Predictors of early and late stroke following cardiac surgery
Bibliographic record
Abstract
BACKGROUND: Much is known about the short-term risks of stroke following cardiac surgery. We examined the rate and predictors of long-term stroke in a cohort of patients who underwent cardiac surgery. METHODS: We obtained linked data for patients who underwent cardiac surgery in the province of Ontario between 1996 and 2006. We analyzed the incidence of stroke and death up to 2 years postoperatively. RESULTS: Of 108,711 patients, 1.8% (95% confidence interval [CI] 1.7%-1.9%) had a stroke perioperatively, and 3.6% (95% CI 3.5%-3.7%) had a stroke within the ensuing 2 years. The strongest predictors of both early and late stroke were advanced age (≥ 65 year; adjusted hazard ratio [HR] for all stroke 1.9, 95% CI 1.8-2.0), a history of stroke or transient ischemic attack (adjusted HR 2.1, 95% CI 1.9-2.3), peripheral vascular disease (adjusted HR 1.6, 95% CI 1.5-1.7), combined coronary bypass grafting and valve surgery (adjusted HR 1.7, 95% CI 1.5-1.8) and valve surgery alone (adjusted HR 1.4, 95% CI 1.2-1.5). Preoperative need for dialysis (adjusted odds ratio [OR] 2.1, 95% CI 1.6-2.8) and new-onset postoperative atrial fibrillation (adjusted OR 1.5, 95% CI 1.3-1.6) were predictors of only early stroke. A CHADS2 score of 2 or higher was associated with an increased risk of stroke or death compared with a score of 0 or 1 (19.9% v. 9.3% among patients with a history of atrial fibrillation, 16.8% v. 7.8% among those with new-onset postoperative atrial fibrillation and 14.8% v. 5.8% among those without this condition). INTERPRETATION: Patients who had cardiac surgery were at highest risk of stroke in the early postoperative period and had continued risk over the ensuing 2 years, with similar risk factors over these periods. New-onset postoperative atrial fibrillation was a predictor of only early stroke. The CHADS2 score predicted stroke risk among patients with and without atrial fibrillation.
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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 | 0.003 | 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 | 0.000 | 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".