Anthropometry in Long-Term Survivors of Acute Lymphoblastic Leukemia in Childhood and Adolescence
Bibliographic record
Abstract
PURPOSE: Body mass index (BMI) is an inadequate measure of nutritional status in children and adolescents with cancer as it does not distinguish muscle from adipose tissue. However, arm anthropometry offers simple assessments of fat mass and lean body mass; especially valuable in low- and middle-income countries where the great majority of young people with cancer live and access to sophisticated expensive measures of body composition is markedly limited. METHODS: The nutritional status of 75 long-term survivors of acute lymphoblastic leukemia was assessed by arm anthropometry, in addition to BMI, in a cross-sectional cohort study. Normal ranges for triceps skin fold thickness (TSFT, a surrogate for fat mass) and mid-upper arm circumference (MUAC, a surrogate for lean body mass) were between the 15th and 85th percentiles for age and sex. Overweight/obesity was classified as a TSFT >85th percentile and sarcopenia as an MUAC <15th percentile. Height normalized indices for TSFT and MUAC were also calculated. RESULTS: Overweight/obesity was identified in 1/3 of subjects by a BMI >25 and by TSFT; and 20% of the subjects had a TSFT >95th percentile. Only two subjects were sarcopenic. None met the combined criteria for sarcopenic obesity. TSFT and MUAC/height indices did not add sensitivity to identification of sarcopenia or obesity. CONCLUSIONS: TSFT is a useful measure of overweight/obesity in this population, but MUAC does not identify a notable proportion with sarcopenia. Further resolution may be provided by more sophisticated measures of body composition.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".