Impact of the antiplatelet strategy following patent foramen ovale percutaneous closure
Bibliographic record
Abstract
AIMS: Temporary dual antiplatelet therapy (DAPT) is recommended following patent foramen ovale (PFO) percutaneous closure although its benefit, compared to single antiplatelet therapy (SAPT), has not been demonstrated in this setting. We aimed at assessing outcomes following PFO closure according to the antiplatelet strategy at discharge. METHODS AND RESULTS: The ambispective AIR-FORCE cohort included consecutive patients from seven centres in France and Canada undergoing PFO closure and discharged without anticoagulation. Patients treated in French and Canadian centres were mostly discharged with DAPT and SAPT, respectively. The primary endpoint was the composite of death, stroke, transient ischaemic attack, peripheral embolism, myocardial infarction, or BARC type ≥2 bleeding with up to 5 years of follow-up. The impact of the antiplatelet strategy on outcomes was evaluated with a marginal Cox model (cluster analyses per country) with inverse probability weighting according to propensity score. A total of 1532 patients (42.2% female, median age: 49 [40-57] years) were included from 2001 to 2022, of whom 599 (39.1%) were discharged with SAPT and 933 (60.9%) with DAPT, for ≤3 months in 894/923 (96.9%) cases. After a median follow-up of 2.4 [1.1-4.4] years, a total of 58 events were observed. In the weighted analysis, the rate of the primary endpoint up to 5 years was 7.8% in the SAPT strategy and 7.3% in the DAPT strategy (weighted hazard ratio 1.04, 95% confidence interval 0.59-1.83). CONCLUSION: The antiplatelet strategy following PFO closure did not seem to impact clinical outcomes, thus challenging the current recommendations of temporary DAPT.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".