Long-term cerebrovascular outcomes of patients undergoing percutaneous patent foramen ovale closure in observational studies: a systematic review and meta-analysis
Bibliographic record
Abstract
Objectives Patent foramen ovale (PFO) closure is recommended for patients who experience a cryptogenic stroke attributable to PFO. Although few randomized control trials (RCTs) have captured long-term effectiveness of PFO closure, observational data has been abundant. This is the first systematic review of observational studies determining incidence of long-term adverse outcomes in adults who underwent transcatheter PFO closure, with comparisons to findings from RCTs. Methods Medline, Cochrane, and Embase databases were searched from inception to October 2023. Only observational studies with ≥4 years of mean or median follow-up were included. A meta-analysis was conducted to calculate the incidence of recurrent stroke after PFO closure. Results After reviewing 2,432 records, 13 prospective and 12 retrospective cohort studies were included. Average follow-up lengths ranged from 4 to 12.3 years, and sample sizes from 75 to 1,533 participants. The average age ranged between 43.5-63.0, and 24.0-72.8% patients had an atrial septal aneurysm. The incidence of stroke was 0.34 per 100 person-years (I 2 = 67%). This was similar to rates from four RCTs that were used for comparison (0.35 per 100 person-years, I 2 = 51%). There was a significant improvement in heterogeneity once the study with one of the largest follow-up was removed. Conclusions Real-world PFO closure studies with long-term follow-up report similar outcomes as RCTs which is important considering the exclusion of several important populations from trials. Future observational studies should include more rigorous reporting of follow-up strategies and explore different long-term adverse outcomes.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".