Does perioperative nutrition improve clinical outcomes in patients undergoing upper gastrointestinal surgery?: A network meta-analysis.
Bibliographic record
Abstract
Each year in Canada, more than 2000 patients undergo surgical resection for treatment of esophageal, pancreatic or stomach cancer. However, resection of upper gastrointestinal (GI) malignancies is associated with significant mortality and morbidity. One reason for the high rate of complications in this population of patients is preoperative malnutrition. To counteract the effects of malnutrition, post-operative nutritional support is often provided to these patients. Nutrition can be provided directly into the central circulation by total parenteral nutrition (TPN) or into the GI tract via a nasojejunal tube (a catheter passed through the nose into the small bowel) or a surgically placed jejunostomy tube (through the anterior abdominal wall and into the small bowel). It remains unclear which method of nutrient delivery, if any, provides the best overall patient outcomes. For this reason, we have undertaken a network meta-analysis to evaluate the effects of the various perioperative nutritional delivery methods on clinical outcomes in patients undergoing upper gastrointestinal surgery.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.023 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".