Management of antiplatelet therapy in patients undergoing elective invasive procedures. Proposals from the French Working Group on perioperative haemostasis (GIHP) and the French Study Group on thrombosis and haemostasis (GFHT). In collaboration with the French Society for Anaesthesia and Intensive Care Medicine (SFAR)
Bibliographic record
Abstract
The French Working Group on Perioperative Haemostasis (GIHP) and the French Study Group on Haemostasis and Thrombosis (GFHT) in collaboration with the French Society for Anaesthesia and Intensive Care Medicine (SFAR) drafted up-to-date proposals for the management of antiplatelet therapy in patients undergoing elective invasive procedures. The proposals were discussed and validated by a vote; all proposals but one could be assigned with a high strength. The management of antiplatelet therapy is based on their indication and the procedure. The risk of bleeding related to the procedure can be divided into high, moderate and low categories depending on the possibility of performing the procedure in patients receiving antiplatelet agents (none, monotherapy and dual antiplatelet therapy respectively). If discontinuation of antiplatelet therapy is indicated before the procedure, a last intake of aspirin, clopidogrel, ticagrelor and prasugrel 3, 5, 5 and 7 days before surgery respectively is proposed. The thrombotic risk associated with discontinuation should be assessed according to each specific indication of antiplatelet therapy and is higher for patients receiving dual therapy for coronary artery disease (with further refinements based on a few well-accepted items) than for those receiving monotherapy for cardiovascular prevention, for secondary stroke prevention or for lower extremity arterial disease. These proposals also address the issue of the potential role of platelet functional tests and consider management of antiplatelet therapy for regional anaesthesia, including central neuraxial anaesthesia and peripheral nerve blocks, and for coronary artery surgery.
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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 | 0.086 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.017 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".