Management of early postoperative coronary artery bypass graft failure
Bibliographic record
Abstract
Perioperative graft failure following coronary artery bypass grafting (CABG) may result in acute myocardial ischaemia. Whether acute percutaneous coronary intervention, emergency reoperation or conservative intensive care treatment should be used is currently unknown. Between 2003 and 2009, 39 of the 5598 patients who underwent isolated CABG surgery underwent early postoperative coronary angiography for suspected myocardial ischaemia. Following angiography, two groups were identified: patients who underwent immediately reintervention (group 1); and those treated conservatively (group 2). Primary study endpoints were mortality and postoperative myocardial infarct size. Postoperative coronary angiography revealed early perioperative bypass graft failure in 32 of 39 patients. Acute percutaneous coronary intervention was performed in 15 patients, redo-CABG in 4 patients and conservative treatment in 13 patients. The number of failing bypass grafts were significantly higher in group 1 compared with group 2 (P = 0.0251). A trend toward lower post-procedural peak cardiac troponin T and creatinine phosphokinase serum levels in group 1 was observed (163.0 vs. 206.0 and 4.35 vs. 5.53, respectively) (P = 0.0662 and 0.1648). Early reintervention may limit the extent of myocardial cellular damage compared with conservative medical strategy in patients with myocardial ischaemia due to early graft failure.
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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 | 0.000 |
| 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 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".