Factor XIII Val34Leu Variant Is Protective against Venous Thromboembolism: A HuGE Review and Meta-Analysis
Bibliographic record
Abstract
It has been suggested that a G-to-T transition in exon 2 of the factor XIIIA gene resulting in a substitution of leucine for valine at amino acid 34 (FXIII Val34Leu) protects against venous thromboembolism (VTE). However, the evidence to date is insufficient to incorporate testing for the FXIII Val34Leu variant into clinical practice. To determine whether genotypes with the FXIII Val34Leu variant are protective against VTE, the authors performed a meta-analysis of 12 studies with genotyping for the FXIII Val34Leu variant (3,165 objectively diagnosed VTE cases and 4,909 controls). When a random-effects model was used, the combined odds ratios for VTE were 0.63 (95% confidence interval: 0.46, 0.86) for the homozygotes of the FXIII Val34Leu variant, 0.89 (95% confidence interval: 0.80, 0.99) for the heterozygotes, and 0.85 (95% confidence interval: 0.77, 0.95) for the homozygotes and heterozygotes combined. Potential sources of heterogeneity and potential bias were explored. The meta-analysis provided evidence that the FXIII Val34Leu variant has a small, but significant protective effect against VTE. Since VTE is a complex disorder, this information, along with results of ongoing studies to identify additional genetic factors underlying VTE, will be crucial in developing accurate risk profiles to identify individuals at higher risk of VTE.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.020 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".