Patterns of Depressive Symptoms Before and After Surgery for Osteoarthritis: A Descriptive Study
Bibliographic record
Abstract
OBJECTIVE: To examine patterns of depressive symptoms before and over the year following osteoarthritis (OA) surgery, stratified by joint and postsurgical outcome. METHODS: Participants were hip (n = 287), knee (n = 360), and lumbar spine (n = 100) OA patients scheduled for joint replacement or decompression surgery with or without fusion. One pre- and 4 postsurgery questionnaires were completed. Depressive symptoms were quantified using the Hospital Anxiety and Depression Scale (HADS). One-year outcomes were based on Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain scores for hip and knee patients and Oswestry Disability Index (ODI) scores for spine patients and were categorized as "worse" (top score tertile) vs. "better" outcomes (first, second tertiles). Plots over time were generated by joint and outcome: 1) mean pain/disability and depression scores and 2) percentage of patients meeting HADS cut-off for depression "caseness," reporting depression diagnosis and treatment. RESULTS: There were notable decreases in depression scores for patients with better outcomes. For those with worse outcomes, decreases were smaller for hip patients and were not significant for knee and spine patients. Among those with poorer outcomes, 25% of spine and knee patients were depression "cases" pre- and postsurgery; an additional 16% of spine and 10% of knee patients developed new "caseness" postsurgery. The proportion of these patients deemed depression cases by score was much higher than the proportion reporting diagnosis/treatment. CONCLUSION: Although depressive symptoms decrease overall in OA patients postsurgery, degrees of change vary by joint and surgical outcome. Greater attention to mental health postsurgery is warranted and may lead to improved surgical outcomes, particularly among knee and spine patients.
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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 | 0.001 | 0.001 |
| 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".