Short‐term outcomes of 43 dogs treated with arthroscopic suturing for meniscal tears associated with cranial cruciate ligament disease
Bibliographic record
Abstract
OBJECTIVE: To describe short-term outcomes and complications in dogs receiving meniscal suturing and concurrent tibial plateau leveling osteotomy (TPLO) with or without augmentation with an extracapsular suture. STUDY DESIGN: Retrospective case series. ANIMALS: Forty-three client-owned dogs submitted for cruciate ligament disease. METHODS: Dogs were included if meniscal suturing was performed during or after a TPLO procedure. Criteria included an unstable medial meniscus without evidence of a tear, a caudal vertical longitudinal tear with or without displacement, or if a bucket-handle tear was debrided and the remaining rim was unstable. Stifle stabilization was performed by either a standard TPLO or an augmented TPLO (TPLO + internal brace [IB]). Outcome measures included physical examination findings, radiographs, subjective gait examination, Liverpool Osteoarthritis in Dogs (LOAD) scores, and second-look arthroscopy. RESULTS: Forty-four meniscal repairs were performed in 43 dogs. Five types of meniscal tears were treated employing eight suture materials. Complications were documented in 15 cases (34%). The stabilization technique had a significant impact on the outcome (p = .049): TPLO + IB had a 93.3% success rate and the success rate was 71.4% in the TPLO-only group. CONCLUSION: Five types of meniscal pathology were addressed successfully in the study, indicating that currently accepted criteria for meniscal suturing in dogs may be overly conservative. The majority of complications were not related to the meniscal suturing itself and did not compromise the outcome. The stifle stabilization technique had an impact on outcome. CLINICAL SIGNIFICANCE: The authors found arthroscopic meniscal suturing to be practical and successful in this patient population. Postoperative stifle stability had an impact on successful treatment.
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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 | 0.001 | 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".