Effects of psychological distress on the general health to self-reported pain and function outcome relationship in knee arthroplasty: A causal mediation study
Bibliographic record
Abstract
Objectives: We examined two potential causal pathways that could be intervention targets to enhance knee arthroplasty outcomes. Data from a no-effect trial of persons with moderate to high pain catastrophizing were used to determined whether pain catastrophizing, depressive symptoms causally mediate the effect of preoperative general health on postoperative knee pain and functional difficulty. Methods: We used natural-effects models to conduct causal mediation analyses using the preoperative dichotomized EQ-5D-5L general health measure as the exposure, 2-month postoperative pain catastrophizing, depressive symptoms, and localized knee pain as potential mediators, and 12-month dichotomized Western Ontario and McMaster's University Osteoarthritis Index (WOMAC) Pain and Function scores reflecting good versus poor outcome as the outcomes. Results: Estimates of the indirect (mediating) effect suggested that pain catastrophizing mediated the effect of preoperative general health on 12-month WOMAC pain score by increasing odds of a good outcome by 8% (natural indirect effect odds ratio = 1.08, 95% CI: 0.88, 1.29). The direction of mediating effects and their magnitude were similar for depressive symptoms; Sensitivity analyses suggested similar magnitudes and mediating effects to those reported for the main analyses. Conclusions: Our findings suggested that pain catastrophizing and depressive symptoms have a mediating role on the effect of baseline general health on self-reported pain and function outcomes. These findings support the continued treatment of pain catastrophizing and depressive symptoms as viable targets for interventions to potentially enhance pain and function outcomes for patients with moderate to high levels of psychological distress prior to surgery.
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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 | 0.022 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".