Health‐related quality of life for pediatric patients with end‐stage kidney disease: A systematic review and meta‐analysis of the Pediatric Quality of Life Inventory (PedsQL)
Bibliographic record
Abstract
INTRODUCTION: Health-related quality of life (HRQoL) studies demonstrate the impact of end-stage renal disease (ESRD) on the physical and psychosocial development of children. While several instruments are used to measure HRQoL, few have standardized domains specific to pediatric ESRD. This review examines current evidence on self and proxy-reported HRQoL among pediatric patients with ESRD, based on the Pediatric Quality of Life Inventory (PedsQL) questionnaires. METHODS: Following PRISMA guidelines, we conducted a systematic review and meta-analysis on HRQoL using the PedsQL 4.0 Generic Core Scale (GCS) and the PedsQL 3.0 ESRD Module among 5- to 18-year-old patients. We queried PubMed, Embase, Web of Science, CINAHL, and Cochrane databases. Retrospective, case-controlled, and cross-sectional studies using PedsQL were included. FINDINGS: Of 435 identified studies, 14 met inclusion criteria administered in several countries. Meta-analysis demonstrated a significantly higher total HRQoL for healthy patients over those with ESRD (SMD:1.44 [95% CI: 0.78-2.09]) across all dimensional scores. In addition, kidney transplant patients reported a significantly higher HRQoL than those on dialysis (PedsQL GCS, SMD: 0.33 [95% CI: 0.14-0.53]) and (PedsQL ESRD, SMD: 0.65 [95% CI: 0.39-0.90]) concordant with parent-proxy reports. DISCUSSION: Patients with ESRD reported lower HRQoL in physical and psychosocial domains compared with healthy controls, while transplant and peritoneal dialysis patients reported better HRQoL than those on hemodialysis. This analysis demonstrates the need to identify dimensions of impaired functioning and produce congruent clinical interventions. Further research on the impact of individual comorbidities in HRQoL is necessary for developing comprehensive, integrated, and holistic treatment programs.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".