Endothelial nitric oxide synthase (−786T>C) polymorphism and migraine susceptibility
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to evaluate the correlation between endothelial nitric oxide synthase (eNOS) polymorphism (-786T>C) and migraine susceptibility in a meta-analysis. METHODS: A literature search was performed for case-control studies from inception to July 30, 2018 focusing on eNOS polymorphism (-786T>C) and risk of migraine. From 454 full-text articles, 6 were included in this study. Heterogeneity was assessed with the I index and quality assessment was performed using the Newcastle-Ottawa scale. RESULTS: CC genotype was not related to higher susceptibility of migraine compared with TT+ TC genotypes with significant difference (fixed effects model; OR = 1.27; 95% CI = 0.90-1.80; P = .17; I = 18%). However, subgroup analysis showed CC variant increase the risk for migraine compared with TT+ TC genotypes in Caucasian populations (fixed effects model; OR = 1.62; 95% CI = 1.03-2.56; P = .04; I = 18%), which could not be observed in non-Caucasian populations (fixed effects model; OR = 0.88; 95% CI = 0.51-1.53; P = .66; I = 0%). There was no significant difference for other genotypes and alleles between patients with migraine and healthy controls (all P > .05). CONCLUSION: This meta-analysis indicated that CC variant increases the risk for migraine compared with TT + TC genotypes in Caucasian populations.
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 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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".