Increased symptoms of stiffness 1 year after total knee arthroplasty are associated with a worse functional outcome and lower rate of patient satisfaction
Bibliographic record
Abstract
PURPOSE: Symptoms of stiffness after total knee arthroplasty (TKA) cause significant morbidity, but there is limited data to facilitate identification of those most at risk after surgery. Stratifying risk can aid earlier directed treatment options. METHODS: A retrospective cohort consisting of 2589 patients undergoing a primary TKA was identified from an established arthroplasty database. Patient demographics, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and short form (SF) 12 scores were collected pre-operatively and 1 year post-operatively. In addition, patient satisfaction was assessed for 1 year. Patients with a worse WOMAC stiffness score in 1 year were defined as the "increased" stiffness group and the other cohort as the non-stiffness group. RESULTS: At 1 year after surgery 129 (5%) patients had a significant increase in their stiffness symptoms (20%, 95% confidence interval (CI) 17.9-22.0, p < 0.001), and had significantly (all p < 0.001) less of an improvement in their pain, function and total WOMAC scores, and SF-12 scores compared to the non-stiffness group (n = 2460). Patient satisfaction was significantly lower (odds ratio (OR) 0.178, CI 0.121 to 0.262, p < 0.001) for the increased stiffness group. Logistic regression analysis identified male gender (OR 1.66, p = 0.02), lung disease (OR 2.06, p = 0.002), diabetes (OR 1.82, p = 0.02), back pain (OR 1.81, p = 0.005), and a pre-operative stiffness score of 44 or more (OR 5.79, p < 0.001) were significantly predictive of increased stiffness. CONCLUSION: Patients with increased symptoms of stiffness after TKA have a worse functional outcome and a lower rate of patient satisfaction, and patients at risk of being in this group should be informed pre-operatively. LEVEL OF EVIDENCE: Retrospective prognostic study, Level III.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".