The Etiology of Total Knee Arthroplasty Failure Influences on Improvement in Knee Function: A Follow-Up Study
Bibliographic record
Abstract
Background: Outcomes following total knee arthroplasty (TKA) revisions are variable, and it is hypothesized that the underlying cause of primary TKA failure impacts postoperative outcomes. This study analyzes the results of TKA revisions seven years after surgery, in relation to the etiology of primary failure and other influencing factors. A previous study conducted in 2013 examined the same cohort of patients three months after revision surgery. Methods: From the original study, 97 patients were followed up, and 49 patients were eligible for inclusion. Patients were classified into four groups: “periprosthetic infection” (PPI), “aseptic loosening,” “instability,” and “arthrofibrosis.” Outcomes were analyzed using established scores (the Knee Society Score (KSS), New Knee Society Score (nKSS), and the Western Ontario and McMaster Universities (WOMAC) index) and considering factors such as age, gender, BMI, and ASA classification. The outcomes were analyzed using three time intervals: “Outcome Short” (preoperative to 3 months postoperative); “Outcome Long” (preoperative to 7 years postoperative); and “Delta PostOP” (3 months postoperative to 7 years postoperative). Results: Significant improvements were observed in all time intervals, especially in the “Outcome Short” (p < 0.001) and “Delta PostOP” (p < 0.001) periods. The “instability” and “aseptic loosening” groups showed better outcomes in terms of range of motion and knee scores than the “arthrofibrosis” and “infection” groups (p < 0.05). A lower BMI and an ASA status of II were associated with better outcomes (p < 0.05). Women also showed superior results in the nKSS (p < 0.05). Discussion: Patients with “aseptic loosening” and “instability” had the best long-term outcomes. Lower BMI and better ASA status also correlated with improved results. These findings can inform patients of the potential outcomes of revision surgery, thereby facilitating informed decision-making.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".