Antebrachial Deformity Correction Combined with Osteotomized Pancarpal Arthrodesis Using Patient-Specific Guides and a Custom Printed Implant in a Dog
Bibliographic record
Abstract
Abstract This case report describes individualized treatment for a 4-year-old, 26 kg, Labrador–Springer crossbreed dog affected by chronic antebrachial growth deformity (ABGD) and recent acute carpal hyperextension injury. On the basis of a CT scan, patient-specific osteotomy guides (PSG) were designed for a diaphyseal radial ostectomy to correct the ABGD, as well as for distal radial and proximal radiocarpal and ulnar carpal bone ostectomies to arthrodese the antebrachiocarpal joint. A patient-specific 3D-printed titanium alloy implant (PSI) was applied to the dorsal aspect using the PSG pin holes as screw holes and the entire plate as a reduction device. Distally, the plate was applied to metacarpal bones II, III, and IV. At 2-month follow-up, the patient had returned to normal function, all implants were stable, and at 13 months, bone fusion was documented radiographically. When performing pancarpal arthrodesis, one might consider ostectomies (rather than burring) to increase the area of cancellous bone contact. Additional potential advantages of a PSG-PSI system include accurate limb alignment, improved distal fixation, and reduced surgical time. Carefully planned and executed single-session ABGD-correction and PCA resulted in an excellent long-term outcome in this large breed dog.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".