Direct Oral Anticoagulants versus Aspirin for Secondary Stroke Prevention in Patients with Embolic Stroke of Undetermined Source: An Updated Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Abstract Embolic stroke of undetermined source (ESUS) accounts for around 20% of ischemic strokes. The ideal treatment for secondary prevention in ESUS remains unclear. This study aimed to perform a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing the safety and efficacy of direct oral anticoagulants (DOACs) versus aspirin in patients with ESUS. A systematic search of PubMed, Embase, Cochrane, and Web of Science databases was conducted for eligible trials until March 2024. The primary outcome was recurrent stroke, while safety outcomes included major bleeding and clinically relevant non-major bleeding (CRNMB). Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated for analysis. Four RCTs were included, involving 13,970 patients, half of whom were randomized to the DOACs group. Over a mean follow-up of 16 months, DOACs did not significantly reduce recurrent stroke (HR: 0.95; 95% CI: 0.81-1.09; p=0.44), ischemic stroke (HR: 0.91; 95% CI: 0.79-1.06; p=0.23), all-cause mortality (HR: 1.11; 95% CI: 0.87-1.42; p=0.40), or major bleeding (HR: 1.56; 95% CI: 0.85%-2.86; p=0.15) compared to aspirin. However, DOACs were associated with a significantly higher risk of CRNMB (HR: 1.54; 95% CI: 1.23-1.92; p=0.0002). Subgroup analysis revealed no significant differences in stroke recurrence among patients with low or high CHA2-DS2-VASc scores. DOACs did not demonstrate superior efficacy over aspirin in preventing recurrent stroke among ESUS patients and were linked to an increased risk of CRNMB.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.007 | 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".