Excellent 10-year patient-reported outcomes and survival in a single-radius, cruciate-retaining total knee arthroplasty
Bibliographic record
Abstract
PURPOSE: Over 2 million Triathlon single-radius total knee arthroplasties (TKAs) have been implanted worldwide. This study reports the 10-year survival and patient-reported outcome of the Triathlon TKA in a single independent centre. METHODS: From 2006 to 2007, 462 consecutive cruciate-retaining Triathlon TKAs were implanted in 426 patients (median age 69 (21-89), 289 (62.5%) female). Patellae were not routinely resurfaced. Patient-reported outcome measures (SF-12, Oxford Knee Scores (OKS), satisfaction) were assessed preoperatively and at 1, 5 and 10 years when radiographs were reviewed. Forgotten Joint Scores (FJS) were collected at 10 years. Kaplan-Meier survival analysis was performed. RESULTS: At 10-11.6 years, 123 patients (128 TKAs) had died and 8 TKAs were lost to follow-up. There were four aseptic failures (two cases of tibial loosening, two cases of instability) and four septic failures requiring revision. Symptomatic aseptic radiographic loosening was present in three further cases at 11 years. Four (1%) patellae were secondarily resurfaced. OKS score improved by 17.7 ± 9.7 points at 1 year (p < 0.001), and was maintained at 34.7 ± 9.6 at 10 years with FJS 48.5 ± 31.4. Patient satisfaction was 88% at each timepoint. Ten-year survival was 97.9% (95% confidence interval 96.5-99.3) for revision for any reason, 98.9% (97.7-100) for mechanical failure, and 98.6% (97.4-99.8) for aseptic loosening (symptomatic radiographic or revised). CONCLUSION: The Triathlon TKA continues to show excellent longer-term results with high implant survivorship, low rates of aseptic failure, consistently maintained PROMs and excellent patient satisfaction rates of 88% at 10 years. LEVEL OF EVIDENCE: II, Prospective cohort study.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".