Early Extubation and Fast-Track Management of Off-Pump Cardiac Patients in the Intensive Care Unit
Bibliographic record
Abstract
Off-pump surgery was the original approach to treating patients with cardiac disease in the era before cardiopulmonary bypass. With the advent and refinement of cardiopulmonary bypass, the use of this technique fell out of favor and was quickly surpassed by on-pump techniques. However, the limitations of bypass surgery, especially for coronary artery bypass procedures, was still significant, leading to renewed interest in this technique. Postoperative care for off-pump coronary artery bypass (OPCAB) surgery presents both a challenge and opportunity to the intensivist. OPCAB patients can be treated in a fast-track manner allowing rapid recovery and early extubation and discharge from the intensive care unit. This is supported through the use of protocols that help standardize care and set expectations for the post-cardiac care team. Importantly, complications that may delay recovery including hypothermia, hypotension, and bleeding must be recognized early and treated aggressively to prevent unwanted complications and intensive care delays. Finally, care of these patients has shifted to the post-anesthesia recovery room, making knowledge of the care of these patients in the early postoperative period essential for cardiac anesthesiologists. This article will discuss the care of OPCAB patients following surgery and include approaches to managing patients who return both intubated and extubated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".