Nutritional status at diagnosis among children with cancer referred to a nutritional service in Brazil
Bibliographic record
Abstract
INTRODUCTION: Children and adolescents with cancer are particularly vulnerable to malnutrition and require special attention on nutritional assessment. An adequate nutritional status during treatment is essential in reducing morbidity and mortality, being a modifiable risk factor for clinical outcomes. This study aims to determine the nutritional status of pediatric patients with cancer assessed by the nutrition team at diagnosis and evaluate its association with the overall survival. METHOD: This is a retrospective cross-sectional study of patients at the time of cancer diagnosis who had nutritional assessments when hospitalized or referred to the nutrition outpatient clinic. Nutritional status was classified by the mid-upper arm circumference (MUAC) and body mass index for age z-score (zBMI/A). The Cox regression analysis was used to determine the association between the nutritional status and overall survival, adjusting for gender, tumor group and age. RESULTS: The study included 366 patients. The prevalence of undernutrition varied from 8 to 23% and overweight, from 5 to 20%. The MUAC identified more children as undernourished than the zBMI/A in patients with solid and hematological tumors. There was no significant difference in the overall survival by malnutrition classified by the zBMI/A (p = 0.1507) or MUAC (p = 0.8135). When adjusted for gender, tumor group and age, the nutritional status classification by the zBMI/A (hazard ratio [HR], 1.27; 95% confidence interval [CI], 0.88-1.83; p = 0.209) and MUAC (HR, 0.94; 95% CI, 0.61-1.44; p = 0.773) did not impact overall survival. CONCLUSION: The nutritional status at diagnosis did not significantly impact the overall survival, which suggests there may have been a protective effect by successful nutritional intervention during the subsequent care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 teacher head, 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".