Patent Foramen Ovale Management for Secondary Stroke Prevention: State-of-the-Art Appraisal of Current Evidence
Bibliographic record
Abstract
Patent foramen ovale (PFO) is frequently identified in young patients with ischemic stroke. Randomized controlled trials provide robust evidence supporting PFO closure in selected patients with cryptogenic ischemic stroke; however, several questions remain unanswered. This report summarizes current knowledge on the epidemiology of PFO-associated stroke, the role of PFO as a cause of stroke, and anatomic high-risk features. We also comment on breakthrough developments in patient selection algorithms for PFO closure in relation to the PFO-associated stroke causal likelihood risk stratification system. We further highlight areas for future research in PFO-associated stroke including the efficacy and safety of PFO closure in the elderly population, incidence, and long-term consequences of atrial fibrillation post-PFO closure, generalizability of the results of clinical trials in the real world, and the need for assessing the effect of neurocardiology teams on adherence to international recommendations. Other important knowledge gaps such as sex, race/ethnicity, and regional disparities in access to diagnostic technologies, PFO closure devices, and clinical outcomes in the real world are also discussed as priority research topics.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".