Robotic total knee arthroplasty for moderate to high-grade valgus knee deformity: technique and outcomes
Bibliographic record
Abstract
INTRODUCTION: Although the surgical techniques and functional outcomes of conventional total knee arthroplasty (TKA) are well-established, there is limited data available on robotic arm-assisted TKA (RATKA) in the context of valgus knee arthroplasty. The purpose of this study is to assess the efficacy of RATKA in the correction of moderate to severe valgus knee deformities using minimally constrained implants and to evaluate the short-term functional outcomes associated with this technique. METHODS: This prospective study was conducted on patients with moderate to severe grade valgus knee deformity who underwent RATKA from August 1, 2020 to May 31, 2022. Of 873 primary RATKA cases, 48 cases had valgus knee deformities. Among these, 27 had grade 2-3 valgus with intact medial collateral ligament (MCL), two had grade 3 valgus with incompetent MCL, 14 had grade 1 valgus, and five had post-traumatic valgus deformities. Over a two-year follow-up period, functional outcomes were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Knee Society Score (KSS), and complications were documented; however, radiological outcomes were not analyzed. RESULTS: Among 27 patients with Grade 2-3 valgus, the final cohort included 21 patients (24 knees). The mean age was 58.33 ± 9.63 years and 70.8% were female. Ten (41.7%) patients had rheumatoid arthritis and 14 (58.3%) had degenerative osteoarthritis (OA). The median surgical time was 68.00 (13.00) minutes, and the median blood loss was 478.45 (176.25) mL. The valgus grade was reduced from a baseline value of 22.43 ± 7.05 degrees to 5.26 ± 1.53 degrees at 6 weeks. The WOMAC scores improved from 67.58 ± 7.27 at baseline to 1.38 ± 0.57 in the second year post-operatively. Similarly, the KSS scores improved from 26.67 ± 10.34 at baseline to 181.96 ± 7.20 in the second year. One patient sustained a Type II supracondylar femur fracture after a fall, managed with distal femur arthroplasty, while another had delayed tibia pin tract healing, treated with antibiotics and dressings. CONCLUSION: RATKA facilitates precise correction of moderate to severe valgus deformity through enhanced surgical planning and execution, achieving adequate functional outcomes with minimal complications through the application of functional alignment philosophy.
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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 | 0.001 |
| 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 | 0.000 | 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".