Quantifying the Pain Experience in Hip and Knee Osteoarthritis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The present study investigated whether the conceptualization of hip and knee osteoarthritis pain implicit in the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Medical Outcomes Study Short-Form 36 (SF-36) scales is complete, or whether the addition of another scale, such as the Short-Form McGill Pain Questionnaire (MPQ-SF), provides a more complete characterization. Furthermore, the impact that mental health symptoms and catastrophizing had on these scales was investigated. METHODS: Before hip and knee arthroplasty, 200 patients completed surveys of demographic data, the WOMAC pain scale, the MPQ-SF, the SF-36 Bodily Pain scale, the Pain Catastrophizing Scale and the Hospital Anxiety and Depression Scale. Correlations between scales were calculated and linear regression modelling was used to determine the impact of mental health and catastrophizing on these three pain measures. RESULTS: A strong correlation between the WOMAC and SF-36 pain scales (r=-0.70) was found; however, both correlated only moderately with the MPQ-SF (r=0.36 and r=-0.36, respectively). Linear regression modelling showed that the Pain Catastrophizing Scale significantly predicted a greater score on all three pain scales (P<0.05). CONCLUSIONS: The addition of the MPQ-SF appears to add to a more complete quantification of the pain experience in hip and knee osteoarthritis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it