Comparison of Four Bleeding Risk Scores to Identify Rivaroxaban‐treated Patients With Venous Thromboembolism at Low Risk for Major Bleeding
Bibliographic record
Abstract
OBJECTIVES: Outpatient treatment of acute venous thromboembolism (VTE) requires the selection of patients with a low risk of bleeding during the first few weeks of anticoagulation. The accuracy of four systems, originally derived for predicting bleeding in VTE treated with vitamin K antagonists (VKAs), was assessed in VTE patients treated with rivaroxaban. METHODS: All patients treated with rivaroxaban in the multinational EINSTEIN deep vein thrombosis (DVT) and pulmonary embolism (PE) trials were included. Major bleeding was defined as ≥2 g/dL drop in hemoglobin or ≥2-unit blood transfusion, bleeding in critical area, or bleeding contributing to death. The authors examined the incidence of major bleeding in patients with low-risk assignment by the systems of Ruiz-Gimenez et al. (score = 0 to 1), Beyth et al. (score = 0), Kuijer et al. (score = 0), and Landefeld and Goldman. (score = 0). For clinical relevance, the definition of low risk for all scores except Kuijer includes all patients < 65 years with no prior bleeding history and no comorbid conditions (current cancer, renal insufficiency, diabetes mellitus, anemia, prior stroke, or myocardial infarction). RESULTS: A total of 4,130 patients (1,731 with DVT only, 2,399 with PE with or without DVT) were treated with rivaroxaban for a mean (±SD) duration of 207.6 (±95.9) days. Major bleeding occurred in 1.0% (40 of 4,130; 95% confidence interval [CI] = 0.7% to 1.3%) overall. Rates of major bleeding for low-risk patients during the entire treatment period were similar: Ruiz-Gimenez et al., 12 of 2,622 (0.5%; 95% CI = 0.2% to 0.8%); Beyth et al., nine of 2,249 (0.4%; 95% CI = 0.2% to 0.8%); Kuijer et al., four of 1,186 (0.3%; 95% CI = 0.1% to 0.9%); and Landefeld and Goldman, 11 of 2,407 (0.5%; 95% CI = 0.2% to 0.8%). At 30 days, major bleed rates for low-risk patients were as follows: Ruiz-Gimenez et al., five of 2,622 (0.2%; 95% CI = 0.1% to 0.4%); Beyth et al., five of 2,249 (0.2%; 95% CI = 0.1% to 0.5%); Kuijer et al., three of 1,186 (0.3%; 95% CI = 0.1% to 0.7%); and Landefeld and Goldman, seven of 2,407 (0.3%; 95% CI = 0.1% to 0.6%). No low-risk patient had a fatal bleed. CONCLUSIONS: Four scoring systems that use criteria obtained in routine clinical practice, derived to predict low bleeding risk with VKA treatment for VTE, identified patients with less than a 1% risk of major bleeding during full-course treatment with rivaroxaban.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".