Improvement in mental health following total hip arthroplasty: the role of pain and function
Bibliographic record
Abstract
BACKGROUND: Mental health has been shown to improve after total hip arthroplasty (THA). Little is known about the role of pain and function in this context. We assessed whether change in mental health was associated with improvement in pain and function 1 year post-surgery. METHODS: This prospective study included patients enrolled in a THA registry from 2010 to 2014. We examined the mental component score (MCS) before and 1 year post-surgery, and 1-year change, in association with Western Ontario McMaster Universities (WOMAC) pain and function scores. All scores were normalized, ranging from 0 to 100 (larger score indicating better outcome). Analyses were adjusted for potential confounders. RESULTS: Our study included 610 participants, of which 53% were women. Descriptive statistics are as follows: the average (SD) for age (years) was 68.5 (11.8), and for BMI was 26.9 (4.9). In addition, the MCS average (SD) at baseline was 44.7 (11.2), and at 1-year after THA was 47.5 (10.5). The average change from baseline to 1-year post-THA in MCS was 2.8 (95% CI: 1.9, 3.6), for an effect size of 0.26. As for the WOMAC pain score, the average change from baseline to 1-year post-THA was 44.2 (95%CI: 42.4, 46.0), for an effect size of 2.5. The equivalent change in WOMAC function was 38.1 (95% CI: 36.2, 40.0), for an effect size of 2.0. Results from multivariable analysis controlling for covariates showed that an improvement of 10 points in the 1-year change in pain score resulted in a 0.78 point (95%: CI 0.40, 1.26) increase in the 1-year change in MCS, whereas a 10-point improvement in the 1-year change in function was associated with a 0.94 point (95% CI: 0.56, 1.32) increase. CONCLUSIONS: Mental health significantly improved from baseline to 1-year post-THA. Greater improvement in pain and function was associated with greater improvement in mental health 1 year post-THA.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".