Direct oral factor Xa inhibitors for the prevention of non-central nervous systemic embolism patients with non-valvular atrial fibrillation - a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The aim of this systematic review and meta-analysis was to evaluate the efficacy of direct oral factor Xa inhibitors for preventing non-central nervous systemic embolism in patients with non-valvular atrial fibrillation. METHODS: We conducted a systematic review of the following databases: Ovid MEDLINE, EUROPUBMED, EMBASE, and the Cochrane Central Register of Controlled Trials, from July 1st 1990 to April 1st, 2015. Randomised controlled trials were included if they reported the outcomes of patients with non-valvular atrial fibrillation treated with a direct oral factor Xa inhibitors compared to a vitamin K antagonist. The primary outcome was objectively confirmed as non-central nervous systemic embolism and ischaemic stroke was the secondary outcome. The random-effects model odds ratio was used as the outcome measure. RESULTS: Our initial search identified 987 relevant articles, of which three satisfied our inclusion criteria and were included. Compared to vitamin K antagonists targeting an INR between 2 and 3, direct oral factor Xa inhibitors alone did not reduce the incidence of non-central nervous systemic embolism [OR 0.63 (95 % CI 0.30 - 1.35)] or ischaemic stroke [OR 1.06 (95 % CI 0.86 - 1.32)]. CONCLUSIONS: As a drug class, direct oral factor Xa inhibitors do not reduce the incidence of non-central nervous systemic embolism (or ischaemic stroke) in patients with non-valvular atrial fibrillation. Selecting drugs for the prevention of non-central nervous systemic embolism in patients with non-valvular atrial fibrillation should be based on individual drug efficacy data, rather than class data.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".