Reasons for hospitalization and risk of mortality in patients with atrial fibrillation treated with dabigatran or warfarin in the Randomized Evaluation of Long-term Anticoagulation Therapy (RE-LY) trial
Bibliographic record
Abstract
AIMS: Hospitalizations are common among patients with atrial fibrillation. This article aimed to analyse the causes and consequences of hospitalizations occurring during the Randomized Evaluation of Long-term Anticoagulation Therapy (RE-LY) trial. METHODS AND RESULTS: The RE-LY database was used to evaluate predictors of hospitalization using multivariate regression modelling. The relationship between hospitalization and subsequent major adverse cardiac events was evaluated in a time dependent Cox proportional-hazard modelling. Of the 18 113 patients in RE-LY, 7200 (39.8%) were hospitalized at least once during a mean follow-up of 2 years. First hospitalization rates were 2312 (39.5%) for dabigatran etexilate (DE) 110, 2430 (41.6%) for DE 150, and 42.6% (N = 2458) for warfarin. Hospitalization was associated with post-discharge death [absolute event rate 9.1% vs. 2.2%; adjusted hazard ratio (HR) 3.6, 95% confidence interval (CI) 3.2-4.0, P < 0.0001], vascular death (adjusted HR 2.9, 95% CI 2.5-3.3, P < 0.0001), and sudden cardiac death (adjusted HR 2.3; 95% CI 1.8-2.9, P < 0.0001). Cardiovascular hospitalization was also associated with an increased risk of post-discharge death (adjusted HR 2.8, 95% CI 2.5-3.2, P < 0.0001), vascular death (adjusted HR 2.8, 95% CI 2.4-3.2, P < 0.0001), and sudden cardiac death (adjusted HR 2.1, 95% CI 1.6-2.7, P < 0.0001) compared with patients not hospitalized for any cardiovascular reason. CONCLUSION: Hospitalizations are associated an increased risk of with death and cardiovascular death in patients with atrial fibrillation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".