Association between disease progression and depression onset in persons with radiographic knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: Osteoarthritis (OA) disease progression may lead to deteriorating psychosocial function, but it is unclear what aspects of disease severity are related to the onset of depression. This study assessed which components of OA disease progression cumulatively contribute to depression onset in persons with radiographic knee OA. METHODS: Osteoarthritis Initiative participants (n = 1651) with radiographic disease (Kellgren-Lawrence grade ≥2) in one or both knees and below the screening threshold for probable depression [Center for Epidemiological Studies Depression (CES-D) scale <16] at baseline were included. Disease severity was measured from baseline to the third annual follow-up visit using joint space width, 20-meter gait speed, and the Western Ontario and McMaster Universities Osteoarthritis Index pain subscale, each categorized into quintiles. Depression onset (CES-D ≥ 16) was assessed annually at four follow-up visits. Marginal structural models that account for time-dependent confounding and attrition evaluated the association between each time-varying disease severity measure and depression onset. RESULTS: Each disease severity measure exhibited a non-linear relationship concerning the probability of depression onset, with the higher quintiles generally being associated with a larger risk. The highest quintile (relative to the lowest) of joint space width and gait speed were both significantly associated with depression onset. By contrast, none of the higher pain quintiles compared with the lowest were significantly associated with the onset of depression. CONCLUSION: Faster disease progression as measured by either worsening structural severity or decreasing physical performance corresponds to an increased risk of depression among individuals with radiographic knee OA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 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".