Psychosocial Determinants of Total Knee Arthroplasty Outcomes Two Years After Surgery
Bibliographic record
Abstract
Objective To evaluate the association of preoperative psychosocial and demographic factors with total knee arthroplasty (TKA) outcomes and satisfaction in patients with osteoarthritis (OA) of the knee at 24 months after surgery. Methods A prospective cohort study of patients undergoing TKA was conducted. Outcome measures included: Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Short Form 36 (SF‐36) scores at baseline and 24 months after surgery, and patient satisfaction with TKA at 24 months. Linear regression models were performed to evaluate the association of preoperative psychosocial determinants (ie, Medical Outcome Study Social Support Scale; Depression, Anxiety, and Stress Scale; Brief COPE inventory, The Life Orientation Test‐Revised; Multidimensional Health Locus of Control; and Arthritis Self‐Efficacy Scale) on outcomes. Results We included 178 patients. Increasing WOMAC pain scores at 24 months were associated with increasing age and body mass index (BMI); low tangible social support and low optimism were associated with higher levels of pain (R2 = 0.15). A decrease in WOMAC function scores was also associated with older age and higher BMI; low tangible support, increased stress, and low optimism were also associated with worse function (R2 = 0.22). When evaluating quality of life, lower SF‐36 physical functioning scores at 24 months were associated with age, high BMI, and comorbidity (R2 = 0.34). Lower SF‐36 mental functioning scores were associated with depression and low optimism (R2 = 0.38). Having a dysfunctional style of coping was associated with lower satisfaction with surgery after 24 months (adjusted R2 = 0.12). Conclusion Psychosocial factors, such as tangible support, depression, dysfunctional coping, and optimism, were associated with pain, function, and satisfaction 2 years after TKA. Perioperative programs identifying and addressing psychosocial problems may result in improvements in pain and function after TKA.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".