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 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 | 0.000 | 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".