The use of an imageless robotic system in revision of unicompartmental knee arthroplasty
Bibliographic record
Abstract
PURPOSE: The application of robotics in revision arthroplasty particularly from unicompartmental knee arthroplasty (UKA) to total knee arthroplasty (TKA), is underexplored. The purpose of this study is to describe the surgical technique of an imageless robotic system used in the revision of UKA to TKA and to evaluate short- to mid-term outcomes. METHODS: This prospective study includes 35 patients treated from May 2020 to July 2023. Demographic data of the patients were gathered and the reasons for needing revision surgery were assessed. All patients were clinically evaluated preoperatively and at the final follow-up of 31.3 ± 12.1 months, using the Western Ontario and McMaster Universities Arthritis Index (WOMAC), Oxford Knee Score (OKS), Forgotten Joint Score (FJS-12), Numerical Rating Scale (NRS) and range of motion (ROM). Additionally, a radiographic evaluation was performed, and implant survival was assessed by analyzing complications at final follow-up. RESULTS: In 88.6% of the patients, a primary Posterior Stabilized (PS) or Constrained Posterior Stabilized prosthetic implant was used, with 11.4% of patients requiring a varus-valgus constraint implant. In 71.4% of the cases, a thinnest size liner of 10 mm was used. The use of the robotic system was never aborted for any reason. At final follow-up, the implant survival rate was 97.14%. Average OKS increased from 31.4 ± 9.4 to 41.5 ± 4.3, FJS-12 from 47.3 ± 19.3 to 80.7 ± 8.9; WOMAC at final follow-up was 17.8 ± 8.7, from 53.5 ± 21.3 preoperatively. Analyzing ROM, NRS and patient-reported outcome measures, there were significant differences in each parameter between prerevision surgery and final follow-up. CONCLUSIONS: This study highlights that in a cohort of patients undergoing robotic-assisted conversion from UKA to TKA, the use of an imageless procedure incorporating intraoperative bone morphing and alignment based on a functional philosophy has proven to be safe and has yielded excellent clinical and radiographic outcomes. LEVEL OF EVIDENCE: Level II, prospective cohort study.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".