Influence of time elapsed between myocardial infarction and coronary artery bypass grafting surgery on operative mortality☆
Bibliographic record
Abstract
OBJECTIVE: Optimal timing for CABG surgery after myocardial infarction (MI) remains controversial. We examined the influence of patient age and time elapsed between MI and isolated CABG surgery on operative mortality. METHODS: Perioperative data of 13,545 patients who underwent isolated CABG surgery from 1991 to 2005 were reviewed. A previous MI was found in 7219 patients, classified among groups A-E whether they underwent surgery less than 6h (A, n=26), between 6 and 24h (B, n=51), between 1 and 7 days (C, n=313), between 8 and 30 days (D, n=917), or more than 30 days (E, n=5912) after the event. Crude percentages and odds ratio estimates of operative mortality were calculated. RESULTS: In patients who had no history of MI, the mortality rate was 1.7%, while it was, respectively, 19.2, 9.8, 8.6, 3.2, and 2.4% in patients from groups A to E. Among 6589 patients over 65 years of age, 3027 had no history of MI. Their mortality was 2.4%, compared to, respectively, 35.7, 13.8, 11.3, 5.1, and 3.9% for those belonging to groups A-E. Overall odds ratio estimates of operative mortality were 3.92 (p=0.19), 5.08 (p=0.002), 4.33 (p=0.0001), 1.50 (p=0.08), and 1.18 (p=0.24) for groups A-E, respectively. CONCLUSIONS: Operative mortality is not influenced by a history of MI sustained more than 30 days prior to isolated CABG surgery, but is highly and most significantly increased between 6h and 1 week after MI, especially in older patients. That critical period should be avoided whenever possible.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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".