Health-Related Quality of Life Assessments by Children and Adolescents with Sickle Cell Disease and Their Parents in Portugal
Bibliographic record
Abstract
Health-Related Quality of Life (HRQL) can be used to measure the impact of Sickle Cell Disease (SCD) on the child and their family and is generally reduced. No research has yet measured HRQL in Portuguese pediatric SCD patients. OBJECTIVES: (1) Describe and compare HRQL of children with SCD reported by them and their parents; (2) Compare with a pediatric population with no SCD; (3) Find predictive factors of HRQL in SCD children. METHODS: 4.0 Generic Scales. Summary scores for overall HRQL and subscale scores for physical, emotional, social and school functioning were compared within groups (children-parents) and with the control group. Clinical and socio-demographic variables were analyzed to find predictive factors of HRQL in pediatric SCD patients. RESULTS: Children with SCD and their parents had significantly lower overall and all subdomains of HRQL, compared with the control group. Children with SCD also rated lower when compared with their parents (only significant for social functioning), with low to moderate correlations. Children and parent reports declined with increasing age. Higher pain frequency was associated with worse total and psychosocial domains of HRQL. The number of hospitalizations was a predictor of worse school score, and female gender was a predictor of worse emotional score. CONCLUSIONS: SCD significantly affects children's HRQL. Parents can provide a good proxy report, although both evaluations are beneficial. Disease status, like number of hospitalizations and frequency of pain, influences HRQL. Interventions in SCD should consider improvements in HRQL as an important outcome.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".