American Society of Hematology living guidelines on use of anticoagulation for thromboprophylaxis for patients with COVID-19: executive summary
Bibliographic record
Abstract
BACKGROUND: COVID-19-related critical and acute illness is associated with an increased risk of venous thromboembolism (VTE). These evidence-based recommendations of the American Society of Hematology (ASH) are intended to support patients, clinicians, and other health care professionals in decisions about using anticoagulation for thromboprophylaxis for patients with COVID-19-related critical illness; patients with COVID-19-related acute illness; and those being discharged from the hospital, who do not have suspected or confirmed VTE. METHODS: ASH formed a multidisciplinary panel, including patient representatives. The Michael G. DeGroote Cochrane Canada and MacGRADE Centres at McMaster University supported guideline development, including performing systematic reviews (up to June 2023). The panel prioritized clinical questions and outcomes according to their importance for clinicians and patients. The panel used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess certainty in the evidence and make recommendations. RESULTS: This is an executive summary of 3 updated recommendations that have been published, which concludes the living phase of the guidelines. For patients with COVID-19-related critical illness, the panel issued conditional recommendations suggesting (a) prophylactic-intensity over therapeutic-intensity anticoagulation and (b) prophylactic-intensity over intermediate-intensity anticoagulation. For patients with COVID-19-related acute illness, conditional recommendations were suggested (a) prophylactic-intensity over intermediate-intensity anticoagulation, and (b) therapeutic-intensity over prophylactic-intensity anticoagulation. The panel issued a conditional recommendation suggesting against the use of postdischarge anticoagulant thromboprophylaxis. CONCLUSIONS: These conditional recommendations were made based on low or very low certainty in the evidence, underscoring the need for additional, high-quality, randomized controlled trials for patients with COVID-19.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".