Correlation between the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Scores and the Stability Metrics in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
Aims:The aim of the present study was to assess the correlation between the stability metrics related to the center of pressure excursion measurements and the WOMAC questionnaire scores.Method and Materials: Fourteen patients with moderate knee osteoarthritis and fourteen healthy age-matched individuals were participated to stand with open and closed eyes, and on firm and rocking support on a force platform.The WOMAC questionnaire was obtained from the patient group.One-way ANOVA was utilized to determine the effects of knee osteoarthritis, vision, and support on postural stability metrics.Spearman's correlation was also used to indicate the correlation between the stability metrics and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) sub scores.Findings: The anterior-posterior variability of the center of pressure was significantly greater in patients (2.7 mm, p=.003).Elimination of the visual feedback and the rocking support affected the sway area and the AP (p<.001), and the ML variability (p<.024).The pain subscore of the WOMAC questionnaire was negatively and strongly correlated to the AP total mean velocity (open-eyes: r=-.466, closed-eyes: r=-.779).The pain was positively and strongly correlated to the AP variability (open-eyes: r=.796, closed-eyes: r=.744).Patients with knee osteoarthritis showed more postural instabilities.Conclusion: The instability in the anterior-posterior was more eminent than in the lateral direction.The pain was the most role-playing factor in the destabilization of the posture among the patients with knee osteoarthritis but may be disregarded in physically-difficult conditions of standing.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".