P3581Real-world effectiveness of stroke prevention in patients with non-valvular atrial fibrillation treated with rivaroxaban vs. phenprocoumon in Germany - insights from the reload study
Bibliographic record
Abstract
Background: Only limited evidence exists regarding the effectiveness and safety of rivaroxaban versus phenprocoumon in non-valvular atrial fibrillation (NVAF) patients treated in a real world setting in Germany where phenprocoumon represents the predominantly prescribed VKA. Purpose: The RELOAD study is a retrospective study, using a new user approach based on a representative sample of a German insurance claims database to assess the real world comparative effectiveness and safety of rivaroxaban vs. VKA prescribed in non-valvular atrial fibrillation (NVAF) routine care patients in Germany. This abstract analyses baseline characteristics of the two cohorts. Methods: The study analyses NVAF-patients with an initial prescription of rivaroxaban or VKA between January 2012 and December 2015. Primary endpoints of this study will be the comparative risk of ischemic stroke (effectiveness) and intracranial haemorrhage (ICH, safety). Incidence rates and time-to-event analyses using adjusted multivariate Cox proportional hazard models and a 1:1 propensity score matching will be conducted to estimate hazard ratios and corresponding 95% confidence intervals.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".