Depression Subtypes in Individuals With or at Risk for Symptomatic Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: The present study was undertaken to identify depression subtypes in individuals with or at risk for symptomatic knee osteoarthritis (OA) and to evaluate differences in pain and disability trajectories between groups. METHODS: Participants (n = 4,486) were enrolled in the Osteoarthritis Initiative. Latent class analysis was applied to the 20-item Center for Epidemiologic Studies Depression Scale measured at baseline to identify groups with similar patterns of depressive symptoms, and subtypes were assigned using posterior probability estimates. The relationships between depression subtypes and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and disability subscales were modeled over 4 years and stratified by baseline knee OA status (symptomatic [n = 1,626] or at risk [n = 2,860]). RESULTS: Four subtypes were identified: asymptomatic (80.6%), catatonic (5.3%), anhedonic (10.6%), and melancholic (3.5%). Catatonic and anhedonic subtypes were differentiated by symptoms corresponding to psychomotor agitation and the inability to experience pleasure, respectively. The melancholic subtype expressed symptoms related to reduced energy and movement, anhedonia, and other somatic symptoms. Detectable mean differences in pain and disability compared to the asymptomatic group were observed for the anhedonic (1.5-2.3 WOMAC units) and melancholic (4.8-6.6 WOMAC units) subtypes, and associations were generally larger in individuals with symptomatic knee OA relative to those at risk. CONCLUSION: Among individuals with or at risk for symptomatic knee OA, there is evidence of depression subtypes characterized by distinct clusters of depressive symptoms that have differential effects on reports of pain and disability over time. Our findings thus imply that depression interventions could be optimized by targeting the specific symptomology that these subtypes exhibit.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".