Controversies in enhanced recovery after cardiac surgery
Bibliographic record
Abstract
Advances in cardiac surgical operative techniques and myocardial protection have dramatically improved outcomes in the past two decades. An unfortunate and unintended consequence is that 80% of the preventable morbidity and mortality following cardiac surgery now originates outside of the operating room. Our hope is that a renewed emphasis on evidence-based best practice and standardized perioperative care will reduce overall morbidity and mortality and improve patient-centric care. The Perioperative Quality Initiative (POQI) and Enhanced Recovery After Surgery-Cardiac Society (ERAS® Cardiac) have identified significant evidence gaps in perioperative medicine related to cardiac surgery, defined as areas in which there is significant controversy about how best to manage patients. These five areas of focus include patient blood management, goal-directed therapy, acute kidney injury, opioid analgesic reduction, and delirium.
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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 | 0.017 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.023 | 0.037 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".