Reliable improvements in participation in low‐impact sports following implantation of a patellofemoral inlay arthroplasty at mid‐term follow‐up
Bibliographic record
Abstract
PURPOSE: The aim of this study was, to investigate the rate of return to sports (RTS) and physical activity after implantation of PFIA and to identify factors predictive of improved postoperative sporting ability. METHODS: Sixty-two patients with a mean age of 46 ± 11 years, who underwent implantation of PFIA at the senior authors' institution, were enrolled. They were prospectively evaluated preoperatively and at a minimum of 2 years postoperatively with a mean follow-up of 60 ± 25 months. Clinical outcomes, return to sports and activity, type of sport or activity, subjective satisfaction, and frequency were evaluated by questionnaire. RESULTS: The transformed overall Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score improved from 67 ± 16 to 77 ± 19 (p = 0.003), Tegner activity scale results improved from 3 ± 2 points to 4 ± 1 points (p < 0.001), and scores on the visual analog scale (VAS) pain scale decreased from 6 ± 2 points to 3 ± 2 points (p < 0.001). The sports frequency increased from 1 ± 2 sessions to 2 ± 1 sessions per week (p = 0.001). Ninety-four percent of the patients who did not fail could return to the same or higher level of sports, with 74% of the patients reporting an improved ability to perform sports. No preoperative factors could be detected to significantly influence RTS after surgery. CONCLUSIONS: PFIA is a valid treatment option for the active patient with end-stage isolated patellofemoral OA. Reliable improvements in knee function, pain, and participation in low-impact sports were found. LEVEL OF EVIDENCE: IV.
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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 | 0.004 |
| 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) | 0.002 | 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".