High in‐vivo accuracy of a novel robotic‐arm‐assisted system for total knee arthroplasty
Bibliographic record
Abstract
PURPOSE: Robotic-assisted total knee arthroplasty (TKA) has been shown to improve the accuracy and precision of bony resections and implant position. However, the in vivo accuracy of the full surgical workflow has not been widely reported. The primary objective of this study is to determine the accuracy and precision of a robotic-arm-assisted system throughout the intraoperative workflow. METHODS: This was a retrospective cohort study of adult patients who underwent primary TKA with various workflows and alignment targets by three arthroplasty-trained surgeons with previous experience using the ROSA® Knee System (Zimmer Biomet) over a 3-month follow-up period. Accuracy and precision were determined by measuring the difference between various workflow time points, including the final preoperative plan (PP), robot-validated (RV) resection angle and postoperative radiographs (PR). The absolute mean difference between the measurements determined accuracy, and the standard deviation represented precision. The lateral distal femoral angle, medial proximal tibial angle, femoral flexion angle and tibial slope were measured on postoperative coronal long-leg radiographs and true short-leg lateral radiographs. RESULTS: A total of 77 patients were included in the final analyses. The accuracy for the coronal femoral angle was 1.62 ± 1.11°, 0.75 ± 0.79° and 1.96 ± 1.29° for the differences between PP and PR, PP and RV and RV and PR. The tibial coronal accuracy was 1.44 ± 1.03°, 0.81 ± 0.67° and 1.57 ± 1.14° for PP/PR, PP/RV and RV/PR, respectively. Femoral flexion accuracy was 1.39 ± 1.05°, 0.83 ± 0.59° and 1.81 ± 1.21° for PP/PR, PP/RV and RV/PR, respectively. Tibial slope accuracy was 0.99 ± 0.72°, 1.19 ± 0.87° and 1.63 ± 1.11°, respectively. The proportion of patients within 3° was 93.2%, 95.3%, 97.3% and 94.6% for the distal femur, proximal tibia, femoral flexion and tibial slope angles when the final intraoperative plan was compared to PRs. No patients had a postoperative complication at the final follow-up. CONCLUSIONS: The ROSA Knee System has acceptable accuracy and precision of coronal and sagittal plane resections with few outliers at various steps throughout the platform's entire workflow in vivo. LEVEL OF EVIDENCE: Level III.
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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 | 0.002 | 0.005 |
| 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".