Patient-reported quality of life after primary major joint arthroplasty: a prospective comparison of hip and knee arthroplasty
Bibliographic record
Abstract
BACKGROUND: To investigate and compare the impact of primary hip (THA) and knee (TKA) arthroplasty on quality of life in patients with osteoarthritis, to determine patients' satisfaction with total joint arthroplasty, and to detect the effect of patients' demographic and clinical characteristics on outcome. METHODS: Three hundred seventy eight (378) patients with hip (174) and knee (204) osteoarthritis undergoing total joint arthroplasty (174 THA-204 TKA) were assessed pre- and post-operatively (6 weeks, 3, 6, and 12 months) using the Western Ontario and McMaster Osteoarthritis Index (WOMAC) and Centre for Epidemiological Studies Depression Scale (CES-D10). The patients' satisfaction with the results of total joint arthroplasty was also assessed. Differences were analyzed using general linear model for repeated measures. RESULTS: The one-year response rate was 97 % for THA and 90 % for TKA. WOMAC and CES-D10 scores improved significantly after one year for both THA and TKA (P < 0.0001). The improvement in WOMAC total score was significantly greater for TKA patients (P < 0.0001 at 12 months). WOMAC pain and stiffness improved earlier for THA (6 weeks), while TKA had equivalent improvements at 3 and 6 months respectively. Both THA/TKA displayed significant improvement of WOMAC function at 3 months but TKA had greater improvement. Age, body mass index, residence, education and social support were not significant predictors of quality of life after total joint arthroplasty. One year postoperatively 88 % of patients were satisfied. CONCLUSIONS: WOMAC and CES-D10 improved significantly one year postoperatively. Although pain and stiffness improved earlier in THA, functional improvement was inferior in THA compared to 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".