Developing a Nomogram for Predicting the Probability of Shoulder Redislocation after the First Episode in Young Patients - Chih-Kai Hong; Chin Kuo; Chia-Li Chang; Wei-Ren Su; Ta-Wei Tai (Formosan Journal of Musculoskeletal Disorders)
Background: The recurrence rate of shoulder dislocation is high, and the male sex and young age have been recognized as risk factors. A personalized model for predicting the probability of shoulder redislocation would be useful in clinical practice. Objectives: We aimed to establish a prediction model for estimating the redislocation probability within 5 years after nonsurgical management for the first-time episode in young patients. Materials and Methods: With the use of a nationwide administrative database, patients aged 13–50 years with a diagnosis of primary shoulder dislocation receiving closed reduction from January 1, 2000, to December 31, 2013, were extracted. We apportioned the data into training and validation sets with a 2:1 split. The putative prognostic predictors, including age, sex, diabetes mellitus, hypertension, hyperlipidemia, and Charlson Comorbidity Score, were identified and analyzed in a nomogram. Penalized Cox regression with the adaptive elastic-net variable selection method was utilized to construct a nomogram. Results: A total of 461 patients were included in this study. After regression analysis, age and sex were incorporated into the nomogram. After the model training, a nomogram for prediction was developed; the AUC of this model ranged from 0.704 to 0.751. The calibration plots for the endpoints showed optimal agreement between the nomogram’s prediction and the actual observation. Conclusions: The present study proposed a nomogram that can be used to predict the probability of shoulder redislocation within 5 years after nonsurgical treatment for the first shoulder dislocation.