Anticoagulant treatment for venous thromboembolism: A pooled analysis and additional results of the XALIA and XALIA‐LEA noninterventional studies
Bibliographic record
Abstract
BACKGROUND: The XALIA and XALIA-LEA prospective, noninterventional studies investigated the safety and effectiveness of rivaroxaban versus standard anticoagulation for venous thromboembolism (VTE) treatment in routine clinical practice across global regions. OBJECTIVES: This pooled analysis combined their data to determine the incidence of thromboembolic and bleeding events in both treatment groups and addressed specific bleeding patterns in a broad range of patients. METHODS: Patients with objectively confirmed VTE and an indication for ≥3 months' anticoagulation treatment received rivaroxaban or standard anticoagulation (eg, initial treatment with heparin/fondaparinux, followed by a vitamin K antagonist [VKA]). Treatment choice, dose, management, and duration were at the physician's discretion. Primary outcomes (major bleeding, recurrent VTE, and all-cause mortality) were compared between the two treatment groups. Propensity score stratification, and matching were used to reduce bias due to confounding variables. RESULTS: Overall, 7129 patients were enrolled from 36 countries; 6445 and 2714 patients were included in the propensity score-stratified and -matched analyses, respectively. Major bleeding and incidences of recurrent VTE were similar between treatment groups; all-cause mortality was lower with rivaroxaban than with standard anticoagulation. The incidences of genitourinary bleeding were higher with rivaroxaban than with standard anticoagulation therapy (46 and 23 events in the matched analysis, respectively). VKA management in real-world practice was suboptimal. CONCLUSION: XALIA and XALIA-LEA show similar safety and effectiveness profiles of rivaroxaban and standard anticoagulation for VTE treatment in routine practice in many parts of the world. The observations are consistent with results from the phase III EINSTEIN randomized controlled trials.
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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 | 0.031 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.044 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".