Development and validation of a risk prediction model for rotator cuff tears following acute anterior shoulder dislocation

Following shoulder dislocation, injuries such as rotator cuff tear (RCT), axillary nerve injury, greater tuberosity (GT) fracture, Hill-Sachs lesion, and Bankart lesion frequently occur. This study aimed to develop and validate a clinical prediction model for the occurrence of RCT after acute anterior shoulder dislocation. This study included all patients with acute anterior shoulder dislocation who presented to the emergency orthopedics department of the same institution from July 2021 to March 2025. Lasso regression was used to select independent variables for the model. A logistic regression model was constructed for prediction. The model’s validity was assessed using the bootstrap method. This study ultimately included 310 patients with acute anterior shoulder dislocation, among whom 110 were confirmed to have RCT. Logistic regression revealed significant associations between RCT post-dislocation and the following factors: age(p<.001, OR = 1.06), male gender (p=.016, OR = 2.58), GT fracture (p<.001, OR = 3.84), glenoid injury (p<.001, OR = 9.34), Hill-Sachs lesion (p=.035, OR = 6.01), and critical shoulder angle (CSA) (p<.001, OR = 1.43). The area under the ROC curve (AUC) for the prediction model was 0.940 (95% CI = 0.9147–0.9654). This study identified risk factors for RCT following acute shoulder dislocation. The findings may assist orthopedic surgeons in identifying patients at high risk for RCT after shoulder dislocation. When MRI is not readily available in clinical practice, our prediction model can help reduce the rate of missed diagnoses of post-dislocation RCT. Ⅲ