Risk of stroke and other adverse outcomes in patients with perioperative atrial fibrillation 1 year after non-cardiac surgery
Bibliographic record
Abstract
AIMS: To determine the 1-year risk of stroke and other adverse outcomes in patients with a new diagnosis of perioperative atrial fibrillation (POAF) after non-cardiac surgery. METHODS AND RESULTS: The PeriOperative ISchemic Evaluation (POISE)-1 trial evaluated the effects of metoprolol vs. placebo in 8351 patients, and POISE-2 compared the effect of aspirin vs. placebo, and clonidine vs. placebo in 10 010 patients. These trials included patients with, or at risk of, cardiovascular disease who were undergoing non-cardiac surgery. For the purpose of this study, we combined the POISE datasets, excluding 244 patients who were in atrial fibrillation (AF) at the time of randomization. Perioperative atrial fibrillation was defined as new AF that occurred within 30 days after surgery. Our primary outcome was the incidence of stroke at 1 year of follow-up; secondary outcomes were mortality and myocardial infarction (MI). We compared outcomes among patients with and without POAF using multivariable adjusted Cox proportional hazards models. Among 18 117 patients (mean age 69 years, 57.4% male), 404 had POAF (2.2%). The stroke incidence 1 year after surgery was 5.58 vs. 1.54 per 100 patient-years in patients with and without POAF, adjusted hazard ratio (aHR) 3.43, 95% confidence interval (CI) 2.00-5.90; P < 0.001. Patients with POAF also had an increased risk of death (incidence 31.37 vs. 9.34; aHR 2.51, 95% CI 2.01-3.14; P < 0.001) and MI (incidence 26.20 vs. 8.23; aHR 5.10, 95% CI 3.91-6.64; P < 0.001). CONCLUSION: Patients with POAF have a significantly increased risk of stroke, MI, and death at 1 year. Intervention studies are needed to evaluate risk reduction strategies in this high-risk population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".