Outcomes of primary total knee arthroplasty: the impact of patient-relevant factors on self-reported function and quality of life
Bibliographic record
Abstract
PURPOSE: To identify factors associated with functional recovery and outcome 1 year after total knee arthroplasty (TKA). METHODS: In the prospective follow-up study, all the patients (n = 75, aged 60-80 years) underwent primary TKA. Assessments were performed preoperatively and 12 months after surgery. The main measures were the Western Ontario and McMaster Universities OA Index (WOMAC) and the 15D. The clinical examination included analyses of comorbidity and a detailed knee examination. Age-standardised population values of the 15D and the Outcome Measures in Rheumatology-Osteoarthritis Research Society International (OMERACT-OARSI) criteria were used as indices of response. RESULTS: Osteoporosis, pain, gender, age and preoperative function of the opposite knee accounted for 29.9% of the variance in the change in the WOMAC function score. A preoperative score of the 15D below the age-standardised population level, pain, higher age and pulmonary disease reduced the possibility to reach the HRQOL level of the general population. Osteoporosis decreased the likelihood of achieving responder status according to the OMERACT-OARSI criteria. CONCLUSION: The baseline preoperative score of the 15D strongly associated with the achieved level of HRQOL after TKA. The findings of the present study highlight the multifactorial nature of health status in 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".