Autologous Osteochondral Grafting (Mosaic Arthroplasty) for Treatment of Subchondral Cystic Lesions in the Equine Stifle and Fetlock Joints
Bibliographic record
Abstract
OBJECTIVE: To describe treatment of equine subchondral bone cysts (SBCs) by reconstruction of the articular surface with osteochondral grafts. STUDY DESIGN: Case series of horses with SBCs unresponsive to conservative therapy. ANIMALS: Eleven horses (1-12 years). METHODS: SBCs were identified in 4 locations: medial femoral condyle (5 horses), lateral femoral condyle (1), distal epiphysis of the metacarpus (4), or metatarsus (1). Osteochondral autograft transplantation (mosaic arthroplasty) was performed, taking grafts from the abaxial border of the medial femoral trochlea of the unaffected limb. Graft implantation was achieved through a small arthrotomy or by arthroscopy depending on SBC location. RESULTS: All horses improved postoperatively; 10 horses had successful outcomes with radiographic evidence of successful graft incorporation and 7 returned to a previous or higher activity level. On follow-up arthroscopy (5 horses) there was successful reconstitution of a functional gliding surface. One horse had delayed incorporation of a graft because of a technical error but became sound. One horse had recurrence after 4 years of work and soundness. One stallion was used for breeding and light riding because of medial meniscal injuries on the same limb. CONCLUSIONS: Implantation of osteochondral grafts should be considered for SBC when conservative management has not improved lameness and there is a risk of further joint injury and degeneration. CLINICAL RELEVANCE: Mosaic arthroplasty should be considered for treatment of subchondral bone cysts of the femoral condyle and distal articular surface of the metacarpus/tarsus in horses that are refractory to non-surgical management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".