Stability of Serial Range-of-Motion Measurements of the Lower Extremities in Children With Cerebral Palsy: Can We Do Better?
Bibliographic record
Abstract
BACKGROUND: Serial joint range-of-motion (ROM) measurements are an important component of assessments for children with cerebral palsy. Most research has studied ROM stability using group data. Examination of longitudinal intraindividual measures may provide more clinically relevant information about measurement variability. OBJECTIVE: The aim of this study was to examine the stability of intraindividual longitudinal measurements of hip abduction (ABD), popliteal angle (POP), and ankle dorsiflexion (ADF) ROM measures of children with cerebral palsy. DESIGN: Secondary data analyses were performed. METHODS: The stability patterns of individual serial measurements of ABD, POP, and ADF from 85 children (mean age=3.8 years, SD=1.4) collected at baseline (T1), 3 months (T2), 6 months (T3), and 9 months (T4) were examined using T1 as the anchor and bandwidths of ±15 degrees (ABD and POP) and ±10 degrees (ADF) as acceptable variability. Frequencies of stability categories (0°-5°, 5.1°-10°, 10.1°-15°, and >15°) were calculated. Patterns of stability across the 4 time periods also were examined. Group means (T1-T4) were compared using repeated-measures analysis of variance. RESULTS: No significant differences in group means were found except for ABD. Stability patterns revealed that 43.3% to 69.5% of joint measurements were stable with T1 measurements across all 3 subsequent measurements. Stability category frequencies showed that many measurements (ABD=17%, POP=29.9%, and ADF=37.1%) went outside the variability bandwidths even though 39% or more of joint measurements had a change of 5 degrees or less over time. LIMITATIONS: Measurement error and true measurement variability cannot be disentangled. The results cannot be extrapolated to other joint ROMs. CONCLUSIONS: Individual ROM serial measurement exhibits more variability than group data. Range-of-motion data must be interpreted with caution clinically and efforts made to ensure standardization of data collection methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".