P.072 Ticagrelor vs Clopidogrel in Addition to Aspirin in Minor Ischemic Stroke/ TIA – a Systematic Review & Network Meta-Analysis (NMA)
Bibliographic record
Abstract
Background: Dual antiplatelet therapy (DAPT) is recommended after minor ischemic stroke/ transient ischemic attack (TIA), but Clopidogrel/ Aspirin has never been compared directly to Ticagrelor/ Aspirin. Our objective is to compare these regimens in terms of efficacy and safety. Methods: Medline, Embase, and Cochrane were searched for randomized controlled trials (RCTs) that enrolled adults with minor stroke/ TIA and administered antiplatelets within 72 hours. The primary efficacy outcome is recurrent stroke or death at 90 days. We performed a Bayesian-approach NMA. Between group comparisons were presented as odds-ratios (OR) with 95% credible intervals (95%CI). Sucraplots were based on calculated probabilities of rankings for individual outcomes. Results: 9/4014 studies were included: 5 RCTs and 4 subgroup analyses. 22,098 patients were analyzed. At 90 days, both DAPT regimens were superior to Aspirin in the prevention of recurrent stroke/ death. There was no significant difference between Clopidogrel/ ASA compared to Ticagrelor/ ASA (OR 0.90 [95%CI 0.74 – 1.09]), although Clopidogrel/ Aspirin was ranked #1 using Sucraplots. There was no significant difference between the interventions for mortality, bleeding, or adverse events. Conclusions: DAPT was superior to ASA in the prevention of recurrent strokes/ death, but there was no difference between Clopidogrel/ ASA and Ticagrelor/ ASA.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.039 |
| Bibliometrics | 0.006 | 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) | 0.009 | 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; 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".