Assessment of Nutritional Status and Malnutrition Risk at Diagnosis and Over a 6-Month Treatment Period in Pediatric Oncology Patients With Hematologic Malignancies and Solid Tumors
Bibliographic record
Abstract
In total, 74 pediatric oncology patients with hematologic malignancies (n=56) or solid tumors (n=18) and a median age of 78.5 months were included in this prospective study. The aims were to assess malnutrition risks and nutritional status over a 6-month treatment period measured at regular intervals. The rate of patients with high risk for malnutrition at diagnosis was 28.4% by Screening Tool for Risk of Impaired Nutritional Status and Growth tool and 36.5% by Pediatric Yorkhill Malnutrition Score. Body mass index (BMI) z-scores at diagnosis showed 12.3% undernutrition (<-2 SD) and 6.8% overnutrition (>2 SD), which changed to 6.7% and 11.1% at the sixth month, respectively. Malnutrition (BMI<5th age percentile) was detected in 13.7% at diagnosis. Despite an initial deterioration noted in BMI, BMI for age percentile, and z-scores at month 1 in all malignancy subgroups (at month 3 for acute lymphoblastic leukemia), the scores improved later on. There was an increase in weight from baseline in 88.2% of patients over 6 months. This study revealed a decrease in the prevalence of undernutrition and malnutrition over a 6-month treatment period with improved anthropometrics despite an initial deterioration in all malignancy subgroups and even in patients with high risk for malnutrition at baseline screening. Solid tumors and acute lymphoblastic leukemia seem to be associated with higher likelihood of undernutrition and overnutrition, respectively, during 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".