Assessment of effect of osteoarthritis of knee on the activities of daily living and treatment seeking behaviour of patients at Kalaburagi, Gulbarga city of Karnataka
Bibliographic record
Abstract
Background: Osteoarthritis (OA) is estimated to be the fourth leading cause of disability in most of the countries. It is the most frequent joint disease with a prevalence of 22% to 39% in India. The objectives of the study were to assess the effect of OA of knee on activities of daily living using Western Ontario and McMasters University Osteoarthritis (WOMAC) index and treatment seeking behaviour of patient with OA of knee.Methods: Convenience sampling was used to find out patients of OA from 15th April to 1st June 2016 with cross-section type of study design. Data was collected and analyzed using MS Excel 2000.Results: In this study 16% of participants in underweight category and 79% participants in overweight category reported moderate to very severe pain on visual analogue score (VAS). Treatment seeking behaviour was quite poor in lower socio-economic class (SEC) as compared to upper SEC. 20.34% participants had extreme pain while walking. 9.74% participants experienced extreme level of morning stiffness while 18.72% had extreme difficulty while ascending stairs. 14.87% experienced extreme difficulty during getting standing position from sitting position.Conclusions: Moderate to severe pain on VAS was more common in overweight group compared to underweight group. Treatment seeking behaviour was quite poor in lower SEC as compared to upper SEC. 20.34% participants had extreme pain while walking. 14.87% experienced extreme difficulty during getting standing position from sitting position.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".