PAPER 114: WHY ARE SOME PATIENTS DISSATISFIED WITH THEIR PRIMARY TOTAL KNEE ARTHROPLASTY (TKA)?
Bibliographic record
Abstract
Purpose: The purpose of this study was to determine the reasons for patient dissatisfaction after primary TKA. Method: Primary TKA patients (n=2513) entered into the Ontario Joint Replacement Registry (OJRR) with decision date and one year follow-up data (WOMAC, expectations, satisfaction and willingness to undergo surgery) were analyzed to determine the factors that might be associated with patients who were not satisfied with their total knee replacement. Results: The majority of patients were satisfied with their TKA (n=1939, 81%), but 169 (7%) were uncertain and 281 (12%) were not satisfied. Pre-operative expectations were important as 89% of patients who did not have their expectations met and 40% who had no expectations were dissatisfied with their TKA. Factors that affected patient satisfaction for their TKA, controlling for age, comorbidity and post-operative complications were better pre-operative WOMAC function scores (p25 point improvement). Conclusion: In this province-wide study, one in five TKA patients were not satisfied with their surgery at one-year follow-up. It is important that patients, surgeons and healthcare payers recognize significant factors that can lead to patient dissatisfaction and help patients establish realistic expectations prior to undergoing TKA surgery.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".