Prevelence of depression in patients with osteoarthritis and its relationship with associated pain and physical disability – A Descriptive Cross-sectional Questionnaire Based Study
Bibliographic record
Abstract
Aim and Objective;This study was aimed at establishing a correlation between disease activity (Total WOMAC Score), pain (VAS-during interview, WOMAC Pain-while doing activities), stiffness (WOMAC Stiffness Score), disability (WOMAC Disability Score), duration of disease (caused due to osteoarthritis) to prevalence of comorbid depression (BDI). Methodology: This is a descriptive cross-sectional questionnaire-based study on 151 participants with osteoarthritis. The study was conducted in the Government Wenlock Hospital, Mangalore, Karnataka, India from 17th May to 29th September 2018. The WOMAC (Western Ontario and Macmaster Universities Arthritis Index) was used to assess symptoms for the past 48 hrs and the VAS (Visual Analogue Scale) was used to measure pain intensity. Backs Depression Inventory ( B D I ) scale is used to measure depression. Results: In this study it was found that depression was highly prevalent among osteoarthritis patients. 73.83% of participants were found to have moderate depression. Pain experienced during interview due to osteoarthritis (as measured by VAS) had very high statistical correlation with depression. Pain experienced due to osteoarthritis while performing certain daily activities (as measured by pain section of WOMAC) had significant statistical correlation with depression (p=0.028). Conclusion: The study concluded that pain caused due to osteoarthritis has significant correlation with comorbid depression. Duration of disease and duration of treatment though was not significantly correlated with depression [p(disease)=0.382 and p(treatment)=0.521]. Physical disability caused by osteoarthritis (as measured by disability portion of WOMAC) is not significantly correlated to depression (p=0.464, r=0.060).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".