Is It the Surgeon, the Patient, or the Device? A Comprehensive Clinical and Radiological Evaluation of Factors Influencing Patient Satisfaction in 648 Total Knee Arthroplasties
Bibliographic record
Abstract
Total knee arthroplasty (TKA) is a successful and safe surgical procedure for treating osteoarthritic knees, but despite the overall good results, some patients remain dissatisfied. The aim of this study is to evaluate the influence of patient-related and surgery-related variables in a consecutive group of patients that underwent TKA. Individuals (n = 648) who had TKA performed between 01 January 2013 and 31 December 2017 were enrolled in the study. Postoperative Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, Knee Injury and Osteoarthritis Outcome Score (KOOS) and Forgotten Joint score (FJS-12) were collected at a mean follow-up of 4.79 years. Patient satisfaction was assessed with a questionnaire. Determinants of satisfaction (age, sex, smoking, presence of diabetes or cardiovascular disease, pain in other joints, preoperative arthritic stage) and components of satisfaction (slope variation, mechanical axis variation, outlier final alignment, surgeon experience) were examined to identify which variables correlated with positive outcome. Correlations with septic and mechanicals failures were also evaluated. Thirteen percent of patients were unsatisfied, despite good results in KOOS, WOMAC and FJS-12 tests. Female gender, low Kellgren–Lawrence grade and the presence of back pain and pain in other joints were factors associated with poor clinical results. Poorer clinical results were also reported in younger patients. Infection rate was correlated with active smoking and mechanical failure with an outlier final alignment. Comorbidities, smoking habits and high expectations have a big influence on TKA results and on final satisfaction after surgery.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".