Changes in the cardiovascular risk profile in children approaching kidney replacement therapy
Bibliographic record
Abstract
Background Despite significant cardiovascular (CV) morbidity in children on dialysis and after kidney transplantation, data on the evolution of CV damage in children with chronic kidney disease (CKD) approaching kidney replacement therapy (KRT) is unknown. Methods The burden, progression, and predictors of CV damage before KRT onset were explored in two prospective multicenter cohorts from Europe and Canada: Cardiovascular Comorbidity in Children with CKD (4C) and Haemodiafiltration, Heart and Height (3H) studies, conducted from 2009–19 and 2013–16, respectively. CV damage and risk factors were evaluated (i) cross sectionally at KRT-start (n = 248), and (ii) longitudinally over the 2-years preceding KRT start (n = 157; 331 patient-visits). Longitudinal analyses with mixed-effects models estimated associations of modifiable CV risk factors with change in carotid intima-media thickness (cIMT) standard deviation score (SDS), pulse wave velocity (PWV-SDS), left ventricular (LV) mass and systolic dysfunction. Findings 248 patients, age 14.3 (12.2, 16.2) years were evaluated at median 35 (28–114) days before KRT start. Elevated cIMT-SDS and PWV-SDS were present in 43% and 25%, and LV hypertrophy and systolic dysfunction in 49% and 33%. Aortic stiffness and LV hypertrophy significantly increased, especially in the year before KRT start (adjusted odds ratio, OR 0.33, P = 0.002 and OR 0.54, P = 0.01, respectively). 79% of children had >3 modifiable CV risk factors at KRT onset. Diastolic BP and BMI were strongly associated with a linear increase in all CV measures. After controlling for CV risk factors, the time to KRT onset no longer predicted the burden of CV damage. Interpretation This comprehensive CV evaluation shows the progressive accrual of modifiable risk factors and a high burden of CV damage in the years preceding KRT onset. CV damage in the pre-KRT period is preventable. Funding Supported by EU4Health Programme (101085068) and Kidney Research UK (RP39/2013).
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".