Influence of pre-operative co-morbidities on pain and function outcomes at 1 year after primary total knee arthroplasty
Bibliographic record
Abstract
INTRODUCTION: Multimorbidity has been found to be associated with more pain and poorer function following total knee arthroplasty (TKA). We describe the relationship between both the total number of pre-operative co-morbidities, and individual co-morbidities, with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score at 12 months after TKR. METHODS: We performed a secondary analysis on 290 participants from the Arthroplasty Pain Experience (APEX) trial, with seventeen imputations by Chained Equations. Using multivariable adjusted linear regression models, we analysed the relationship between total number of pre-operative co-morbidities, followed by individual co-morbidities, with WOMAC score at 12 months after randomisation. RESULTS: Patients with ≥ 5 co-morbidities have worse outcomes compared to patients with 3 co-morbidities, scoring -9.6 points for function (95% CI -15.3 to -3.8), and -9.8 points for pain (95%CI -15.9 to -3.8). Patients reported worse pain with osteoporosis (-7.8 95%CI -14.1 to -1.6), peripheral vascular disease (-17.8 95%CI -34 to -1.8), depression (-9.8 95%CI -18.1 to -1.4), anxiety (-9.7 95%CI -18 to -1.4) or degenerative disc disease (-7.5 95%CI -13.3 to -1.7). Worse function was associated with osteoporosis (-7.1 95%CI -12.9 to -1.4), diabetes mellitus (-9.1 95%CI -15.6 to -2.6), anxiety (-8.1 95%CI -16 to -0.2) and degenerative disc disease (-8.6 95%CI -14.1 to -3.2). CONCLUSION: Pre-operative multimorbidity is associated with worse outcomes after TKA. Patients with pre-operative osteoporosis, anxiety and degenerative disc disease had worse pain and function at 12-months. Surgeons may use these results during discussion with patients about their potential outcome after TKA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".