Improved clinical outcomes and a low rate of failure following implantation of a patellofemoral inlay arthroplasty model featuring an enlarged lateral offset – a prospective clinical and radiographic evaluation at short term follow-up
Bibliographic record
Abstract
PURPOSE: To prospectively evaluate clinical, functional, radiographic, and sports-related short-term outcomes following isolated patellofemoral inlay arthroplasty (PFIA) utilizing an inlay arthroplasty model featuring an enlarged lateral offset. METHODS: Kahuna Prosthesis (Anika Therapeutics, Franklin, MA, USA) between January 2017 and July 2020 were included in the study and assessed both preoperatively and at a minimum follow-up of 24 months postoperatively. Patient-reported outcomes measures (PROs) included the transformed Western Ontario and McMaster Universities Arthritis Index (WOMAC), Visual Analogue Scale (VAS) for pain, and Tegner Activity Scale. The Kellgren-Lawrence grading scale was used to assess tibiofemoral osteoarthritis (OA) progression. The Caton-Deschamps Index was used to assess differences in pre- to postoperative patellar height. RESULTS: Eighteen patients (19 knees, 86% follow-up) were available at 28.2 ± 9.1 (range 24.0-55.0) months. WOMAC score (55.8 ± 16.0 to 77.2 ± 17.0; p <.001) and VAS for pain (6.1 ± 2.3 to 2.7 ± 2.1; p <.001) improved statistically significantly from pre- to postoperative whereas the mean Tegner Activity Scale (2.5 ± 1.3 to 3.1 ± 1.3; p >.05) improved slightly. No significant progression of tibiofemoral OA (p >.05) or changes in patellar height (p >.05) were observed. No implant-related maltracking or patellar instability was reported. One patient (5.3%) required revision surgery due to aseptic component loosening. CONCLUSION: Isolated patellofemoral inlay arthroplasty (PFIA) utilizing an implant with an enlarged lateral offset has been shown to be an effective and safe intervention for patients with symptomatic patellofemoral osteoarthritis. The procedure significantly improved knee function and pain relief, with low failure rates observed at short-term follow-up. LEVEL OF EVIDENCE: 4, prospective case series.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".