Bibliographic record
Abstract
Background and Objective(s): Many children with cerebral palsy (CP) experience difficulty with gait, which can significantly impact the child's health, participation in daily activities, and quality of life (QOL).3D gait analysis is used to evaluate the gait pattern of children with CP.Kinematic data is summarized using the Gait Profile Score (GPS), which provides an overall score of gait quality (GPS) and values for nine different kinematic domains (Gait Variable Score [GVS]).The aims of this study are to determine the correlation between GPS scores and parent reported QOL measures and whether a specific GVS value has a greater effect on the QOL of children with CP. Study Design: Retrospective review.Study Participants & Setting: 112 patients with CP who underwent 3D gait analysis at a large tertiary-care pediatric hospital were included in this retrospective review.The average age was 10.5±4.8 (range 3-26) years.The impairment distribution of the cohort was as follows: 27.7% hemiplegia, 50.9% diplegia, 7.1% triplegia, and 14.3% quadriplegia.39.3% were classified as GMFCS level I, 28.6% GMFCS level II, and 32.1% GMFCS level III.Materials/Methods: Demographic data, GPS and GVS values, and Pediatric Outcomes Data Collection Instrument (PODCI) and Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) scores were evaluated.Overall GPS and GVS scores were analyzed for all patients.Pearson's correlations were used to compare continuous variables.Mann-Whitney U and Kruskal-Wallis tests were used to compare scores between groups.Results: There was a statistically significant difference in scores between GMFCS levels for multiple PODCI and CPCHILD domains and GPS values (p<0.001).There was a high correlation between GPS and PODCI Transfers and Basic Mobility (r=-0.547).Pelvic tilt, hip flexion/extension, and knee flexion/extension GVS values were moderately or highly correlated to PODCI Transfers and Basic Mobility, Sports and Physical Functioning, and Global Functioning domains and the CPCHILD Positioning, Transferring, and Mobility domain.Conclusions/Significance: Sagittal plane kinematics of hip flexion/extension, knee flexion/extension, and pelvic tilt GVS values have the greatest contribution to worse QOL scores on the PODCI and CPCHILD.The domains that are most impacted are those that reflect the child's ability to ambulate, participate in activities in their environment, and complete activities of daily living.Providers can use the information gained from this study to help focus their intervention strategies by targeting muscles that can help improve hip flexion/extension, knee flexion/extension, and pelvic tilt during the gait cycle.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.722 | 0.539 |
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".