Risk of Recurrent Stroke in Patients With Silent Brain Infarction in the Prevention Regimen for Effectively Avoiding Second Strokes (PRoFESS) Imaging Substudy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Silent brain infarctions are associated with an increased risk of stroke in healthy individuals. Risk of recurrent stroke in patients with both symptomatic and silent brain infarction (SBI) has only been investigated in patients with cardioembolic stroke in the European Atrial Fibrillation Trial. We assessed whether patients with recent noncardioembolic stroke and SBI detected on MRI are at increased risk for recurrent stroke, other cardiovascular events, and mortality. METHODS: The prevalence of SBI detected on MRI was assessed in 1014 patients enrolled in the imaging substudy of the Prevention Regimen for Effectively Avoiding Second Strokes (PRoFESS) trial. The primary outcome was first recurrence of stroke in patients with both symptomatic stroke and SBI in comparison with age- and sex-matched patients with stroke without SBI. Secondary outcomes were a combined vascular end point, other vascular events, and mortality. The 2 groups were compared using conditional logistic regression. RESULTS: Silent brain infarction was detected in 207 (20.4%) of the 1014 patients. Twenty-seven (13.0%) patients with SBI and 19 (9.2%) without SBI had a recurrent stroke (OR, 1.42; 95% CI, 0.79-2.56; P=0.24) during a mean follow-up of 2.5 years. Similarly, there was no statistically significant difference for all secondary outcome parameters between patients with SBI and matched patients without SBI. CONCLUSIONS: The presence of SBI in patients with recent mild noncardioembolic ischemic stroke could not be shown to be an independent risk factor for recurrent stroke, other vascular events, or a higher mortality rate. CLINICAL TRIAL REGISTRATION: URL: http://clinicaltrials.gov. Unique identifier: NCT00153062.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".