Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia and its prevalence increases with advancing age. 1,2Dr Wilson and coworkers from Ireland have conducted a systematic review and metaanalysis to establish if there is evidence as to which drug, either flecainide or dronedarone, is more effective to maintain sinus rhythm following electrocardioversion for persistent AF.The authors concluded that dronedarone and flecainide displayed similar efficacy in maintaining SR in patients following electrocardioversion for persistent AF.4][5] Since hematuria may be associated with urinary tract cancer, Dr Rasmussen et al. from Denmark, aimed to investigate the potential association between gross hematuria and urinary tract cancer in anticoagulated patients with AF.They included 125 063 AF patients from Danish nationwide registers.They concluded that gross hematuria was associated with clinically relevant risks of urinary tract cancer in anticoagulated patients with AF.Dr Elgandy and coworkers from the United States have examined the efficacy and safety of direct oral anticoagulants (DOACs) versus low molecular weight heparin (LMWH) in patients with cancer-related venous thromboembolism (VTE).They used four randomized trials with a total of 2907 patients and found that compared with LMWH, DOACs were associated with lower risk of VTE recurrence and similar risk of major bleeding (MB) compared with LMWH.Oral anticoagulants, including vitamin K antagonists (VKAs) and DOACs, are usually given lifelong to prevent stroke in patients with nonvalvular atrial fibrillation (NVAF). 1 The prolonged use of VKAs is a concern, given their potential detrimental effect on bone metabolism. 6Dr Renoux et al. from Canada, have used Quebec administrative healthcare databases, including 10 306 new users of DOACs and 15 357 new users of VKAs.After propensity scorebased fine stratification and weighting, the authors found that prolonged use of DOACs is associated with a lower risk of fracture compared with VKAs.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".