Abstract 208: Periprocedural Stroke and Myocardial Infarction as Risks for Long-term Mortality in CREST
Bibliographic record
Abstract
Introduction: Occurrence of stroke and myocardial infarction (MI) after carotid endarterectomy or stenting have each been associated with increased later mortality. Methods: In the Carotid Revascularization Endarterectomy versus Stenting Trial (CREST) 69 strokes, 37 protocol MIs, and 19 biomarker + only events occurred within 30 days among 2272 patients followed up to 10 years. Mortality was determined and compared for patients with stroke, MI, or biomarker + only to those without. Cox proportional hazard models adjusting for age, sex, symptomatic status and treatment were calculated to assess the relationship between mortality and stroke and mortality and MI status. Kaplan-Meier survival curves were plotted. Results: Patients with peri-procedural stroke had a 67% greater likelihood of long-term mortality compared to those without stroke (HR=1.67, 95% CI 1.15,2.43; p<0.007)(Figure A). Patients with a protocol MI had a 249% greater likelihood of mortality, and biomarker+ only patients had a 104% greater likelihood of mortality, compared to those without MI (HR=3.49; 95%CI 2.20,5.53, p<0.0001; and HR=2.04; 95% CI 1.09,3.83, p=0.03)(Figure B). Discussion: Stroke, MI, and biomarker + only events following CEA or CAS are associated with increased long-term mortality. The higher risk for MI may be a marker for patients with serious underlying heart disease, rather than causal, providing an opportunity to decrease long-term mortality through aggressive diagnostic evaluation and preventive treatment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".