E-030 Antiplatelet therapy is associated with better outcomes in patients with moyamoya disease. a meta-analysis
Bibliographic record
Abstract
Introduction Moyamoya disease causes progressive stenosis of the supraclinoid internal carotid arteries with subsequent development of moyamoya collaterals. The mainstay treatment is surgical revascularization using direct or indirect bypass techniques. The use of antiplatelet agents is advocated to facilitate blood flow, maintain bypass patency, and reduce thrombotic events. We searched published literature to determine the benefits of antiplatelet therapy in this patient population. Methods We performed a literature search of published papers in the English language using EMBASE, PUBMED, and Web of Science databases. With the assistance of a librarian, we used various combinations of keywords such as Moyamoya disease, ischemic stroke, hemorrhagic stroke, antiplatelet, and the names of individual antiplatelet agents. Titles and abstracts were screened by the first two authors (MAS and MEE), with a full-text review of relevant papers. Articles were included if they examined the effect of antiplatelet therapy on ischemic or hemorrhagic stroke or survival in patients with moyamoya disease. Results Out of 132 retrieved studies, we identified five eligible studies published between 2014 and 2019 and included 26,605 patients (9499 on antiplatelet therapy, and 17106 controls) with follow up ranging from post-operative period to 6.3 years. Only one study had a prospective design and two studies were multi-center. Three of the studies included post-bypass patients, and one included only asymptomatic moyamoya disease. The antiplatelet therapy regimens varied across the studies and included ASA, clopidogrel, or cilostazol.Three studies had a control arm that did not receive any antiplatelet therapy. In these studies, the pooled risk for a composite outcome (any ischemic or hemorrhagic stroke, or death) was lower in the antiplatelet group compared to controls (9% vs 11%; relative risk 0.85, 95% CI: 0.79 to 0.92). Conclusions The use of antiplatelet therapy in patients with moyamoya disease may confer better stroke-free survival. Multicenter prospective studies with a uniform antiplatelet protocol are needed to elucidate the potential benefits of this intervention. Disclosures M. Suheel: None. M. Eagles: None. M. Almekhlafi: None.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.036 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".