New clinical practice guidelines for venous thromboembolism prevention: orthopedic surgery as a paradigm
Bibliographic record
Abstract
SUMMARY To produce up‐to‐date clinical practice guidelines on the prevention of venous thromboembolism (VTE) in orthopedic surgery. A Steering Committee defined the scope of the topic, the questions to be answered, and the assessment criteria. A multidisciplinary working group performed a critical appraisal of the literature. The resultant reports and guidelines were submitted for comment and completion of the AGREE questionnaire to peer reviewers, before producing definite guidelines. The report answers the following questions: (i) What is the VTE incidence according to clinical and/or paraclinical criteria in the absence of prophylaxis? (with stratification of VTE risk into low, moderate and high categories); (ii) What is the efficacy and safety of the prophylactic measures used? (iii) When should prophylaxis be introduced and how long should it last? (iv) Does ambulatory surgery affect efficacy and safety of prophylaxis? Apart from answering the above questions, the guidelines provide a summary table. This table stratifies types of surgery into the three risk categories, specifies the recommended prophylaxis for VTE (pharmacological and/or mechanical) and grades each recommendation. In addition, whenever appropriate, the recommended prophylaxis is adjusted to low‐ and high‐risk patients.
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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 | 0.035 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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".