Short- and long-term outcomes following atrial fibrillation in patients with acute coronary syndromes with or without ST-segment elevation
Bibliographic record
Abstract
OBJECTIVE: To assess variables associated with the occurrence of atrial fibrillation (AF) and the relation of AF with short- and long-term outcomes and with other in-hospital complications in patients with acute coronary syndromes (ACS) with and without ST-segment elevation. DESIGN: Pooled database of 120 566 patients with ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation (NSTE) ACS enrolled in 10 clinical trials. Multivariable logistic regression and Cox proportional hazards modelling were used to identify factors associated with AF and its relation with clinical outcomes. SETTING: ACS complicated by AF. PATIENTS: 120,566 patients with STEMI and NSTE-ACS in 10 clinical trials. INTERVENTIONS: None evaluated. MAIN OUTCOME MEASURE: Short- and long-term mortality. RESULTS: Occurrence of AF was 7.5% in the overall population (STEMI 8.0% (n = 84 161); NSTE-ACS = 6.4% (n = 36,405)). Seven-day mortality was higher for patients with AF (5.1%) than for those without (1.6%). After adjusting for confounders, association of AF with 7-day mortality was present in STEMI (hazards ratio (HR) = 1.65; 95% CI 1.44 to 1.90) and NSTE-ACS (HR = 2.30; 95% CI 1.83 to 2.90; p interaction = 0.015). Risk of long-term mortality (day 8 to 1 year) was also higher in STEMI (HR = 2.37; 95% CI 1.79 to 3.15) and NSTE-ACS (HR = 1.67; 95% CI 1.41 to 1.99). AF had a larger impact in NSTE-ACS on risk of short-term mortality (p<0.001), stroke (p<0.001), ischaemic stroke (p<0.001) and moderate or severe bleeding (p<0.001). CONCLUSIONS: AF is more common in patients with STEMI. An association of AF with short- and long-term mortality among patients with STEMI and NSTE-ACS was found. Understanding these findings may lead to better care of patients with this common arrhythmia.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".