Rationale and design of XAMOS: noninterventional study of rivaroxaban for prophylaxis of venous thromboembolism after major hip and knee surgery
Bibliographic record
Abstract
Venous thromboembolism is a frequent and potentially life-threatening complication of orthopedic surgery. Rivaroxaban is an oral direct factor Xa inhibitor, which was shown to be effective for the prevention of venous thromboembolism after elective hip and knee arthroplasty in the RECORD study program. Rivaroxaban has the potential to overcome the limitations of the current standards of care in the prevention of venous thromboembolism. XAMOS (Xarelto(®) in the prophylaxis of post-surgical venous thromboembolism after elective major orthopedic surgery of hip or knee) is an international, noninterventional, parallel-group study to gain insight into the safety (major bleeding, side effects) and effectiveness (prevention of symptomatic thromboembolic events) of rivaroxaban in daily clinical practice. XAMOS will follow 15,000 patients after major orthopedic surgery in approximately 200 centers worldwide, with about 7500 patients receiving rivaroxaban and about 7500 standard of care. XAMOS will supplement the clinical data obtained in the Phase III RECORD 1, 2, 3, and 4 trials in which rivaroxaban was shown to be superior for the primary efficacy endpoints, and with a safety profile similar to that of enoxaparin after hip or knee replacement surgery. XAMOS was started in 2009 and will complete recruitment and follow-up in 2011.
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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 | 0.056 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.025 | 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".