Treatment of Pulmonary Embolism With Rivaroxaban: Outcomes by Simplified Pulmonary Embolism Severity Index Score from a Post Hoc Analysis of the <scp>EINSTEIN PE</scp> Study
Bibliographic record
Abstract
OBJECTIVES: The objective was to assess adverse outcomes in relation to the simplified Pulmonary Embolism Severity Index (PESI) score in patients treated with rivaroxaban or standard therapy in the phase III EINSTEIN PE study and to evaluate the utility of the simplified PESI score to identify low-risk pulmonary embolism (PE) patients. METHODS: A post hoc analysis of EINSTEIN PE data was performed to assess the efficacy and safety of rivaroxaban in patients with a range of simplified PESI scores. Recurrent venous thromboembolism, fatal PE, all-cause mortality, and major bleeding were stratified by simplified PESI scores of 0, 1, or ≥2 and according to treatment period at 7, 14, 30, and 90 days and at the end of the full intended treatment period. RESULTS: Simplified PESI scores could be calculated in 4,831 of the 4,832 randomized patients; of those, 53.6, 36.7, and 9.7% had PESI scores of 0, 1, and ≥2, respectively. Among patients with simplified PESI scores of 0 or 1, fatal PE, all-cause mortality, and other adverse outcomes were uncommon within the first 7, 14, and 30 days. Patients with simplified PESI scores of ≥2 had more frequent adverse outcomes. Major bleeding was lower in the rivaroxaban group, particularly in those with simplified PESI scores of 1 or ≥2. CONCLUSIONS: The findings support using risk stratification with the simplified PESI score to identify low-risk patients with PE.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".