Objective:To screen the key risk factors for secondary scapulohumeral periarthritis in patients with rotator cuff tear based on LASSO-Logistic regression analysis,construct a visual nomogram prediction model,and evaluate the discrimination and calibra-tion of the model through internal or external verification,so as to provide an individualized risk assessment tool for clinical practice.Methods:The clinical data of 84 patients with rotator cuff injury(including 30 patients with secondary scapulohumeral periarthritis and 54 patients without secondary scapulohumeral periarthritis)were retrospectively analyzed.Logistic regression analysis was employed to identify risk factors for secondary scapulohumeral periarthritis in patients with rotator cuff injury,and the predictive weights were visual-ized using a nomogram.The receiver operating characteristic(ROC)curve and DeLong test were utilized to assess the predictive per-formance of the model for secondary scapulohumeral periarthritis in patients with rotator cuff injury.Results:The results of LASSO-Lo-gistic regression analysis showed that Degenerative injury,diabetes mellitus,Goutallier classification(grade Ⅲ-Ⅳ),tear size(large),Patte classification(grade Ⅲ),joint capsule thickness(thick),high expression of C-reactive protein(CRP)and erythrocyte sedimen-tation rate(ESR),low expression of 25-hydroxyvitamin D[25(OH)D]were the risk factors of secondary scapulohumeral periarthritis in patients with rotator cuff injury Factors(P＜0.05).The nomogram analysis revealed that the Goutallier grade(grades Ⅲ-Ⅳ),tear size(large),Patte grade(grade Ⅲ),and joint capsule thickness(thick)were the most significant factors influencing secondary scapu-lohumeral periarthritis in patients with rotator cuff injuries.These were followed by degenerative damage,diabetes mellitus,high levels of CRP and ESR expression,and low levels of 25(OH)D expression.The area under the ROC curve of the nomogram was 0.891.Delong test results showed that the learning set and test set were 0.943 and 0.952,respectively,and there was no significant difference between the predicted value and the actual observed value(P＞0.05).Conclusion:The nomogram model based on LASSO-Logistic regression analysis has a good predictive effect on secondary scapulohumeral periarthritis in patients with rotator cuff injury.