Abstract 15386: Hospitalizations and Other Healthcare Resource Utilization Among Patients With Deep Vein Thrombosis Treated With Rivaroxaban versus Low-Molecular-Weight Heparin and Warfarin in the Outpatient Setting
Bibliographic record
Abstract
Introduction: Compared with low-molecular-weight heparin (LMWH) and warfarin, the oral anticoagulant rivaroxaban has advantages such as simplified care that may lead to less healthcare resource utilization (HRU). Objective: To compare HRU (hospitalization, emergency room [ER], and outpatient [OP] visit) among deep vein thrombosis (DVT) patients who received rivaroxaban or LMWH/warfarin in the outpatient setting. Methods: A retrospective matched-cohort analysis was conducted using the Truven Health Analytic MarketScan Claims database from 1/2011-12/2013. Adult patients with a primary diagnosis of DVT during an OP/ER visit after November 02, 2012, and who initiated treatment on the same day with rivaroxaban or LMWH/warfarin were identified. Patients were observed within 1, 2, 3, and 4 weeks after their DVT diagnosis. Mean number of all-cause and VTE (DVT or PE)-related hospitalizations and other HRU were evaluated using Lin’s method. Results: All of the 512 rivaroxaban patients were well-matched with LMWH/warfarin patients. Mean all-cause number of hospitalizations was significantly lower for rivaroxaban compared to LMWH/warfarin users within 1 week (0.012 vs 0.032; P=0.044) and 2 weeks (0.022 vs 0.048; P=0.040), and numerically lower within 3 weeks (0.038 vs 0.061; P=0.112) and 4 weeks (0.045 vs 0.078; P=0.058). Corresponding mean number of VTE-related hospitalizations was significantly lower for rivaroxaban within 1 week (0.008 vs 0.028; P=0.020) and 2 weeks (0.016 vs 0.042; P=0.020), numerically lower within 3 weeks (0.030 vs 0.052; P=0.074), and significantly lower within 4 weeks (0.034 vs 0.068; P=0.036). Corresponding all-cause OP visits were significantly lower for rivaroxaban users, while ER visits were similar between cohorts (Table 1). Conclusion: DVT patients treated with rivaroxaban following an OP/ER visits had significantly fewer hospitalizations and outpatient visits during the first weeks compared to matched LMWH/warfarin users.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".