Incidence and Risk Factors of Obesity in Childhood Solid-Organ Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Obesity is a significant public health concern; however, the incidence post solid-organ transplantation is not well reported. METHODS: This study determined the incidence and risk factors of obesity among pediatric solid-organ transplant recipients (heart, lung, liver, kidney, multiorgan) at The Hospital for Sick Children (2002-2011), excluding prevalent obesity. Follow-up occurred from transplantation until development of obesity, last follow-up, or end of study. Incidence of obesity was determined overall, by baseline body mass index, and organ group. Risk factors were assessed using Cox proportional-hazards regression. RESULTS: Among 410 (55% male) children, median transplant age was 8.9 (interquartile range [IQR]: 1.0-14.5) years. Median follow-up time was 3.6 (IQR: 1.5-6.4) years. Incidence of obesity was 65.2 (95% confidence interval [CI]: 52.7-80.4) per 1000 person-years. Overweight recipients had a higher incidence, 190.4 (95% CI: 114.8-315.8) per 1000 person-years, than nonoverweight recipients, 56.1 (95% CI: 44.3-71.1). Cumulative incidence of obesity 5-years posttransplant was 24.1%. Kidney relative to heart recipients had the highest risk (3.13 adjusted hazard ratio [aHR]; 95% CI: 1.53-6.40) for obesity. Lung and liver recipients had similar rates to heart recipients. Those with higher baseline body mass index (z-score; 1.72 aHR; 95% CI: 1.39-2.14), overweight status (2.63 HR; 95% CI: 1.71-4.04), and younger transplant age (y; 1.18 aHR; 95% CI: 1.12-1.25) were at highest risk of obesity. Higher cumulative steroid dosage (per 10 mg/kg) was associated with increased risk of obesity after adjustment. CONCLUSIONS: Among all transplanted children at The Hospital for Sick Children, 25% developed obesity within 5-years posttransplant. Kidney recipients, younger children, those overweight at transplant, and those with higher cumulative steroid use (per 10 mg/kg) were at greatest risk. Early screening and intervention for obesity are important preventative strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".