Revalidation of Proactive Gastrostomy Tube Placement Guidelines for Head and Neck Cancer Patients Receiving Helical Intensity-Modulated Radiotherapy
Bibliographic record
Abstract
The Royal Brisbane and Women's Hospital (RBWH) Swallowing and Nutrition Management Guidelines for Patients with Head and Neck Cancer were developed to enable evidence-based decision-making by the Head and Neck Multidisciplinary Team (H&N MDT) regarding enteral nutrition support options. The purpose of this study was to revalidate these guidelines in a cohort of patients receiving helical intensity-modulated radiotherapy (H-IMRT) compared to a historical cohort who received primarily 3D-conformal radiotherapy. Eligible patients attending the RBWH H&N MDT between 2013 and 2014 (n = 315) were assessed by the guidelines, with high-risk patients being recommended proactive gastrostomy tube placement. Data were collected on guideline adherence, gastrostomy tube insertions, the duration of enteral tube use and weight change. Sensitivity, specificity and positive predictive and negative predictive values were calculated and compared with the historical cohort. Overall guideline adherence was 84%, with 60% and 96% adherence to the high-risk and low-risk pathways, respectively. Seventy patients underwent proactive gastrostomy tube placement (n = 62 high-risk; n = 8 low-risk). Validation outcomes were sensitivity 73% (compared to 72%) and specificity 86% (compared to 96%). The guidelines yielded a high sensitivity and specificity, remaining valid in a cohort of patients treated with H-IMRT. Further studies are recommended to improve the sensitivity and understand the decrease in specificity in order to make ongoing guideline improvements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".