Stiffness, Pain, and Hip Muscle Strength Are Factors Associated With Self-reported Physical Disability in Hip Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Physical disability (PD) is common among patients with osteoarthritis (OA) of the hip. Exercise therapy is proposed to be a potential intervention to reduce PD. However, the optimal targets of an exercise program are not known. PURPOSE: The aim of the present study was to identify factors that explain the level of self-reported PD in patients with hip OA. Knowledge of these factors will help develop specific and effective exercise programs. METHODS: Data from 149 patients with hip OA (85 men and 64 women) were analyzed. Self-reported PD was quantified using the physical function subscale of the Western Ontario and McMaster index. A stepwise regression analysis was conducted to identify significant factors associated with self-reported PD. RESULTS: Stiffness, pain, and hip muscle strength were found to be significant factors related to the level of self-reported PD in hip OA. These factors explained 59% (r adjusted = 0.59) of the variance. Body mass index, gender, age, and passive internal hip rotation and flexion range of motion explained only minor parts of the dependent variable self-reported PD. DISCUSSION AND CONCLUSION: Stiffness, pain, and hip muscle strength are associated with self-reported PD in hip OA. It is imperative that exercise treatments for hip OA include strategies to modify these factors. Further research should evaluate their role in preventing hip OA.
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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 | 0.001 | 0.004 |
| 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) | 0.002 | 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".