Outcomes following patent foramen ovale percutaneous closure according to the delay from last ischemic event
Bibliographic record
Abstract
Abstract Background Randomized controlled trials evaluating patent foramen ovale (PFO) percutaneous closure only included patients with recent embolic event. We aimed to evaluate outcomes following percutaneous PFO closure outcomes according to the delay from the last embolic episode. Methods This international ambispective cohort included consecutive patients from two centers in France and Canada undergoing PFO percutaneous closure for secondary prevention of paradoxical embolic event. The primary endpoint was the composite of stroke or transient ischemic attack (TIA). Logistic regression model was used to evaluate determinants of late PFO closure procedures. Results A total of 1,179 patients (mean age 49±12.7 years; 44.4% female) underwent PFO closure from 2001 to 2021 (Figure 1). The median delay from last embolic event to procedure was 6.0 (3.4–11.2) months. Determinants of late PFO closure procedure were the center (France versus Canada) adjusted Odds Ratio (aOR) 1.65 95% confidence interval (CI) 1.25–2.19, year of procedure (≥2018 versus <2018) aOR 1.43 95% CI 1.08–1.90, female sex aOR 1.63 95% CI 1.28–2.07 and lower RoPE score aOR 1.10 95% CI 1.03–1.19. After a median follow-up of 2.61 (1.13–7.25) years, the incidence rate of first stroke or TIA did not differ between early and late PFO procedures with 0.51 versus 0.29 events per 100 patient-years, respectively, incidence rate ratio 1.74 95% CI 0.66–5.08, p=0.25 (Figure 2). In univariate analysis, late PFO percutaneous closure was not associated with the occurrence of stroke or TIA, with hazard ratio 0.54 95% CI 0.22–1.34 p=0.17. Conclusion This analysis provides indirect evidence that delay from last ischemic event does not impact outcomes following PFO percutaneous closure for secondary prevention. Funding Acknowledgement Type of funding sources: 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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".