Nutrition in the Neoadjuvant Gastric Cancer Patient, is early administration appropriate?
Bibliographic record
Abstract
ABSTRACT Purpose: Gastric cancer is one of the world's leading cancers. Despite the availability of testing, patients often present with advanced (stage III or stage IV) gastric cancer. These patients are always in a state of malnutrition and will be sarcopenic secondary to pain, loss of appetite, nausea, vomiting and dysphagia. Treatment for this cancer includes radical surgery, sometimes chemotherapy and rarely radiotherapy. It is already well documented that nutrition is critical to patient outcomes during chemotherapy, surgery and healing; because of this, many measures are already in place to improve nutrition in these patients. This literature review will look directly at the use of enteral feeding (EN) of gastric cancer patients prior to or in conjunction with neoadjuvant chemotherapy (NACT). Methods: Research was focused on the keywords: nutrition, gastric cancer, enteral feeding and neoadjuvant nutrition. Several electronic journals were reviewed, National Center for Biotechnology Information (NCBI), PubMed, QxMD Read, Science Direct, as well, a search was conducted through Alberta Health Services Knowledge Resource Service (KRS). Results: The combined information within each of the articles reviewed all recognized that early nutrition supplementation had positive impacts on maintaining albumin levels, an increase in the patient's immunity, improved healing and shortened length of hospital stay. Conclusion: All patients receive nutrition throughout their hospital stay; research indicates that the earlier nutrition is given to a patient, the better the overall outcomes of chemotherapy, surgery, shortened length of stay, and quality of life. Keywords: nutrition, gastric cancer, enteral feeding and neoadjuvant nutrition.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".