Anesthesia for off-pump coronary artery bypass surgery
Bibliographic record
Abstract
The evolution of techniques and knowledge of beating heart surgery has led anesthesia toward the development of new procedures and innovations to promote patient safety and ensure high standards of care. Off-pump coronary artery bypass (OPCAB) surgery has shown to have some advantages compared to on-pump cardiac surgery, particularly the reduction of postoperative complications including systemic inflammation, myocardial injury, and cerebral injury. Minimally invasive surgery for single vessel OPCAB through a limited thoracotomy incision can offer the advantage of further reduction of complications. The anesthesiologist has to deal with different issues, including hemodynamic instability and myocardial ischemia during aorto-coronary bypass grafting. The anesthesiologist and surgeon should collaborate and plan the best perioperative strategy to provide optimal care and ensure a rapid and complete recovery. The use of high thoracic epidural analgesia and fast-track anesthesia offers particular benefits in beating heart surgery. The excellent analgesia, the ability to reduce myocardial oxygen consumption, and the good hemodynamic stability make high thoracic epidural analgesia an interesting technique. New scenarios are entering in cardiac anesthesia: ultra-fast-track anesthesia with extubation in the operating room and awake surgery tend to be less invasive, but can only be performed on selected patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".