Thromboembolism in Heart Transplantation: Role of Prothrombin G20210A and Factor V Leiden
Bibliographic record
Abstract
BACKGROUND: Thromboembolism has been reported as a frequent complication after cardiac transplantation. Many risk factors for thrombosis may explain this, such as metabolic alterations and the use of cyclosporine. In the general population, two single nucleotide polymorphisms (SNPs), factor V Leiden and prothrombin G20210A (PT G20210A), have been associated with a significant increase in the risk of thrombosis. However, these mutations have not been analyzed in cardiac transplant patients. We describe the protracted history of recurrent thromboembolism in a rare case of homozygosity for the PT G20210A variant. This prompted us to analyze the entire cardiac transplant cohort for the incidence of thromboembolic events and their association with these genetic polymorphisms. METHODS: We report the study of 84 cardiac transplant recipients. We retrospectively analyzed the frequency of thromboembolic episodes. The genotypes for FVL and PT G20210A were determined and correlated with those episodes. RESULTS: Our results confirm a very high incidence of thromboembolism in this population. We also found a significant increase in the likelihood of thromboembolism in subjects with the PTB G20210A variant (odds ratio 3.08; 95% confidence interval: 1.7-5.5). CONCLUSIONS: The incidence of thromboembolic complications after heart transplantation is increased and may be related in part to genetic predisposition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".