Standards of nutritional care in pediatric oncology: Results from a nationwide survey on the standards of practice in pediatric oncology. a Children's Oncology Group study
Bibliographic record
Abstract
BACKGROUND: The prevalence of malnutrition in children with cancer ranges between 8% and 60%. Malnutrition is strongly associated with the nature of treatment and increases an individual's risk of infection. Clinical studies have suggested that nutrition intervention may decrease toxicity and improve survival in the oncology population. In order to identify the standards of practice in the nutritional management of a child with cancer, we conducted an international survey in institutions that are part of the Children's Oncology Group (COG) consortium. PROCEDURE: Surveys were submitted to 233 participating COG institutions. We requested one member in three disciplines complete the survey: physician, registered dietitian, and nurse or nurse practitioner. The survey was returned to the nutrition sub-committee of COG. RESULTS: Fifty-four percent of institutions responded to the survey. We found no consistency in the provision of nutrition services. Assessment of nutritional status does not routinely occur and different indices are employed to indicate the nutrition status of a patient. Institutions rely upon different guidelines when categorizing malnutrition. When nutrition intervention is clinically indicated, a variety of approaches are employed. CONCLUSIONS: This survey did not find standardized nutrition protocols being employed in the pediatric oncology population. The effect of varied nutrition practices on the quality of life, toxicity, and outcome in children with cancer is unknown. Prior to the initiation of clinical trials, uniform guidelines need to be developed and validated. Future clinical trials need to investigate the most efficacious method of nutrition assessment and intervention and its effect on quality of life, toxicity, and survival in children 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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| 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) | 0.001 | 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".