Assessment of Days Alive Out of Hospital as a Possible End Point in Trials of Stroke Prevention for Atrial Fibrillation: A ROCKET AF Analysis
Bibliographic record
Abstract
Background Days alive out of hospital (DAOH) is an objective and patient‐centered net benefit end point. There are no assessments of DAOH in clinical trials of interventions for atrial fibrillation (AF), and it is not known whether this end point is of clinical utility in these populations. Methods and Results ROCKET AF (Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation) was an international double‐blind, double‐dummy randomized clinical trial that compared rivaroxaban with warfarin in patients with atrial fibrillation at increased risk for stroke. We assessed DAOH using investigator‐reported event data for up to 12 months after randomization in ROCKET AF. We assessed DAOH overall, by treatment group, and by subgroup, including age, sex, and comorbidities, using Poisson regression. The mean±SD number of days dead was 7.3±41.2, days hospitalized was 1.2±7.2, and mean DAOH was 350.7±56.2, with notable left skew. Patients with comorbidities had fewer DAOH overall. There were no differences in DAOH by treatment arm, with mean DAOH of 350.6±56.5 for those randomized to rivaroxaban and 350.7±55.8 for those randomized to warfarin ( P =0.86). A sensitivity analysis found no difference in DAOH not disabled with rivaroxaban versus warfarin (DAOH not disabled, 349.2±59.5 days and 349.1 days±59.3 days, respectively, P =0.88). Conclusions DAOH did not identify a treatment difference between patients randomized to rivaroxaban versus warfarin. This may be driven in part by the low overall event rates in atrial fibrillation anticoagulation trials, which leads to substantial left skew in measures of DAOH.
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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 | 0.100 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.026 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".