Oral anticoagulation versus antiplatelet therapy for secondary stroke prevention in patients with embolic stroke of undetermined source: A systematic review and meta-analysis
Bibliographic record
Abstract
Purpose We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the efficacy and safety of direct oral anticoagulation (DOAC) compared with antiplatelet therapy for secondary stroke prevention in adult patients with embolic stroke of undetermined source (ESUS). Method We searched major databases (Embase, MEDLINE, CINAHL, CENTRAL, and Web of Science) for RCTs published until March 2021. The primary outcome was recurrent stroke, and the main safety outcomes were major bleeding and clinically relevant non-major bleeding (CRNB). We assessed risk of bias using the Cochrane Risk of Bias tool. We used a random-effects model to determine pooled risk ratios and 95% confidence intervals in the datasets and key subgroups. Findings Our search identified two RCTs, involving a total of 12,603 patients with ESUS. Anticoagulation with dabigatran or rivaroxaban compared with aspirin did not reduce the risk of recurrent stroke (RR, 0.96 [0.76–1.20]) or increase major bleeding (RR, 1.77 [0.80–3.89]) but significantly increased the composite of major or clinically relevant non-major bleeding (RR, 1.57 [1.26–1.97]). Prespecified subgroup analysis demonstrated consistent results according to age and sex. Additional post-hoc subgroup analyses demonstrated consistent results according to prior stroke and presence of a patent foramen ovale but suggested that DOACs reduced recurrent stroke in patients with an estimated glomerular filtration rate (eGFR) <50 and 50-80 ml/min but not in those with eGFR >80 ml/min (interaction P = 0.0234). Discussion/conclusion Direct oral anticoagulations are not more effective than aspirin in preventing stroke recurrence in patients with ESUS and increase bleeding. Registration PROSPERO ID: CRD42019138593
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.033 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".