Development of a set of core outcome measures for ambulant children with cerebral palsy after lower limb orthopaedic surgery
Bibliographic record
Abstract
AIM: To develop consensus on a core set of standardized outcome measures to be applied to each domain of the previously developed core outcome set for lower limb orthopaedic surgery for ambulant children with cerebral palsy (CP). METHOD: This work consisted of the following three steps: (1) a scoping review of the literature to identify previously used outcome measures to assess lower limb orthopaedic surgery of ambulant children with CP; (2) searching the COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) and PubMed databases to assess the quality of the psychometric properties of outcome measures and feasibility criteria; and (3) a consensus meeting with seven healthcare professionals with expertise in CP research and in the assessment of outcome measure psychometric properties was held in September 2021. Consensus on the outcome measures core set was developed through presentation of the evidence and whole-group discussions. RESULTS: A combination of clinician-driven and patient-reported outcome measures was considered the most appropriate way to assess the outcome of orthopaedic surgical interventions. Agreement was reached on seven core outcome measures: three-dimensional gait analysis, Edinburgh Visual Gait Scale, Gross Motor Function Measure, Gait Outcome Assessment List, Gillette Functional Assessment Questionnaire, Patient-Reported Outcome Measure Instrument System (pain interference, and fatigue), and Cerebral Palsy Quality of Life for Children questionnaire. INTERPRETATION: This study recommends a set of core outcome measures for use in research on lower limb orthopaedic surgery for ambulant children with CP. Consistent use of this core set would enhance validity and comparability of future research.
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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 | 0.176 | 0.274 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.017 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".