Accuracy of a Patient-Specific Total Ankle Arthroplasty Instrumentation
Bibliographic record
Abstract
BACKGROUND: Total ankle arthroplasty (TAA) is a preferred surgical option for end-stage ankle osteoarthritis; however, it is a demanding procedure with a higher historical rate of revision compared with ankle fusion. Patient-specific instrumentation (PSI) has been introduced to optimize prosthesis alignment and theoretically overall improve TAA outcomes. The goal of this study is to report on the experience and surgical outcomes of one implant with specific evaluation of the accuracy and reproducibility of the system with respect to prosthesis alignment and prediction of implant size. METHODS: A retrospective, multicentered study involving 4 foot and ankle fellowship-trained orthopaedic surgeon's patients undergoing TAA between January 1, 2015, and December 31, 2018, using the PROPHECY PSI system. RESULTS: 80 TAA procedures were performed. On average the postoperative tibial component alignment was 89.9 (range, 86.1-96.5) degrees in the coronal plane, with a mean sagittal alignment of 88.1 (range, 81.3-96.7) degrees. The mean deviation from neutral sagittal alignment improved from 4.9 ± 3.9 degrees preoperatively to 2.7 ± 1.7 degrees postoperatively, whereas the mean coronal alignment improved from 3.3 ± 2.5 degrees to 1.3 ± 1.1 degrees. The PSI software correctly determined the tibial implant size in 70 patients (89%). Prediction of talar implant sizing was less accurate than the tibial component, with 56 patients (71%) using the predicted sized implant. The overall implant survival at a mean follow-up of 45 months (range, 27-76) was 97.5%. CONCLUSION: We found that this PSI system accurately and reliably assisted in implant total ankle prosthesis positioning within a clinically acceptable margin and without significant outliers. Prediction of implant size was not as accurate as component orientation. LEVEL OF EVIDENCE: Level III, retrospective 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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".