Child and parental perspectives of multidimensional quality of life outcomes after kidney transplantation
Bibliographic record
Abstract
Anthony SJ, Hebert D, Todd L, Korus M, Langlois V, Pool R, Robinson LA, Williams A, Pollock-BarZiv SM. Child and parental perspectives of multidimensional quality of life outcomes after kidney transplantation.Pediatr Transplantation 2010:14:249–256. © 2009 John Wiley & Sons A/S. Abstract: Kidney transplantation is an optimal therapy for pediatric patients with end-stage kidney disease. This pilot study sought to examine multidimensional QOL outcomes after kidney transplant using VAQOL and General Health, the PedsQL 4.0, PedsQL End Stage Renal Disease Module, and Impact on Family Module. Sample included 12 adolescents aged 13–18 yr and their parent; three children aged eight to 12 yr and their parent; and six parents of children aged two to seven yr. All were 73 months post transplant. The median age at transplant was 9.3 yr and median time since transplant was 3.2 yr. VAQOL mean was 7.7/10 (child report) and 7.3/10 (parent report); the mean general health was 7.4/10. High levels of fatigue (≥5/10) were reported in 43%. PedsQL subscale mean values were lower than healthy reference scores. PedsQL Renal Module demonstrated great concern with physical appearance and physical symptoms (thirst and headaches), difficulty with peer and family interaction, and school disruption. Low scores on parental emotional function depict the negative impact of transplant on family functioning. Discordance exists between child and parental reports of QOL. Prospective studies are needed to explore multidimensional QOL to improve long-term outcomes after pediatric kidney transplant.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".