Gender-based analysis of WOMAC scores in moderate and advanced knee osteoarthritis: evaluating pain, stiffness and functional impairment
Bibliographic record
Abstract
Background: Knee osteoarthritis (KOA) significantly impacts mobility and quality of life, with key issues being pain, stiffness, and functional restrictions. With possible differences in the course of the disease and the intensity of symptoms, gender differences in OA symptoms are still uncertain. Using the Western Ontario and McMaster Universities Arthritis Index (WOMAC), this study examined gender-based variations in the burden of OA symptoms between KL grade 2 and KL grade 3 KOA. Methods: According to the EULAR classification, 108 patients with KOA were included in the study. Male and female patients with knee OA underwent WOMAC scores for pain, stiffness, function, and overall discomfort examined. Statistical significance was evaluated using 95% CI, mean differences, and independent t-tests. A p value of less than 0.05 has been considered significant. Results: Across all WOMAC domains, no statistically significant gender differences were discovered, and all comparisons had p values greater than 0.05. In KL grade II, males scored slightly higher on pain and stiffness, but in Kl grade III, these differences decreased. In both grades, the functional and total WOMAC scores were similar for both genders. Conclusions: The results show that among those with knee OA, there are no appreciable differences in symptom load by gender. This highlights the necessity of tailored treatment plans as opposed to gender-specific approaches. Other factors affecting OA outcomes, such as biomechanics, hormonal effects, and lifestyle factors, should be investigated further.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".