Nutritional Approach in Malnourished Surgical Patients
Bibliographic record
Abstract
Hypothesis Perioperative administration of a supplemented enteral formula may decrease postoperative morbidity. Design Randomized clinical trial. Setting Department of surgery at a university hospital. Patients One hundred ninety-six registered malnourished patients (weight loss ≥10%) who were candidates for major elective surgery for malignancy of the gastrointestinal tract. Intervention After randomization (n = 150), one group received postoperative enteral feeding with a standard diet within 12 hours of surgery (control group; n = 50). Another group orally received 1 L/d for 7 consecutive days of a liquid diet enriched with arginine, ω-3 fatty acids, and RNA (preoperative group; n = 50). After surgery, patients were given the same standard enteral formula as the control group. A third group orally received 1 L/d for 7 consecutive days of the enriched liquid diet. After surgery, patients were given enteral feeding with the same enriched formula (perioperative group; n = 50). Main Outcome Measures Postoperative complications and length of hospital stay. Results The 3 groups were comparable for baseline demographics, biochemical markers, comorbidity factors, and surgical variables. The intent-to-treat analysis showed that the total number of patients with complications was 24 in the control group, 14 in the preoperative group, and 9 in the perioperative group (P= .02, control group vs perioperative group). Postoperative length of stay was significantly shorter in the preoperative (13.2 days) and perioperative (12.0 days) groups than in the control group (15.3 days) (P= .01 andP= .001, respectively, vs the control group). Conclusion Perioperative immunonutrition seems to be the best approach to support malnourished patients with cancer.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".