Outcome of Patients With Prior Stroke/Transient Ischemic Attack and Acute Coronary Syndromes
Bibliographic record
Abstract
The association between prior stroke/transient ischemic attack (TIA) and clinical outcomes in patients with acute coronary syndrome (ACS) has not been well explored. We evaluated the impact of prior stroke/TIA on this specific patient population. We conducted an international multicenter study including 15 401 patients with ACS from the Bleeding Complications in a Multicenter Registry of Patients Discharged With Diagnosis of Acute Coronary Syndrome registry. They were divided into 2 groups: patients with and without prior stroke/TIA. The primary end point was death at 1-year follow-up. Prior stroke/TIA was associated with higher rate of 1-year death (8.7% vs 3.4%; P < .001). It was an independent predictor of 1-year death even after adjustment for confounding variables (odds ratio, 1.705; 95% confidence interval, 1.046-2.778; P = .032). Besides, patients with prior stroke/TIA had significantly increased 1-year reinfarction (5.6% vs 3.8%, P = .015), in-hospital bleeding (8.7% vs 5.8%, P < .001), and 1-year bleeding (5.2% vs 3.0%, P < .001). No difference of antithrombotic therapies or dual antiplatelet therapy (DAPT) types on outcomes was observed in patients with prior stroke/TIA. Prior stroke/TIA was associated with higher 1-year death for patients with ACS who underwent percutaneous coronary intervention. No benefits or harms were observed with different antithrombotic therapies or DAPT types in these patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".