Investigating the impact of pain, age, Gross Motor Function Classification System, and sex on health‐related quality of life in children with cerebral palsy
Bibliographic record
Abstract
AIM: To explore whether health-related quality of life (HRQOL) can be predicted by pain, age, Gross Motor Function Classification System (GMFCS) level, and sex in children with cerebral palsy (CP) and whether different pain etiologies have varying effects on HRQOL. METHODS: Children with CP aged 3 to 19 years and their caregivers were consecutively recruited. Caregivers reported their child's pain (Health Utilities Index 3 [HUI3] pain subset) and HRQOL (DISABKIDS questionnaires). Physicians identified pain etiologies. A multiple linear regression model determined whether pain, GMFCS level, sex, and age predicted HRQOL. An ANOVA evaluated the effects of pain etiologies on HRQOL. RESULTS: Three hundred and forty-four participants were approached and 87% (n=300) participated. Sufficient data were available on 248 (72% of total sample). Sixty-six participants (27%) formed the pain group with HUI3 pain scores of at least 3. The presence of pain and increasing age significantly negatively predicted HRQOL (p<0.001, R(2) =0.141), while GMFCS and sex did not. Musculoskeletal deformity (24%) and hypertonia (18%) were the most frequent pain causes. HRQOL statistically differed depending on the pain etiology (p=0.028) with musculoskeletal deformity showing the lowest mean HRQOL. INTERPRETATION: The presence of pain and increasing age negatively predict HRQOL in CP. musculoskeletal deformity has the greatest negative impact on HRQOL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".