Cardiometabolic Health After Pediatric Cancer Treatment: Adolescents Are More Affected than Children
Bibliographic record
Abstract
This cross-sectional study aimed at comparing the cardiometabolic (CM) health of children and adolescents and identifying factors associated with CM complications shortly after cancer treatment. Cancer-related characteristics, blood pressure (BP), anthropometry, and biochemical parameters were collected in 80 patients (56.3% female, mean age: 11.8 years; range: 4.5 − 21.0) a mean of 1.4 years following therapy completion. Compared to children, adolescents had higher mean z-score of insulin (–0.47 vs. 0.20; P = 0.01), HOMA-IR (–0.40 vs. 0.25; P = 0.02), waist-to-height ratio (0.36 vs. 0.84; P = 0.01), subscapular skinfold thickness (–0.19 vs. 0.47; P = 0.02), total body fat (–1.43 vs. 0.26; P < 0.01), and lower mean z-score of HDL-C (0.07 vs. –0.53; P < 0.01). Adolescents were more likely to have high BP (42% vs. 15%; P < 0.01), dyslipidemia (64% vs. 15%; P < 0.001), and cumulating ≥ 2 CM complications (42% vs. 2%; P < 0.001) than children. Adiposity indices (z-scores) were associated with high BP [odds ratio (OR) ranging from 2.11 to 4.09] and dyslipidemia (OR ranging from 2.06 to 4.34). These results suggest that adolescents have a worse CM profile than children shortly after therapy and that adiposity parameters are associated with CM complications, highliting the importance to develop intervention strategies targeting this population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".