A core outcome set for multimorbidity risk in individuals with cerebral palsy
Bibliographic record
Abstract
AIM: To: (1) investigate the importance of outcome measurement instruments (OMIs) within a core outcome set (COS) for multimorbidity (at least two chronic health conditions) risk in individuals with cerebral palsy (CP); (2) investigate the feasibility of OMIs within the COS in international clinical research settings in adolescents and adults with CP; and (3) describe the associations between the COS data and Gross Motor Function Classification System (GMFCS) levels. METHOD: Eighty-three individuals with CP completed a survey on health outcomes: physical behaviour, nutrition, sleep, endurance, body composition, blood pressure, blood lipids, and glucose. A cross-sectional study assessed the feasibility of the COS in 67 adolescents and adults with CP (mean age 30y, SD 15y 1mo, min-max: 14-68y, 52.2% male) at four centres. Prevalence of multimorbidity risk and associations with GMFCS levels are described. RESULTS: Most participants rated physical behaviour, nutrition, sleep, and endurance as very important. Body composition, blood pressure, nutrition, and sleep were highly feasible since data were collected in 88% or more participants who consented to having the assessments. Physical behaviour, cardiorespiratory endurance, and blood draws were collected in less than 60% of participants. Total time sedentary (ρ=0.53, p<0.01) and endurance (ρ=-0.46, p<0.01) were significantly associated with GMFCS level. INTERPRETATION: The COS identified that most participants had poor sleep quality and endurance, did not have healthy diets, and showed increased sedentary behaviour. Individuals with CP valued these outcomes as most important, suggesting a need to assess these modifiable behaviours in this population. Objective measures of physical behaviour and cardiorespiratory endurance in the COS required additional personnel, time, and participant burden. We recommend that healthcare providers should perform a simpler first screen using questionnaire-based assessments and then focus the use of the remainder of the COS if required for the patient.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".