5-Year Survivorship and Outcomes of Robotic-Arm-Assisted Medial Unicompartmental Knee Arthroplasty
Bibliographic record
Abstract
Purpose. While unicompartmental knee arthroplasty (UKA) has demonstrated benefits over total knee arthroplasty (TKA) in selected populations, component placement continues to be challenging with conventional surgical instruments, resulting in higher early failure rates. Robotic-arm-assisted UKA (RA-UKA) has shown to be successful in component positioning through preop planning and intraop adjustability. The purpose of this study is to assess the 5-year clinical outcomes of medial RA-UKA. Methods. This study was a retrospective review of a single-center prospectively maintained cohort of 133 patients (146 knees) indicated for medial UKA from 2009 to 2013. Perioperative data and 2- and 5-year Knee injury Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Score (WOMAC), and Forgotten Joint Score (FJS) outcome measures were collected. Five-year follow-up was recorded in 119 patients (131 knees). Results. Mean follow-up was 5.1 ± 0.2 years. Mean age and BMI were 68.0 ± 8.1 years and 29.3 ± 4.7 kg/m2, respectively. At 2-year follow-up, mean KOOS, WOMAC, and FJS were 71.5 ± 15.3 , 14.3 ± 7.9 , and 79.1 ± 25.8 , respectively. At 5-year follow-up, mean KOOS, WOMAC, and FJS were 71.6 ± 15.2 , 14.2 ± 7.9 , and 80.9 ± 25.1 , respectively. Mean change in KOOS and WOMAC was 34.6 ± 21.4 and 11.0 ± 13.6 , respectively ( p < 0.001 and p < 0.001 ). For patient satisfaction at last follow-up, 89% of patients were very satisfied/satisfied and 5% were dissatisfied. For patient activity expectations at last follow-up, 85% met activity expectations, 52% were more active than before, 25% have the same level of activity, 23% were less active than before, and 89% were walking without support. All patients returned to driving after surgery at a mean 15.2 ± 9.4 days. Survivorship was 95% (95% CI 0.91-0.98) at 5 years. One knee (1%) had a patellofemoral revision, two knees (1.3%) were revised to different partial knee replacements, and five knees (3.4%) were converted to TKA. Conclusion. Overall, medial RA-UKA demonstrated improved patient-recorded outcomes, high patient satisfaction, met expectations, and excellent functional recovery. Midterm survivorship was excellent. Longitudinal follow-up is needed to evaluate long-term outcomes of robotic-arm-assisted UKA procedures.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".