Prehabilitation: metabolic considerations
Bibliographic record
Abstract
PURPOSE OF REVIEW: The major components of ERAS attenuate the inflammatory response and modulate metabolism in direction of sparing body protein and preserving function. However, these perioperative interventions might have limited effectiveness on postoperative outcomes if preoperative risk factors are not addressed and optimized. RECENT FINDINGS: The preoperative metabolic perturbations characterized by insulin resistance and sarcopenia might predispose patients to a higher degree of postoperative catabolism. High-risk populations for such metabolic disturbances include elderly and frail patients, and patients with metabolic syndrome. Research on the effect of prehabilitation on perioperative metabolism is limited, but recent findings suggest that interventions designed to improve insulin sensitivity prior to surgery might represent a promising therapeutic target to minimize surgical complications. SUMMARY: The present paper will discuss the metabolic implications of modulating preoperative risk factors with elements of multimodal prehabilitation, such as exercise training and nutrition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".