Prevention of perioperative venous thromboembolism: 2024 guidelines from the French Working Group on Perioperative Haemostasis (GIHP) developed in collaboration with the French Society of Anaesthesia and Intensive Care Medicine (SFAR), the French Society of Thrombosis and Haemostasis (SFTH) and the French Society of Vascular Medicine (SFMV) and endorsed by the French Society of Digestive Surgery (SFCD), the French Society of Pharmacology and Therapeutics (SFPT) and INNOVTE (Investigation Network On Venous ThromboEmbolism) network
Bibliographic record
Abstract
BACKGROUND: Any surgical procedure carries a risk for venous thromboembolism (VTE), albeit variable. Improvements in medical and surgical practices and the shortening of care pathways due to the development of day surgery and enhanced recovery after surgery, have reduced the perioperative risk for VTE. OBJECTIVE: A collaborative working group of experts in perioperative haemostasis updated in 2024 the recommendations for the Prevention of perioperative venous thromboembolism published in 2011. METHODS: The addressed questions were defined by 40 experts (GIHP, SFAR, SFTH and SFMV) and formulated in a PICO format. They performed the literature review and formulated recommendations according to the Grading of GRADE system. Recommendations were then validated by a vote determining the strength of each recommendation. Of note, these recommendations do not cover all surgical specialties. Especially, thromboprophylaxis in cardiac surgery, neurosurgery and obstetrics is not addressed. RESULTS: 78 recommendations were formalized into 17 sections, including patient-related VTE risk factors, types of surgery, extreme body weight, renal impairment, mechanical prophylaxis, distal deep vein thrombosis; 27 were found to have a high level of evidence (GRADE 1) and 41 a low level of evidence (GRADE 2) and 10 were expert opinion. All had strong agreement among the experts. CONCLUSIONS: These guidelines help to weigh the perioperative risk for VTE (which includes the risk associated to surgery and the patient-related risk) against the adverse effects of thromboprophylaxis, either pharmacological or mechanical. This includes particularly the bleeding risk induced by antithrombotic drugs as well as costs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".