Abstract 102: Consistency of Efficacy of PFO Closure in the Gore Reduce Trial
Bibliographic record
Abstract
Background: The Gore REDUCE Clinical Study (REDUCE) demonstrated superiority of PFO closure in conjunction with antiplatelet therapy over antiplatelet therapy alone in reducing the risk of recurrent clinical ischemic stroke or new silent brain infarct in patients with cryptogenic stroke. Methods: We randomized 664 subjects with cryptogenic stroke at 63 multinational sites in a 2:1 ratio to either antiplatelet therapy plus PFO closure (with Gore HELEX Septal Occluder or Gore CARDIOFORM Septal Occluder) or antiplatelet therapy alone. Co-primary endpoints were freedom from recurrent clinical ischemic stroke through ≥2 years and incidence of new brain infarct (defined as the composite of clinical ischemic stroke and silent brain infarct) at 2 years. Primary analyses were performed on the intention-to-treat (ITT) population. Per-protocol (PP) analysis included only subjects randomized and treated according to critical protocol requirements (excluding those who violated key eligibility criteria, did not receive the therapy to which they were randomized, or did not comply with protocol-required medical regimen). As-treated (AT) analysis assessed all subjects based on treatment received, regardless of study assignment. Results: PFO closure was associated with a highly consistent reduction in risk compared to medical therapy alone in all three analytic cohorts (Table). Conclusions: Among selected patients with cryptogenic stroke and PFO, closure of the PFO plus antiplatelet therapy was superior to antiplatelet therapy alone for reducing the risk of subsequent ischemic stroke.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".