Causes of death in patients with atrial fibrillation anticoagulated with rivaroxaban: a pooled analysis of XANTUS
Bibliographic record
Abstract
AIMS: Anticoagulation can prevent stroke and prolong lives in patients with atrial fibrillation (AF). However, anticoagulated patients with AF remain at risk of death. The aim of this study was to investigate the causes of death and factors associated with all-cause and cardiovascular death in the XANTUS population. METHODS AND RESULTS: Causes of death occurring within a year after rivaroxaban initiation in patients in the XANTUS programme studies were adjudicated by a central adjudication committee and classified following international guidance. Baseline characteristics associated with all-cause or cardiovascular death were identified. Of 11 040 patients, 187 (1.7%) died. Almost half of these deaths were due to cardiovascular causes other than bleeding (n = 82, 43.9%), particularly heart failure (n = 38, 20.3%) and sudden or unwitnessed death (n = 24, 12.8%). Fatal stroke (n = 8, 4.3%), which was classified as a type of cardiovascular death, and fatal bleeding (n = 17, 9.1%) were less common causes of death. Independent factors associated with all-cause or cardiovascular death included age, AF type, body mass index, left ventricular ejection fraction, hospitalization at baseline, rivaroxaban dose, and anaemia. CONCLUSION: The overall risk of death due to stroke or bleeding was low in XANTUS. Anticoagulated patients with AF remain at risk of death due to heart failure and sudden death. Potential interventions to reduce cardiovascular deaths in anticoagulated patients with AF require further investigation, e.g. early rhythm control therapy and AF ablation. TRIAL REGISTRATION NUMBERS: NCT01606995, NCT01750788, NCT01800006.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.013 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".