Excellent results of restricted kinematic alignment total knee arthroplasty at a minimum of 10 years of follow‐up
Bibliographic record
Abstract
PURPOSE: While restricted kinematic alignment (rKA) total knee arthroplasty (TKA) with cemented implants has been shown to provide a similar survivorship rate to mechanical alignment (MA) in the short term, no studies have reported on the long-term survivorship and function. METHODS: One hundred four consecutive cemented cruciate retaining TKAs implanted using computer navigation and following the rKA principles proposed by Vendittoli were reviewed at a minimum of 10 years after surgery. Implant revisions, reoperations and clinical outcomes were assessed using knee injury and osteoarthritis outcome score (KOOS), forgotten joint score (FJS), patients' satisfaction and joint perception questionnaires. Radiographs were analyzed to identify signs of osteolysis and implant loosening. RESULTS: Implant survivorship was 99.0% at a mean follow-up of 11.3 years (range: 10.3-12.9) with one early revision for instability. Patients perceived their TKA as natural or artificial without limitation in 50.0% of cases, and 95.3% were satisfied or very satisfied with their TKA. The mean FJS was 67.6 (range: 0-100). The mean KOOS were as follows: pain 84.7 (range: 38-100), symptoms 85.5 (range: 46-100), function in daily activities 82.6 (range: 40-100), function in sport and recreation 35.2 (range: 0-100) and quality of life 79.1 (range: 0-100). No radiological evidence of implant aseptic loosening or osteolysis was identified. CONCLUSION: Cemented TKA implanted with the rKA alignment protocol demonstrated excellent long-term implant survivorship and is a safe alternative to MA to improve patient function and satisfaction. LEVEL OF EVIDENCE: Level IV, continuous case series with no comparison group.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".