Robotic-arm assisted lateral unicompartmental knee arthroplasty: 5-Year outcomes & survivorship
Bibliographic record
Abstract
Introduction Robotic-arm assisted unicompartmental knee arthroplasty (RA-UKA) has demonstrated accurate component positioning and excellent outcomes for medial components. However, there is a paucity of literature on lateral compartment RA-UKA. The purpose of our study was to assess the midterm clinical outcomes and survivorship of lateral RA-UKA. Methods This study was a retrospective review of a single-center prospectively maintained cohort of 33 patients (36 knees) indicated for lateral UKA. Perioperative, and postoperative two- and five-year Knee injury Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Score (WOMAC), and Forgotten Joint Score (FJS) patient reported outcome measures were collected. Five-year follow-up was recorded in 29 patients (32 knees). Results Mean follow up was 5.1 ± 0.1 years. Mean age and BMI was 70.9 ± 7.2 years and 29.0 ± 4.2 kg/m2, respectively. At discharge, mean distance walked was 273.4 ± 70.4 feet, and mean pain score was 2.0 ± 2.5. At 2-year follow up, mean KOOS, WOMAC, and FJS were 75.1 ± 13.5, 15.0 ± 7.2, and 81.0 ± 23.3, respectively. At 5-year follow up, mean KOOS, WOMAC, and FJS were 75.3 ± 14.6, 14.9 ± 5.0, and 75.8 ± 27.4, respectively. Mean change in KOOS and WOMAC were 35.6 ± 27.1 and 11.7 ± 13.4 ( p< .001 and p< .001). 94% of patients were very satisfied/satisfied, 3% neutral, and 3% dissatisfied. 91% met activity expectations, and 59% were more active than before. Survivorship was 100% at 5 years. Discussion In this study, lateral RA-UKA demonstrated significantly improved clinical outcomes, high patient satisfaction, met expectations, and excellent functional recovery at midterm follow up. Comparative studies are needed to determine differences between robotic-assisted and conventional lateral UKA, as well as TKA.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".