Assessment on Health Status of Adult Patients with Osteoarthritis of the Lower Limb by Western Ontario and McMaster’s Universities Osteoarthritis Index (WOMAC): A Study in Chennai City
Bibliographic record
Abstract
Adult patients with Osteoarthritis of the Lower Limb (OALL) is a widely recognized health burden. Western Ontario and McMaster’s Universities Osteoarthritis Index (WOMAC) are widely used to assess osteoarthritis among patients. The study aimed to evaluate the health status of adult patients with OALL in Chennai City, India using the WOMAC scale. A cross-sectional study design was used. Respondents who arrived at the hospital and met the inclusion criteria were selected one after one. One hundred seven patients diagnosed with OALL participated in the study. Among them, 81 were female patients and 26 were male patients. To assess the health status of OALL patients, three instruments were used; the General information questionnaire, the WOMAC scale and the Self-rated Health status questionnaire. The variables were evaluated by mean and standard deviation. ANOVA was calculated by using SPSS Version 21. The mean ± SD age of the adult patients was 60.42 ± 9.07 years. Experience of pain, stiffness, and performance of daily activities was significantly worse among female patients with OALL. There is a strong correlation between the gender and age group of adult patients (Male <0.003 and Female <0.001) and their level of physical suffering. More than half of the patients (57%) stated that their overall health condition was bad. OALL significantly impairs the health and daily activities of adult patients in India. The findings of this study may support policymakers in designing community-based geriatric health care and health policies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".