P1617Clinical and economic outcomes in low-risk pulmonary embolism patients treated with rivaroxaban vs standard of care
Bibliographic record
Abstract
Introduction: Low-risk pulmonary embolism (LRPE) patients may qualify for immediate or early discharge. Rivaroxaban – a rapid acting fixed-dose oral anticoagulant – facilitates earlier hospital discharge, potentially reducing costs and patient exposure to hospital-acquired complications. The US Veterans Health Administration (VHA) represents a very large, well described, highly validated, and controlled health system cohort to evaluate real world outcomes. Purpose: To compare the effectiveness of rivaroxaban versus the standard of care (SOC) among LRPE VHA patients. Methods: Adult patients with continuous enrolment for ≥12 months before and 3 months after an inpatient diagnosis of PE (index date: discharge date) between 01JAN2011–30JUN2015 and a prescription claim for an anticoagulant during the index hospitalization were included. Patients scoring 0 points on the simplified Pulmonary Embolism Stratification Index (sPESI) were considered at low risk; others were considered at high risk. LRPE patients were further stratified into SOC and rivaroxaban cohorts. The SOC drugs used were low molecular weight heparin, unfractionated heparin, and warfarin. Propensity score matching (PSM) was used to compare PE-related outcomes (recurrent venous thromboembolism [VTE], major bleeding, and death), hospital-acquired conditions, healthcare utilization, and costs among patients receiving SOC and rivaroxaban. Costs were compared with a generalized linear model with a gamma distribution and log link to account for the expected non-normality of cost data.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".