The Association Between Estimated Glomerular Filtration Rate and Left Ventricular Function in Children With Chronic Kidney Disease
Bibliographic record
Abstract
ABSTRACT Background Cardiovascular disease is the leading cause of morbidity and mortality in pediatric patients with chronic kidney disease (CKD). However, the kidney-heart relationship in this population remains poorly understood, particularly in the context of dialysis modality and duration. This study aims to investigate the associations between estimated glomerular filtration rate (eGFR), left ventricular ejection fraction (LVEF), left ventricular (LV) mass, and dialysis modality and duration in pediatric CKD patients. Methods This retrospective study included 16 pediatric CKD patients (median age 3.6 years; 31.3% female and 68.75% male), stratified by the presence of cardiac dysfunction (LVEF ≤ 50%). Clinical data, including eGFR, LVEF, LV mass, and dialysis history (hemodialysis or peritoneal dialysis), were collected. Independent T-tests, Wilcoxon Two-Sample tests, and Spearman’s correlations were performed to assess renal and cardiac function relationships. Multivariate regression models were employed to evaluate predictors of LVEF over time. Results Cardiac dysfunction was observed in 25% of the cohort, with significantly lower LVEF and fractional shortening compared to those without dysfunction. Patients with cardiac dysfunction were younger at CKD diagnosis (p < 0.0001), suggesting an earlier progression of renal and cardiac impairment. Following dialysis, eGFR significantly decreased in patients without cardiac dysfunction (p < 0.0001) but remained unchanged in those with dysfunction. Conversely, LVEF improved post-dialysis in patients with cardiac dysfunction (p = 0.0034) but remained stable in those with normal cardiac function. Prolonged dialysis duration was negatively correlated with eGFR (r = –0.31, p = 0.008) and LV mass (r = –0.26, p = 0.024). Hemodialysis duration was positively correlated with LVEF (r = 0.73, p < 0.001), suggesting potential cardiovascular benefits from prolonged hemodialysis treatment. Conclusions Pediatric CKD patients, particularly those with cardiac dysfunction, experience significant alterations in both renal and cardiac parameters, requiring tailored dialysis strategies in this population.
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 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 | 0.001 | 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".