Intravenous thrombolysis or antiplatelet therapy for acute nondisabling ischemic stroke: A systematic review and network meta-analysis
Bibliographic record
Abstract
PURPOSE: Uncertainties remain on the optimal treatment for acute minor stroke with nondisabling symptoms. The two most common therapeutic approaches are intravenous thrombolysis (IVT) and antiplatelet therapy, notably dual antiplatelet therapy (DAPT). We synthesized data from the literature to compare IVT to DAPT and identify the best treatment for this population. METHOD: We systematically searched Pubmed, Web of Science and the Cochrane Library for randomized trials and observational studies comparing IVT, aspirin, and/or DAPT, started within 24 h of symptom onset in patients with minor stroke (NIHSS ⩽ 5) and nondisabling symptoms. Random-effects Bayesian network meta-analysis was conducted. The primary outcome was excellent functional outcome at 3 months (mRS 0-1). Secondary outcomes included mRS 0-2, symptomatic intracranial hemorrhage, mortality, and recurrent stroke. FINDINGS: Four randomized trials and 2 observational studies (5897 patients for the analysis of the primary outcome) were included. Compared with IVT (alteplase), DAPT (clopidogrel + aspirin) was significantly associated with higher odds of mRS 0-1 (OR = 1.52, 95% CrI, 1.09-2.35), but aspirin alone was not (OR = 1.36, 95% CrI, 0.87-2.30). DAPT was also associated with lower odds of symptomatic intracranial hemorrhage than alteplase (OR = 0.14, 95% CrI, 0.03-0.91). There were no significant differences between treatment groups regarding the other outcomes. For each outcome, the ranking for the best treatment was DAPT, then aspirin, and then IVT. DISCUSSION/CONCLUSION: This network meta-analysis suggests that DAPT may be the optimal treatment for acute nondisabling stroke, with higher odds of excellent functional outcome compared with IVT. REGISTRATION: PROSPERO ID: CRD42024522038.
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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 | 0.019 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.035 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".