Non-OO blood type influences the risk of recurrent venous thromboembolism
Bibliographic record
Abstract
The role of ABO blood type as a risk factor for recurrent venous thromboembolism (VTE) in patients with a first unprovoked VTE who complete oral anticoagulation therapy is unknown. The aim of this study was to determine if non-OO blood type is a risk factor for recurrent VTE in patients with a first unprovoked VTE who completed 5-7 months of anticoagulant therapy. In an ongoing cohort study of patients with unprovoked VTE who discontinued oral anticoagulation after 5-7 months of therapy, six single nucleotide polymorphisms sites were tested to determine ABO blood type using banked DNA. The main outcome was objectively proven recurrent VTE. Mean follow-up for the cohort was 4.19 years (SD 2.16). During 1,553 patient-years of follow-up, 101 events occurred in 380 non-OO patients (6.5 events per 100 patient years; 95% CI 5.3-7.7) compared to 14 events during 560 patient years of follow-up in 129 OO patients (2.5 per 100 patient years; 95% CI 1.2-3.7), the adjusted hazard ratio was 1.98 (1.2-3.8). In conclusion, non-OO blood type is associated with a statistically significant and clinically relevant increased risk of recurrent VTE following discontinuation of anticoagulant therapy for a first episode of unprovoked 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 | 0.000 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".