Secondary Prevention of Cryptogenic Stroke and Outcomes Following Surgical Patent Foramen Ovale Closure Plus Medical Therapy vs. Medical Therapy Alone: An Umbrella Meta-Analysis of Eight Meta-Analyses Covering Seventeen Countries
Bibliographic record
Abstract
Background: Cryptogenic stroke (CS) is an exclusion diagnosis that accounts for 10-40% of all ischemic strokes. Patent foramen ovale (PFO) is found in 66% of patients with CS, while having a prevalence of 25-30% in the general population. The primary aim was to evaluate the risk of recurrent stroke following surgical PFO closure plus medical therapy vs. medical therapy alone amongst CS, an embolic stroke of undetermined source (ESUS), or transient ischemic attack (TIA). The secondary aim was to evaluate new-onset non-valvular atrial fibrillation, mortality, and major bleeding. Methods: We conducted an umbrella meta-analysis using PRISMA guidelines on English studies comparing surgical PFO closure plus medical therapy versus medical therapy alone for managing CS. We extracted data on interventions and outcomes and used random-effects models with generic inverse variance to calculate relative risks (RRs) with 95% confidence intervals for outcome calculations. Results: A comprehensive search yielded 54,729 articles on CS and 65,001 on surgical PFO closure, with 1,591 studies focusing on PFO closure and medical therapy for secondary CS, ESUS, or TIA prevention. After excluding non-meta-analyses, 52 eligible meta-analyses were identified, and eight studies were selected for outcome evaluation, excluding non-English, non-human, and studies before January 2019 as of August 31, 2021. Among a total of 41,880 patients, 14,942 received PFO closure + medical therapy, while 26,938 patients received medical therapy alone. Our umbrella meta-analysis showed that PFO closure plus medical therapy had a 64% lower risk of recurrent strokes than medical therapy alone (pooled RR: 0.36). PFO closure plus medical therapy was associated with 4.94 times higher risk of atrial fibrillation. There was no difference in the risk of death or bleeding between both groups. Conclusion: In patients with CS, PFO closure, in addition to medical therapy, reduces the risk of recurrence. More research is needed to assess the efficacy of early closure as well as specific risk profiles that would benefit from early intervention to reduce the burden of stroke.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".