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A clinical decision-making algorithm for posterolateral corner injuries of the knee: Development and internal
Horacio Rivarola1, Cristian Collazo1, Marcos Palanconi1
1Department of Orthopaedic Surgery, Knee Surgery Unit, Hospital Universitario Austral, Buenos Aires, Argentina.
Summary
A new algorithm helps surgeons decide on knee posterolateral corner (PLC) injury treatment. It uses varus laxity, dial test results, and posterior cruciate ligament (PCL) involvement to guide minimally invasive or anatomic reconstruction.
Area of Science:
- Orthopedic surgery
- Knee biomechanics
- Sports medicine
Background:
- Posterolateral corner (PLC) knee injuries present complex management challenges.
- Existing surgical strategies for PLC injuries lack standardized criteria.
- Variability in treatment approaches necessitates a refined decision-making framework.
Purpose of the Study:
- To develop and internally validate a clinical decision-making algorithm for posterolateral corner (PLC) knee injuries.
- To assess the outcomes of a minimally invasive reconstruction strategy for PLC injuries.
Main Methods:
- Retrospective analysis of 120 patients with PLC injuries (isolated or combined).
- Collected demographic, clinical, radiographic, and intraoperative data.
- Utilized multivariable logistic regression and bootstrap resampling for validation.
Main Results:
- A successful clinical outcome was achieved in 76.7% of patients at a mean follow-up of 24.8 months.
- Key predictors of unsuccessful outcomes included varus laxity >4 mm, positive dial test at 90°, and PCL involvement.
- The developed algorithm demonstrated good discrimination (AUC 0.81) and calibration.
Conclusions:
- An internally validated algorithm effectively guides surgical decisions for PLC knee injuries.
- The algorithm enables tailored selection between minimally invasive and anatomic reconstruction techniques.
- This approach optimizes patient selection for different surgical strategies based on instability patterns.
