Management of bleeding and invasive procedures in patients treated with anti–factor XI(a) anticoagulants: proposals from the French Working Group on Perioperative Haemostasis and French Society of Thrombosis and Haemostasis
Bibliographic record
Abstract
Background: Several anti-FXI(a) agents with distinct mechanisms of action and pharmacological properties are currently under clinical development. While these anticoagulants are not yet available, there is a need to address bleeding risk management for patients already enrolled in phase III trials. These patients may face elective or unplanned invasive procedures and bleeding events in anticipation of marketing authorization.Experience from managing patients with inherited FXI deficiency, along with data from early clinical trials, suggests that the bleeding risk associated with anti-FXI(a) is likely to be low but can vary depending on the clinical situation. Anti-FXI(a) reversal options include tranexamic acid, FXI concentrates, and recombinant activated factor VII. However, these options may not always be suitable, can be expensive, and may carry a thrombotic risk. Objectives: The French Working Group on Perioperative Haemostasis (Groupe d'Intérêt en Hémostase Péri-opératoire (GIHP)) and the French Society of Thrombosis and Haemostasis (SFTH) aimed to develop proposals to manage bleeding and invasive procedures in patients treated with anticoagulants targeting Factor XI or XIa (anti-FXI(a)). Methods: Literature review and development of practical guidelines by an expert panel. Results: We propose pragmatic recommendations for optimizing safety in patients treated with anti-FXI(a), considering bleeding and thrombosis risks, the drug's mechanism of action, and available reversal options. Conclusion: These proposals will be re-evaluated as more data becomes available. The implementation of a registry for managing anti-FXI(a) anticoagulants in patients undergoing invasive procedures or experiencing bleeding complications is needed.
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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 | 0.022 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| 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".