Evidence-informed clinical perspectives on postural management for hip health in children and adults with non-ambulant cerebral palsy
Bibliographic record
Abstract
Postural management is a multi-disciplinary approach incorporating a comprehensive schedule of daily and night-time positions, equipment and physical activity to help maintain or improve body structures and function and increase activity and participation. Postural management may play a role in preventing contracture, deformity, pain, and asymmetry. This article provides an overview of the evidence supporting use of postural management to positively influence hip health in individuals with cerebral palsy, functioning as Gross Motor Classification System (GMFCS) levels IV or V. Sitting or lying without changing position for more than 8 hours, unsupported supine lying and asymmetrical or windswept postures are associated with pain and hip subluxation/dislocation. Although high-quality experimental research is still limited by many factors, there is limited evidence of harm, and most individuals at GMFCS IV or V require positioning supports to enable participation and function and ease caregiving. Clinical recommendations combining research and clinical opinion support the early use of comfortable positioning routines and/or equipment to reduce time spent in sustained asymmetrical or potentially harmful sitting and lying positions. Supported standing, active weightbearing and stepping are recommended to promote active movement and position change when possible, depending on individual, family and caregiver routines and preferences.
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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 | 0.017 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".