Children with Chronic Kidney Disease Are More Overweight in Canada than in Germany
Bibliographic record
Abstract
Objective: Obesity is a potentially modifiable and independent risk factor for chronic kidney disease (CKD) and end stage renal disease (ESRD). We hypothesized that Canadian children are at greater risk for ESRD because of the higher prevalence of overweight. We compared body composition of comparable cohorts of paediatric patients with CKD between Canada and Germany to assess the obesity-related risk for CKD in both countries. Patients: 127 German and 412 Canadian children with CKD who participated in the same study in 1999 were analyzed retrospectively. Measurements and Results: Body composition was determined as a body mass index (BMI) z-score using American reference intervals (NHANES Ⅲ database) and Box-Cox transformation. No significant differences were found in age, gender and underlying diagnosis. Canadian children had a median BMI z-score of +0.4030 that was significantly greater than the median BMI z-score of the German children (+0.1096, p=0.0380, Mann Whitney). The median BMI z-scores of the Canadian children were also found to be statistically greater than those of the American reference intervals (p＜0.0001, Wilcoxon signed rank test). Conclusion: Canadian children with CKD exhibit higher BMI s-scores when compared to a similar cohort of German children with CKD. As obesity is a major risk factor for progression to end stage renal disease, more attention needs to be paid to the body composition of Canadian children with CKD.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".