Validation of Patient-Reported Outcome Measure in Pediatric CKD (PRO-Kid)
Bibliographic record
Abstract
Key Points PRO-Kid is a patient-reported outcome measure of the frequency and burden of symptoms. Higher PRO-Kid scores are associated with lower Pediatric Quality of Life Inventory scores. Background Measuring the burden of symptoms that matter most to children and adolescents with CKD is essential for optimizing patient-centered care. We developed a novel CKD-specific patient-reported outcome measure (PRO-Kid) to assess both frequency and impact of symptoms in children. In this study, we further assessed the validity and internal consistency of PRO-Kid. Methods In this multicenter study, children age 8–18 years with stages 3–5 CKD, including those on dialysis, were recruited from five pediatric centers. Children completed the 14-item PRO-Kid questionnaire and the validated Pediatric Quality of Life Inventory (PedsQL 4.0). We explored the dimensionality of the PRO-kid scale using exploratory and confirmatory factor analysis, to either establish that it is a unidimensional construct or identify evidence of subfactors. We then assessed internal consistency (Cronbach alpha) and construct validity (Pearson correlations). Results In total, 100 children were included. The median eGFR was 27.4 ml/min per 1.73 m 2 (7.43–63.4), and 26 children (26%) were on dialysis. Both the PRO-Kid frequency and the impact scales were unidimensional. Cronbach alpha was high for both the PRO-Kid frequency and impact scales, 0.83 (95% confidence interval [CI], 0.78 to 0.88) and 0.84 (95% CI, 0.80 to 0.89), respectively, showing strong internal consistency. Pearson correlations between PRO-Kid and PedsQL scores were also strong: −0.78 (95% CI, −0.85 to −0.70) for the frequency score and −0.69 (95% CI, −0.78 to −0.56) for the impact score, reflecting the association between poorer quality of life and higher symptom burden. Conclusions PRO-Kid is a novel patient-reported symptom burden tool for children age 8–18 years with CKD that correlates strongly in the expected direction with PedsQL, supporting its validity. Future work will evaluate changes in PRO-Kid score with progression of CKD and implementation of the tool into clinical care.
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 | 0.023 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".