Achieving Accuracy and Gap Balancing in Fully Autonomous Robotic-Assisted Total Knee Arthroplasty with Functional Alignment in Valgus Knee Deformity
Bibliographic record
Abstract
Introduction: The robotic-assisted total knee arthroplasty (RA-TKA) facilitates real-time intra-operative balance assessment and accurate component positioning customized to the patient's ligamentous behavior, enhancing procedural accuracy and precision. Preliminary findings suggest RA-TKA, using fully autonomous computed tomography based systems, such as Cuvis, result in better short-term outcomes and improved patient-reported outcome measures. Coronal plane alignment of the knee classification aids to decide pre-arthritic phenotype of the knee and soft tissue balance judgment. Materials and Methods: This investigation was conducted as a retrospective matched-cohort observational study. We retrospectively analyzed a matched group of patients to compare RA TKA with functional alignment (n = 26) and mechanically aligned conventional-TKA (CM-TKA) (n = 24) in individuals with a valgus deformity Ranawat grade 1 and 2. The evaluation included radiographic assessments and PROMs over a 6-month period. The Western Ontario and McMaster University Osteoarthritis Index score and Oxford Knee Score (OKS) were used to determine the outcomes. Results: The RA TKA cohort showed faster recovery than CM TKA patients. The RA TKA cohort required less soft tissue releases (P = 0.010). At the 3-month follow-up, there was a substantial reduction in pain in the RA TKA cohort (19.73 ± 2.38 vs. 25.71 ± 3.96, P = 0.000). However, over 6 months, pain reduction was found to be similar in both groups (13.27 ± 1.99 vs. 13.21 ± 2.04, P = 0.281). The improvement in OKS in RA TKA cohort was significant at 3 months (33.96 ± 3.88 vs. 31.04 ± 2.79, P = 0.006) and at 6 months (39.77 ± 2.97 vs. 36.46 ± 3.18, P = 0.136), and improved ROM in both groups (111.25 ± 13.29 vs. 116.96 ± 9.31, P = 0.083), with improvement in flexion (12.73 ± 5.85 vs. 7.08 ± 10.41, P = 0.210) in RA TKA compared to the CM-TKA cohort. Conclusion: The CUVIS robotic system leads to optimum gap balancing throughout the range of motion, less soft tissue release, less post-operative pain, and improved function in short-term follow-up with optimum patella tracking in valgus knees.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".