Patient‐reported outcome measures within pediatric solid organ transplantation: A systematic review
Bibliographic record
Abstract
Subjective evaluation of medical care and disease outcomes from patients' perspectives has become increasingly important. Patient-reported outcome measures (PROMs) play a prominent role in engaging patients, capturing their experiences and improving patient care. This systematic review sought to identify PROMs that are used in the field of pediatric solid organ transplantation, with the aim to inform the implementation of PROMs into clinical practice for this population. A systematic review of English language, peer-reviewed articles was performed on key health science databases to identify publications using PROMs in pediatric solid organ transplantation. The search yielded 3670 articles, with a final data set of 62 articles that included 47 different PROMs. The three most frequently used PROMs included the following: (a) PedsQL™ Generic Core Scales (n = 25); (b) Children's Depression Inventory (n = 6); and (c) Child Health Questionnaire (n = 6). Of the 47 PROMs, 42 were generic and five were disease-specific; only six PROMS had a documented psychometric evaluation within a pediatric solid organ transplant population. This review outlines the attributes of the instruments (eg, domains captured), as well as the psychometric properties of those evaluated. PROMs are increasingly used in the field of pediatric transplantation; however, there are limited details in the current literature about their conceptual underpinnings and psychometric properties. This review highlights the need for additional psychometric evaluation of identified measures to establish the necessary foundation to inform the implementation of PROMs into clinical care for pediatric solid organ transplant patients.
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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 | 0.018 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.007 | 0.011 |
| 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".