Development of a Multivariable Model Based on Individual Risk Factors for Recurrent Lateral Patellar Dislocation

Area of Science:

• Orthopedic surgery
• Sports medicine
• Biomechanics

Background:

• Nonoperative treatment is standard for first-time patellar dislocation.
• Certain patients face a high risk of recurrent instability.
• A predictive model is needed to guide individualized management.

Purpose of the Study:

• Develop a multivariable model to identify patients at high risk for recurrent patellar dislocation.
• Guide clinical management based on individual risk assessment.
• Improve patient outcomes by optimizing treatment strategies.

Main Methods:

• A multivariable logistic regression model was developed using data from 291 patients across 4 institutions.
• Factors evaluated included patient history, physical examination, and imaging.
• Model performance was assessed using the area under the receiver operating characteristic curve (AUC).

Main Results:

• Key predictors for recurrent dislocation include age, contralateral patellar dislocation history, skeletal immaturity, lateral patellar tilt, TT-TG distance, Insall-Salvati ratio, and trochlear dysplasia.
• Factors like sex, injury mechanism, and other imaging parameters were not significant predictors.
• The multivariable model achieved an overall AUC of 71%.

Conclusions:

• The developed model can identify high-risk patients for recurrent patellar dislocation, potentially guiding early operative treatment.
• Optimizing management can reduce short-term disability and long-term risk of patellofemoral arthritis.
• Further prospective validation is required before clinical implementation.