Effect of surgical technique on limb function after surgery for rupture of the cranial cruciate ligament in dogs
Bibliographic record
Abstract
OBJECTIVE: To determine the outcome and effect of surgical technique on limb function after surgery for rupture of the cranial cruciate ligament (RCCL) and injury to the medial meniscus in Labrador Retrievers. STUDY DESIGN: Prospective clinical study. ANIMALS: 131 Labrador Retrievers with unilateral RCCL and injury to the medial meniscus and 17 clinically normal Labrador Retrievers. PROCEDURE: Affected dogs had partial or complete medial meniscectomy and lateral suture stabilization (LSS), intracapsular stabilization (ICS), or tibial plateau leveling osteotomy (TPLO). Limb function was measured before surgery and 2 and 6 months after surgery. Treated dogs were evaluated to determine the probability that they could be differentiated from clinically normal dogs and tested to determine the likelihood that they achieved improvement. RESULTS: No difference was found between LSS or TPLO groups, but dogs treated with ICS had significantly lower ground reaction forces at 2 and 6 months. Compared with clinically normal dogs only, 14.9% of LSS-, 15% of ICS-, and 10.9% of TPLO-treated dogs had normal limb function. Improvement was seen in only 15% of dogs treated via ICS, 34% treated via TPLO, and 40% treated via LSS. CONCLUSIONS AND CLINICAL RELEVANCE: Surgical technique can influence limb function after surgery. Labrador Retrievers treated via LSS, ICS, or TPLO for repair for of RCCL and medial meniscal injury managed with partial or complete meniscectomy infrequently achieve normal function. Results of LSS and TPLO are similar and superior to ICS.
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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 | 0.001 |
| 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 | 0.000 | 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".