OUTCOMES AND EXPERIENCE WITH FRESH OSTEOCHONDRAL ALLOGRAFT TRANSPLANTATION OF THE PATELLA: A FIVE-CASE SERIES
Bibliographic record
Abstract
Chondral defects on the patella are a difficult problem in the young active patient and there is no consensus on how to treat these injuries. Fresh osteochondral allografts are a valid option for the treatment of full-thickness osteochondral defects and can be used to restore joint function and reduce pain. The primary purpose of this study was to investigate the clinical and subjective outcomes of a series of patients following fresh osteochondral allograft transplantation for isolated chondral defects of the patella. A series of 5 patients underwent surgery using an open approach for graft transplantation. A strict protocol for the allograft tissue was followed. Transplant recipients must be aged All patients were female, with a mean age of 27.4 (SD 3.65). Knee ligament stability was similar pre- and post-operatively. Knee ROM assessment of flexion and extension demonstrated a less than 10° increase from pre to post-operative. Quadriceps girth measurements demonstrated a mean change of 0.5 cm from pre- to post-operative for the surgical limb. Post-operative radiographs demonstrated incorporation of the graft in 4/5 cases within 6-months of surgery. One patient developed fragmentation of the graft after 18-months, and one patient had a subsequent trochleoplasty for persistent pain. The mean KOOS domain scores demonstrated significant improvement (p Isolated chondral defects of the patella can cause substantial pain, reduced function, and can be challenging to address surgically. This series of 5 cases demonstrated improved function, KOOS and KSS for 4/5 patients. To our knowledge this is a novel biological procedural technique for this problem, which has shown promising results making it a viable treatment option for young active patients with osteochondral defects of the patella.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".