2023 ISTH update of the 2022 ISTH guidelines for antithrombotic treatment in COVID-19
Bibliographic record
Abstract
Based on emerging evidence from the COVID-19 pandemic, the International Society on Thrombosis and Haemostasis (ISTH) guidelines for antithrombotic treatment in COVID-19 were published in 2022. Since then, at least 16 new randomized controlled trials have contributed additional evidence, which necessitated a modification of most of the previous recommendations. We used again the American College of Cardiology Foundation/American Heart Association methodology for assessment of level of evidence (LOE) and class of recommendation (COR). Five recommendations had the LOE upgraded to A and 2 new recommendations on antithrombotic treatment for patients with COVID-19 were added. Furthermore, a section was added to answer questions about COVID-19 vaccination and vaccine-induced immune thrombotic thrombocytopenia (VITT), for which studies have provided some evidence. We only included recommendations with LOE A or B. Panelists agreed on 19 recommendations, 4 for nonhospitalized, 5 for noncritically ill hospitalized, 3 for critically ill hospitalized, and 2 for postdischarge patients, as well as 5 for vaccination and VITT. A strong recommendation (COR 1) was given for (a) use of prophylactic dose of low-molecular-weight heparin or unfractionated heparin in noncritically ill patients hospitalized for COVID-19, (b) for select patients in this group, use of therapeutic-dose low-molecular-weight heparin/unfractionated heparin in preference to prophylactic dose, and (c) for use of antiplatelet factor 4 enzyme immunoassays for diagnosing VITT. A strong recommendation was given against (COR 3) the addition of an antiplatelet agent in hospitalized, noncritically ill patients. These international guidelines provide recommendations for countries with diverse healthcare resources and COVID-19 vaccine availability.
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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 | 0.031 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.016 | 0.014 |
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".