Correlation of Knee Osteoarthritis Patients' Characteristics and the Results of 30-Second Sit-to-Stand Test with Quality of Life
Bibliographic record
Abstract
Pain, joint stiffness, and difficulty performing activities like rising from sitting to standing are signs and symptoms of knee osteoarthritis (OA). These conditions are risk factors for limited mobility and lower quality of life. Knee OA is closely associated with age, women, obesity, and other characteristics. The study's objectives were to determine the correlation of knee OA patients' characteristics with functional mobility using the 30-second sit-to-stand test (30STS) and the correlation of functional mobility with quality of life using the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) Index. The research method was descriptive-analytic cross-sectional using medical records of 73 knee OA patients at the Medical Rehabilitation Clinic at Soreang Hospital, Muhammadiyah Hospital, Al Islam Hospital, Al-Ihsan Regional General Hospital West Java Province, Bandung, from March until August 2021. Patients' characteristics such as age (p=0.02), onset (p=0.01), OA grade (p=0,03), and knee deformity (p=0.04 ) have a negative correlation with functional mobility based on 30STS as well as functional mobility had a negative correlation with various aspects of quality of life, such as pain (p=0.03), stiffness (p=0.02), and functional limitation (p=0.00) subscales based on WOMAC index. Age, the onset of disease, OA grade, and knee deformity significantly correlate to functional immobility. Based on the WOMAC index, functional immobility correlates with the patient's quality of life.
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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 | 0.003 |
| 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".