Management of COVID‐19‐associated coagulopathy in persons with haemophilia
Bibliographic record
Abstract
INTRODUCTION: The SARS-CoV-2 coronavirus-induced infection (COVID-19) can be associated with a coagulopathy mainly responsible for pulmonary microvasculature thrombosis and systemic thromboembolic manifestations. The pathophysiology and management of the COVID-19 coagulopathy are likely more complex in patients with inherited bleeding diseases such as haemophilia. These individuals might indeed present with both bleeding and thrombotic complications and require simultaneous antithrombotic and haemostatic treatments. OBJECTIVE: We propose practical guidance for the diagnosis and management of COVID-19 coagulopathy in persons with haemophilia. RESULTS: Continuation of regular haemostatic treatment is recommended for ambulatory patients. For patients requiring hospital admission and on replacement therapy with factors VIII or IX concentrates, prophylaxis with concentrates should be intensified according to the risk of bleeding complications and associated with prophylactic doses of LMWH. For patients on nonreplacement therapy, emicizumab should be continued and possibly combined with factor VIII and prophylactic doses of LMWH depending on the risk of bleeding and thrombosis. Dose escalation of LMWH tailored to the risk of thrombosis can be employed but not supported by evidence. CONCLUSIONS: These practical recommendations are based on the current literature on COVID-19 with its impact on haemostasis, indications and modalities for thromboprophylaxis mainly in nonhaemophilic patients and how that is likely to affect persons with haemophilia in different circumstances. They will need to be tailored to each patient's clinical status and validated in future studies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".