Abstract 1173: Risk of Recurrent Cerebrovascular Events in Patients with Cryptogenic Cerebral Ischemia and Patent Foramen Ovale: A Meta-Analysis of Observational Studies
Bibliographic record
Abstract
In patients with a patent foramen ovale (PFO) and a prior cryptogenic ischemic stroke or transient ischemic attack (TIA), the risk of recurrent events is unclear. To conduct a systematic review and meta-analysis of studies assessing the risk of recurrent cerebrovascular events in patients with cryptogenic cerebral ischemia and PFO. MEDLINE (1950 to February 2008) and EMBASE (1980 to February 2008) databases were searched to identify studies in any language. Searches were supplemented by scanning bibliographies of key articles. Studies reporting original data on recurrent cerebrovascular events in patients with prior cryptogenic stroke or TIA and PFO, with or without a non-PFO comparison group, were included. Uncontrolled case series evaluating device or surgical closure of PFO were excluded. Two authors independently extracted the data from included studies and evaluated study quality. For studies with a non-PFO comparison group, relative risks were pooled using a fixed effects model after confirming homogeneity of results. For all studies, the pooled absolute rate of recurrent events was calculated using a random effects model due to heterogeneity of results. Fifteen studies published between 1994 and 2007, following 2377 patients over a mean of 37 months were included. In the four studies with a non-PFO comparison group, the pooled relative risk of recurrent stroke or TIA associated with the presence of a PFO was 1.1 (95% CI 0.8 to 1.5), while for recurrent ischemic stroke the pooled relative risk associated with the presence of a PFO was 0.8 (95% CI 0.5 to 1.3). The pooled absolute rate of recurrent ischemic stroke or TIA in patients with PFO was 4.0 events per 100 person-years (95% CI 3.0 to 5.1) while the rate of recurrent ischemic stroke was 1.6 events per 100 person years (95% CI 1.1 to 2.1). No clinical or imaging features are reliably associated with increased risk of recurrent events. In medically treated patients with prior cryptogenic stroke, available evidence does not support an increased risk of recurrent ischemic events in those with vs. without a PFO. Routine PFO closure in these patients may not be warranted, outside of ongoing clinical trials.
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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 | 0.020 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.060 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".