Cross-Sectional and Longitudinal Associations of Comorbidities with Knee Symptoms and Radiographic Abnormalities of Osteoarthritis
Bibliographic record
Abstract
INTRODUCTION: This study aimed to investigate the associations of comorbidities with knee symptoms and radiographic abnormalities of osteoarthritis (OA). METHODS: Participants were from the Osteoarthritis Initiative. Comorbidities were identified at baseline using the modified Charlson Comorbidity Index. For both knees, symptoms were assessed annually from baseline to 48 months using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function scores (rescaled range 0-100), and radiographic abnormalities using the Kellgren-Lawrence (KL, 0-4) grades. The presence of significant pain and functional disability was defined as a WOMAC score of ≥ 25 and ≥ 22, respectively, and radiographic OA (ROA) as KL ≥ 2. An increase of ≥ 9 in WOMAC scores and ≥ 1 in KL grades were defined as symptomatic and radiographic progression, respectively. RESULTS: Of 3337 participants, 28% and 9% had one and ≥ 2 comorbidities, respectively. The number of comorbidities was associated with the presence of significant functional disability (odds ratios [ORs] 1.15; 1.46) and predicted the progression of both knee pain and functional disability (ORs 1.11; 1.51). For the type of comorbidities, non-OA musculoskeletal diseases were associated with the presence of ROA and significant functional disability (ORs 1.63; 1.82) and showed a trend to predict incident ROA (OR 1.84, 95% confidence interval 1.00-3.38 p = 0.051). Diabetes and kidney diseases were associated with symptomatic progression of OA (ORs 1.38; 2.72). CONCLUSIONS: Having more comorbidities, especially diabetes and kidney diseases, is associated with symptomatic progression of knee OA. Moreover, non-OA musculoskeletal diseases may be associated with the presence and onset of ROA.
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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 | 0.000 | 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 | 0.001 |
| 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".