Surgical Technique and Initial Clinical Experience with a Novel Extracapsular Articulating Implant for Treatment of the Canine Cruciate Ligament Deficient Stifle Joint
Bibliographic record
Abstract
OBJECTIVE: To describe the surgical technique, clinical efficacy, and complications using the Simitri Stable in Stride(®) extracapsular articulating implant (EAI) to treat naturally occurring stifle instability due to cranial cruciate ligament (CrCL) insufficiency. STUDY DESIGN: Prospective case series. ANIMALS: Client-owned dogs with CrCL-deficient stifles (n=60 dogs; 66 stifles). METHODS: An EAI was applied to the medial aspect of the distal femur and proximal tibia after stifle exploration and treatment of joint pathology. Outcome measures included lameness score, time to weight bearing, and bilateral assessment of stifle stability, stifle range of motion (ROM), and thigh circumference (TC). Outcome measures were determined preoperatively and at intervals from 4.5 to 16.0 months (median 8.9 months) postoperatively. Data were excluded from bilaterally affected dogs <6 months after CrCL surgery on the contralateral limb, and from dogs with contralateral limb lameness. RESULTS: Within 24 hours of EAI surgery, dogs were weight bearing on 64 of 66 limbs at the walk. Incidence of major complications requiring surgical revision was 15.3% and minor complications was 10.2%. Postoperatively, there were significant improvements in lameness scores and ROM in 34 EAI-treated limbs meeting inclusion criteria, and the mean ROM returned to within normal limits. TC did not change in the operated limb, but decreased significantly in the control limb. CONCLUSION: The EAI effectively stabilized the CrCL-deficient stifle, and significantly improved lameness scores and stifle ROM. Decreased TC in control limbs may have been due to early return to mobility and weight bearing on the EAI-treated limb.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".