Failure Rate of Fixed Versus Mobile Bearing Total Ankle Arthroplasty
Bibliographic record
Abstract
BACKGROUND: With an increasing number of total ankle arthroplasties (TAAs) being performed and an abundance of new survivorship data available, an updated literature review is needed to better understand the impact of different types of implants on outcomes of TAA. This study aims to review existing literature and identify trends among current individual fixed versus mobile bearing TAA implants. METHODS: A comprehensive search of PubMed, CINAHL, and Scopus for all articles published between 2004 and 2024 examining outcomes of third- and fourth-generation TAAs was conducted with a minimum 2-year mean follow-up. Eighty-five clearly defined implant-receiving patient groups met inclusion criteria. Forty-four groups (4,805 subjects; 60.4%) were implanted with mobile bearing devices and 41 (3,147 subjects; 39.6%) with fixed bearing implants. In total, 7,952 subjects were included, with a pooled mean age of 62.1 years and a mean BMI of 28.6 kg/m 2 . RESULTS: Pooled mean implant survival rates were 98.05%, 96.96%, 92.54%, 81.9%, and 72.0% at 1, 2, 5, 10, and 15 years, respectively. Survival rates were statistically significantly better for fixed bearing TAAs compared with mobile bearing TAAs, even when controlling for length of follow-up (fixed: mean average follow-up = 3.88 years; range average follow-up = 2 to 7.1) (mobile: mean average follow-up = 6.28 years; range average follow-up = 2 to 15.7). No statistically significant differences were noted in revision surgery rates. CONCLUSION: This study offers updated literature reviews of current third- and fourth-generation TAA, finding higher metal component survival rates for fixed bearing TAAs compared with mobile bearings, even when controlling for duration of follow-up. While more research is needed to confirm these findings, surgeons should be aware of these data when selecting TAA implants. LEVEL OF EVIDENCE: Level IV, Systematic Review of Level I-IV Studies.
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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 | 0.009 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".