High depression rates among pediatric renal replacement therapy patients: A cross‐sectional study
Bibliographic record
Abstract
Depression is common in pediatric chronic kidney disease (CKD) patients. Depression is associated with inferior long-term outcomes. There is a paucity of studies that evaluate depression and possible associated factors in children and adolescents requiring renal replacement therapy (RRT). Cross-sectional study using Children`s Depression Inventory in a cohort from a large urban center. Forty-seven pediatric RRT patients (26 female, 12 peritoneal dialysis (PD), 17 hemodialysis (HD), 18 after successful kidney transplantation (KTX)) with a mean age at the time of assessment of 13.9 ± 2.3 years. Symptoms of depression were found in 30 (64%, 11KTX, 11HD, 8PD) patients. We found no association with age, sex, renal function, dialysis adequacy markers, anemia, electrolytes, socioeconomical status, IQ, educational status of the child including school attendance and distance from the house to the hospital among HD patients. Significant differences only applied for age at diagnosis of CKD, RRT vintage and deceased donor for KTX. The group with depression had a higher age at diagnosis of CKD and less time on RRT than the group without depression. There was also a high rate of depression in KTX patients. In this cohort, depression was a common comorbidity of RRT in children and adolescents with RRT and also for KTX patients, even though biomarkers of kidney function and time for RRT are much improved.
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 | 0.001 |
| 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 | 0.001 | 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".