Antithrombotic Treatment in Patients With Hemophilia: an EHA-ISTH-EAHAD-ESO Clinical Practice Guidance
Bibliographic record
Abstract
Cardiovascular disease is an emerging medical issue in patients with hemophilia (PWH) and its prevalence is increasing up to 15% in PWH in the United States. Atrial fibrillation, acute and chronic coronary syndromes, venous thromboembolism, and cerebral thrombosis are frequent thrombotic or prothrombotic situations, which require a careful approach to fine-tune the delicate balance between thrombosis and hemostasis in PWH when using both procoagulant and anticoagulant treatments. Generally, PWH could be considered as being naturally anticoagulated when clotting factors are <20 IU/dL, but specific recommendations in patients with very low levels according to the different clinical situations are lacking and mainly based on the anecdotal series. For PWH with baseline clotting factor levels >20 IU/dL in need for any form of antithrombotic therapy, usually treatment without additional clotting factor prophylaxis could be used, but careful monitoring for bleeding is recommended. For antiplatelet treatment, this threshold could be lower with single-antiplatelet agent, but again factor level should be at least 20 IU/dL for dual antiplatelet treatment. In this complex growing scenario, the European Hematology Association in collaboration with the International Society on Thrombosis and Haemostasis, the European Association for Hemophilia and Allied Disorders, the European Stroke Organization, and a representative of the European Society of Cardiology Working Group on Thrombosis has produced this current guidance document to provide clinical practice recommendations for health care providers who care for PWH.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.010 |
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".