Outcomes of management strategies in patients with prior coronary artery bypass grafting presenting with an acute coronary syndrome
Bibliographic record
Abstract
BACKGROUND: Patients with prior coronary artery bypass grafting (CABG) presenting with an acute coronary syndrome (ACS) have poor outcomes and the optimal treatment strategy for this population is unknown. METHODS: Using linked administrative databases, we examined patients with an ACS between 2008 and 2019, identifying patients with prior CABG. Patients were categorized by ACS presentation type and treatment strategy. Our primary outcome was the composite of death and recurrent myocardial infarction at one year. RESULTS: Of 54,641 patients who presented with an ACS, 1670 (3.1%) had a history of prior CABG. Of those, 11.0% presented with an ST-elevation myocardial infarction (STEMI) of which, 15.3% were treated medically, 31.1% underwent angiography but were treated medically, 22.4% with fibrinolytic therapy and 31.1% with primary PCI. The primary outcome rate was the highest (36.8%) in patients who did not undergo angiography and was similar in the primary PCI (20.8%) and fibrinolytic group (21.9%). In patients presenting with a non-ST elevation acute coronary syndrome (NSTE-ACS) (89.0%), 33.2% were treated medically, 38.5% underwent angiography but were treated medically and 28.2% were treated with PCI. Compared to those who underwent PCI, patients treated conservatively demonstrated a higher risk of the composite outcome (14.8% vs 27.3%; adjusted hazard ratio 1.70, 95% confidence interval 1.22-2.37). CONCLUSIONS: Patients with prior CABG presenting with an ACS are often treated conservatively without PCI, which is associated with a higher risk of adverse events.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".