Influence of hip luxation on health related quality of life (HRQL) in children with cerebral palsy evaluated by the CP-CHILD questionaire – preliminary results
Bibliographic record
Abstract
Introduction: Lateralisation of the hip in children with cerebral palsy (CP) depends on motor impairment and varies from moderate impairment to severe pain. Less is known from children with CP and hip lateralisation and its influence on health related quality of life (HRQL). Thea im of the present study was to evaluate the influence of hip lateralisation on HRQL in children with CP via the Caregiver Priorities and Child Health Index of Life with Disabilities (CP-CHILD) questionaire. Methods: We investigated 35 patients (mean age: 11.71±5.1; W: n=18) with bilateral cerebral palsy and Gross motor function classification system (GMFCS) Level III – V. Caregivers were asked to rate the quality of life via the CP-CHILD questionaire. Hip lateralisation was measured by the Migration index (MI) after Reimers. According to the „Hüftampel„ (www.cp-netz.de), patients were divided into a group with a high (MI>40%), medium (MI 25% bis ≤40%) and low (MI <25%) risk to develop progressive hip lateralisation. Two-way analysis of variance (ANOVA) with GMFCS and MI as factors was performed. Results: 57,1% of patients with GMFCS Level III had a MI >40%, 13,3% with GMFCS Level IV and 30,8% with GMFCS Level V. Two-way ANOVA revealed a significant influence of GMFCS and MI on Total score of the CP-CHILD questionaire but not for the interaction of both (GMFCS: p=0,003 [F: 7,361; 2]; MI: p=0,008 [F: 5,807; 2]; MI*GMFCS: p=0,989). Conclusion: We demonstrated – beside the GMFCS – a significant influence of hip lateralisation on HRQL. Our results support the need of an appropriate prevention and therapy of hip lateralisation in children with CP.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".