Polymorphisms in the protein C gene as risk factor for venous thrombosis
Bibliographic record
Abstract
Protein C is an important inhibitor of blood coagulation. We investigated the effect of two polymorphisms within the promoter region of the protein C gene (C/T at position 2405 and A/G at position 2418) on risk of venous thrombosis and on plasma protein C levels. In addition the combined effect of the two polymorphisms with factor V Leiden and oral contraceptive use was investigated. Previous studies on these polymorphisms were small and were not able to investigate synergistic effects. In the Multiple Environmental and Genetic Assessment of risk factors for venous thrombosis (MEGA study), protein C levels were determined in 2,043 patients with venous thrombosis and 2,857 control subjects, and the two polymorphisms in 4,285 patients and 4,863 control subjects. The CC/GG genotype was associated with the lowest protein C levels. Compared to carriers of the TT/AA genotype - a genotype associated with higher protein C levels - the risk of venous thrombosis in CC/GG carriers was 1.3-fold increased (95% confidence interval 1.09-1.48). The combination of factor V Leiden with the CC/GG genotype led to a 4.7-fold increased risk, compared to non-carriers with the TT/AA genotype. Oral contraceptive use together with the CC/GG genotype resulted in a 5.2-fold increased risk. In conclusion, the CC/GG genotype is associated with lower levels of protein C and an elevated risk of venous thrombosis compared to the TT/AA genotype. There is no clear synergistic effect of the CC/GG genotype with factor V Leiden or oral contraceptive use on thrombotic risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".