradient. Responses to infused drugs were compared between patients and matched controls by analysis of variance. RESULTS: In both migraine patients and control subjects, SNP and substance P caused a dose-dependent increase, and L-NMMA a dose-dependent decrease in FBF (P < 0.001 for all responses). In both groups, substance P caused an increase in t-PA release (P < 0.001). FBF responses and t-PA release were comparable between migraine patients and control subjects. CONCLUSIONS: The absence of differences in endothelium-dependent vasodilation, basal endothelial nitric oxide production and stimulated t-PA release between migraine patients and healthy control subjects argues against the presence of endothelial dysfunction in forearm resistance vessels of migraine patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".