Overweight, central obesity, and cardiometabolic risk factors in pediatric liver transplantation
Bibliographic record
Abstract
UNLABELLED: PTMS describes the presence of ≥3 cardiometabolic risk factors that include obesity, hypertension, dyslipidemia, and IR. The prevalence of the clustering of ≥3 cardiometabolic risk factors or central obesity has not been studied in pediatric LT recipients. Single-center, cross-sectional study. INCLUSION CRITERIA: LT recipients 2-18 yr-old, at least one yr post-LT. EXCLUSION CRITERIA: recipients of liver retransplants or multivisceral transplants. Eighty-seven patients were identified. Median age was 9.8 yr (range 2-18), median time since LT was 6.9 yr (range 1-17). The most common indication for LT was biliary atresia (56%), and the most frequently used immunosuppressant was tacrolimus (80%). The prevalence of overweight and obesity was 21% and 5%, respectively. Central obesity affected 14%, hypertension 44%, IR 27%, low HDL 20%, and hypertriglyceridemia 39% of patients. The prevalence of ≥3 cardiometabolic risk factors was 19%. Fifty percent of the overweight/obese patients had ≥3 risk factors. Time since transplant, immunosuppression and renal function were not different between those with <3 or ≥3 risk factors. Clustering of cardiometabolic risk factors is prevalent in pediatric LT recipients, suggesting an increased risk of future CV events.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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 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".