Low back pain and other musculoskeletal pain comorbidities in individuals with symptomatic osteoarthritis of the knee: Data from the osteoarthritis initiative
Bibliographic record
Abstract
OBJECTIVE: To examine the association of concurrent low back pain (LBP), and other musculoskeletal pain comorbidity, with knee pain severity in symptomatic knee osteoarthritis (OA). METHODS: Individuals from the Progression Cohort of the Osteoarthritis Initiative (n=1,389, ages 45-79 years) with symptomatic tibiofemoral knee OA were studied. Participants identified pain in the low back, neck, shoulder, elbow, wrist, hand, hip, knee, ankle, or foot. The primary outcome was the pain subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) applied to the more symptomatic knee. We examined WOMAC pain score in persons with and without LBP, before and after adjusting for other musculoskeletal symptoms. RESULTS: Of the participants, 57.4% reported LBP. The mean±SD WOMAC pain score (possible range 0-20) was 6.5±4.1 in participants with and 5.2±3.4 in participants without LBP (P<0.0001). In multivariate analyses, LBP was significantly associated with increased WOMAC knee pain score (β [SE]=1.00 [0.21], P<0.0001). However, pain in all other individual musculoskeletal locations demonstrated similar associations with knee pain score. In models including all pain locations simultaneously, only LBP (β [SE]=0.65 [0.21], P=0.002), ipsilateral elbow pain (β [SE]=0.98 [0.40], P=0.02), and ipsilateral foot pain (β [SE]=1.03 [0.45], P=0.02) were significantly associated with knee pain score. Having >1 pain location was associated with greater WOMAC knee pain; this relationship was strongest for individuals having 4 (β [SE]=1.83 [0.42], P<0.0001) or ≥5 pain locations (β [SE]=1.86 [0.36], P<0.0001). CONCLUSION: LBP, foot pain, and elbow pain are significantly associated with WOMAC knee pain score, as are a higher total number of pain locations. This may have implications for clinical trial planning.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".