In this Simini Small Animal Surgery Podcast episode, we continue our October 2025 orthopedic coverage by examining two forward-thinking studies on cranial cruciate ligament disease (CCLD) surgery. One leverages machine learning to predict postoperative risk, and the other offers precise geometric modeling for TPLO alternatives.

We cover:

✅ Low et al. — Development of the PROSPECT machine learning model, trained on 670 stifle cases to predict surgical and medical complications after TPLO and CCWO. The model achieved 92.3% accuracy for surgical complications and revealed that complex interactions—like surgeon + technique—were more predictive than any single risk factor. This opens the door for individualized risk scoring and targeted intraoperative interventions, including enhanced infection control strategies.

✅ Petchell et al. — A finite element modeling study evaluating a CORA-based CCWO technique (CCWO-CORA). Unlike older methods, this approach consistently delivered a post-op tibial plateau angle (TPA) of exactly 5.0°—regardless of breed or starting slope. By controlling the mechanical axis advancement (MAA) and wedge angle, the technique offers zero angular variability and preserved tibial length, with customizable MAA options to facilitate plating in steep-sloped breeds.

🎓 Journal Articles Discussed:

• Low et al. — Machine-learning prediction of postoperative complications
  after high tibial osteotomy for canine cranial
  cruciate ligament disease
• Petchell et al. — An in silico comparison of a novel CORA-based cranial
  closing wedge ostectomy methodology with three
  other techniques
  📚 From the October 2025 issue of Veterinary Surgery

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