Ticagrelor vs Clopidogrel in addition to Aspirin in minor ischemic stroke/ transient ischemic attack—Protocol for a systematic review and network meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Patients with minor ischemic stroke or transient ischemic attack represent a high-risk population for recurrent stroke. No direct comparison exists comparing dual antiplatelet therapy regimens-namely, Ticagrelor and Aspirin versus Clopidogrel and Aspirin. This systematic review and network meta-analysis (NMA) will examine the efficacy of these two different antiplatelet regimens in preventing recurrent stroke and mortality up to 30 days. METHODS AND ANALYSIS: MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) will be searched with the assistance of a medical information specialist. Two independent reviewers will screen studies for inclusion; eligible studies will include randomized controlled trials that enrolled adults presenting with acute minor ischemic stroke or transient ischemic attack and compared one or more of the interventions against each other and/or a control. The primary outcomes will be recurrent ischemic stroke up to 30 days from symptom onset. Secondary outcomes will include safety outcomes (I.e. major bleeding and mortality), functional disability, and outcomes up to 90 days from symptom onset. A Bayesian approach to NMA will be implemented using the BUGSnet function in R Software. Between group comparisons for time-to-event (TTE) and dichotomous outcomes will be presented in terms of hazard ratios and odds ratios with 95% credible intervals, respectively. Secondary effect measures of treatment ranking will also be estimated. ETHICS AND DISSEMINATION: No formal research ethics approval are necessary. We will disseminate our findings through scientific conference presentations, peer-reviewed publications, and social media/the press. The findings from this review will aid clinicians in decision-making on the choice of antithrombotic therapy in a high-risk stroke population and could be important in the development of future treatment trials and guidelines. Registration ID with Open Science Framework: 10.17605/OSF.IO/XDJYZ.
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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 | 0.053 | 0.071 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.024 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.058 | 0.006 |
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".