Outpatient Placement of Feeding Gastrostomy (PEG) Prior to Chemo-Radiation for Head & Neck Cancer
Bibliographic record
Abstract
Purpose: Patients with Head & Neck cancer (HNCa) undergoing chemoradiotherapy and/or surgery are at high risk for severe weight loss, dehydration, malnutrition, treatment interruptions and hospitalization. The use of PEG in this population offers a safe, effective method of delivering enteral nutrition to compensate for the decline in oral intake. In the past, patients were admitted to hospital for PEG insertion and education when effects of the cancer treatment caused significant dysphagia, mucositis and reduced oral intake. We are reporting initial results of an innovative program for HNCa patients during which out patient PEG is established prior to the start of chemo-radiation. Follow up and education regarding the care and use of the tube are provided on an outpatient basis. Methods: HNCa patients were selected to have a PEG established prior to chemo-radiation based on individual MD practice. All patients received nutrition counselling and education by a registered dietitian prior to treatment. Weight loss, treatment interruptions and hospitalizations were compared in patients who had vs didn't have a pre-treatment PEG. Results: 31 patients received PEG and enteral feeding as an outpatient procedure and were compared to a group of 20 similar patients who did not receive a PEG. In the PEG group, average weight loss following treatment was 6.8% compared to 11.0% in the non PEG group. 100% of the PEG group completed treatment without interruption or hospitalization for malnutrition/dehydration, compared to 29% of the non-PEG patients who required iv-hydration or hospital admission for nutrition support. PEG complications were abdominal pain requiring hospitalization (2), infection (5). Conclusions: Patients with PEG received more of their prescribed nutrition and fluids, lost less weight, and had fewer treatment interruptions and hospital admissions than non-PEG patients. An average 3–5 day hospital admission for in-patient PEG placement is eliminated saving health care costs. PEG insertion in ambulatory HNCa patients prio to chemo-radiation is safe, well tolerated, cost effective and improves clinical outcome. Our experience supports PEG tube insertion in ambulatory HnCa patients prior to treatment.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".