Prevalence of Cardiovascular Disease Risk Factors in Childhood Glomerular Diseases
Bibliographic record
Abstract
Background Cardiovascular disease is a major cause of morbidity and mortality in children with chronic kidney disease. We sought to determine the prevalence of cardiovascular risk factors in children with glomerular disease and to describe current practice patterns regarding risk factor identification and management. Methods and Results Seven-hundred sixty-one children aged 0 to 17 years with any of 4 biopsy-confirmed primary glomerular diseases (minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, and IgA nephropathy/vasculitis) were enrolled at a median of 16 months from glomerular disease diagnosis in the multicenter prospective Cure Glomerulonephropathy Network study. Prevalence of traditional (hypertension, hypercholesterolemia, and obesity) and novel (proteinuria, prematurity, and passive smoke exposure) cardiovascular risk factors were determined at enrollment and compared across glomerular disease subtypes. Frequency of screening for dyslipidemia and prescribing of lipid-lowering or antihypertensive medications were compared across glomerular disease subtype, steroid exposure, and remission status groups. Compared with the general population, all traditional risk factors were more frequent: among those screened, 21% had hypertension, 51% were overweight or obese, and 71% had dyslipidemia. Children who were not in remission at enrollment were more likely to have hypertension and hypercholesterolemia. Fourteen percent of hypertensive children were not receiving antihypertensives. Only 49% underwent screening for dyslipidemia and only 9% of those with confirmed dyslipidemia received lipid-lowering medications. Conclusions Children with primary glomerular diseases exhibit a high frequency of modifiable cardiovascular risk factors, particularly untreated dyslipidemia. Lipid panels should be routinely measured to better define the burden of dyslipidemia in this population. Current approaches to screening for and treating cardiovascular risk factors are not uniform, highlighting a need for evidence-based, disease-specific guidelines.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".