Childhood Obesity and Outcomes after Bone Marrow Transplantation for Patients with Severe Aplastic Anemia
Bibliographic record
Abstract
The prevalence of obesity in the pediatric population has increased in the last 2 decades and represents a serious health concern, with potential impact on outcomes of hematopoietic cell transplantation (HCT). We studied the effect of weight by age-adjusted body mass index (BMI) percentile in 1,281 pediatric patients (age 2-19 years) with severe aplastic anemia who underwent HCT between 1990 and 2005. The study population was divided into 5 weight groups-underweight, risk of underweight, normal BMI range, risk of overweight, and overweight-according to age-adjusted BMI percentiles. Cox proportional hazards regression models for survival and acute graft-versus-host disease (aGVHD), performed using weight groups as the main effect and the normal BMI range (26th-75th percentile) as the baseline comparison, found higher mortality among overweight children (>95th percentile adjusted for age). Weight at transplantation did not increase the adjusted risk of grade III-IV aGVHD. The 1-year and 2-year overall survival rates were 60% and 59% for overweight children, compared with >70% in children with lower BMI at both time points (P < .001). Other significant factors associated with survival included race and region, donor type, conditioning regimens in related donor transplants, performance score, and year of transplantation. In conclusion, overweight children with aplastic anemia have worse outcomes after HCT. The impact of obesity on survival outcomes in children should be discussed during pretransplantation counseling.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".