Stroke After Coronary Bypass Surgery Is Mainly Related to Diffuse Atherosclerotic Disease
Bibliographic record
Abstract
<p><b>Objective:</b> This study aims to investigate the risk factors for postoperative stroke and analysis of outcome after coronary bypass surgery with cardiopulmonary bypass.</p><p><b>Methods:</b> Between 1999 and 2008, 3248 consecutive patients who underwent isolated coronary surgery with cardiopulmonary bypass were prospectively enrolled in the study. Demographic and perioperative data were analyzed. Postoperative stroke was defined as severe adverse neurological events including permanent deficits or cerebral lesions with radiological demonstration of cerebral infarction within the first postoperative month.</p><p><b>Results:</b> In total, 32 patients (0.9%) were determined with stroke. Univariate risk factors for postoperative stroke were determined as preoperative unstable angina (<i>P</i> = .006), Canadian Class of Angina (CCA) ? 3 (<i>P</i> = .001), preoperative creatinin level >1.2 mg/dL (<i>P</i> = .001), left main coronary artery disease (<i>P</i> = .04), chronic obstructive lung disease (<i>P</i> = .04), peripheral arterial disease (<i>P</i> < .001), New York Heart Association (NYHA) Class ? 3 (<i>P</i> = .004), preoperative renal insufficiency (<i>P</i> = .001), age > 65 years (<i>P</i> = .04), preoperative hypothyroidism (<i>P</i> = .02), postoperative low cardiac output state (<i>P</i> < .001), severe coronary artery disease requiring distal anastomosis ? 4 (<i>P</i> = .05), non-elective operation (<i>P</i> = .02), and body mass index ? 25 (<i>P</i> = .02). Multivariate analysis revealed peripheral arterial disease (odds ratio [OR], 5.2; 95% confidence interval [CI], 1.9-14.0; <i>P</i> = .001), severe coronary artery disease (OR, 3.1; 95% CI, 1.1-8.5; <i>P</i> = .02), and postoperative low cardiac output state (OR, 5.1; 95% CI, 1.4-18.2; <i>P</i> = .01) as the independent risk factors.</p><p><b>Conclusions:</b> Stroke after coronary bypass surgery with cardiopulmonary bypass is mainly related to diffuse atherosclerotic disease.</p>
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".