Initial Perioperative Care of the Cardiac Surgical Patient
Bibliographic record
Abstract
Recently, changes in the management of cardiac patients have allowed earlier discharge from the cardiac recovery area and reduced hospital length of stay. These changes have been drien by a need to reduce the cost of cardiac surgery and imrove efficiency. This change has been both financially sucessful and safe for patients. To allow for this success, a joint effort is required between the departments of cardiac surgery and anesthesiology involving the preoperative, intraoperative and postoperative treatment of these patients. Through recogition of suitable candidates, modifications in anesthetic techique, and appropriate postoperative management, the goal of extubation within 6 hours of admission to the cardiac recovery area can be achieved. Changes in intraoperative and early postoperative management of cardiac surgical patients are discussed. Specific recovery models are reviewed with disussion of the parallel and integrated models. Methods of preicting prolonged extubation times and intensive care unit length of stay are also discussed. Initial management of the cardiac patient in the cardiac recovery area is presented with a more in-depth review of specific complications: stroke, atril fibrillation, blood loss, left ventricular dysfunction, and pulonary dysfunction.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".