Patient Satisfaction after Total Knee Arthroplasty: Who is Satisfied and Who is Not?
Bibliographic record
Abstract
UNLABELLED: Despite substantial advances in primary TKA, numerous studies using historic TKA implants suggest only 82% to 89% of primary TKA patients are satisfied. We reexamined this issue to determine if contemporary TKA implants might be associated with improved patient satisfaction. We performed a cross-sectional study of patient satisfaction after 1703 primary TKAs performed in the province of Ontario. Our data confirmed that approximately one in five (19%) primary TKA patients were not satisfied with the outcome. Satisfaction with pain relief varied from 72-86% and with function from 70-84% for specific activities of daily living. The strongest predictors of patient dissatisfaction after primary TKA were expectations not met (10.7x greater risk), a low 1-year WOMAC (2.5x greater risk), preoperative pain at rest (2.4x greater risk) and a postoperative complication requiring hospital readmission (1.9x greater risk). LEVEL OF EVIDENCE: Level II, prognostic study. See Guidelines for Authors for a complete description of levels of evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".