'À la carte' treatment algorithm for patellofemoral instability.

Area of Science:

• Orthopedics
• Knee Surgery
• Biomechanical Engineering

Background:

• Patellar instability presents complex challenges in treatment.
• Identifying pre-operative risk factors is crucial for successful surgical outcomes.
• Current decision-making processes can be difficult for surgeons.

Purpose of the Study:

• To present a treatment algorithm from the Lyon School of Knee Surgery.
• To guide surgeons in identifying imaging risk factors for treatment failure.
• To propose a therapeutic plan focused on correcting major risk factors.

Main Methods:

• Development of a treatment algorithm based on the Lyon School of Knee Surgery principles.
• Utilizing imaging to identify specific risk factors associated with patellar instability.
• Tailoring therapeutic strategies to address identified major risk factors.

Main Results:

• The algorithm provides a structured approach to patellar instability management.
• Identifies key imaging markers predictive of surgical treatment failure.
• Facilitates personalized treatment plans by addressing specific patient risk factors.

Conclusions:

• The Lyon School of Knee Surgery algorithm aids in optimizing treatment decisions for patellar instability.
• Accurate identification of imaging risk factors improves surgical planning.
• A tailored approach focusing on correcting major risks enhances patient outcomes.