Development and validation of a predictive model for refracture among elderly patients with vertebral osteoporotic fractures

Abstract

Abstract Background The increasing incidence of and adverse events related to refracture among patients with vertebral osteoporotic fractures have attracted increasing attention. In order to carry out preventive strategy effectively, it is of great significance to identify the risk of refractures. In this study, we developed a prediction model to evaluate the risk of refracture after initial fragility fracture.Methods This prospective cohort study was conducted across four tertiary hospitals in Southwest China between April 2018 and December 2021. X-rays were used to diagnose fractures. Participants from 3 of 4 centers were development set and the 4th as a validation set. The discrimination and calibration of each model was assessed using the validation set.Results A total of 1632 patients were included in this study, of which 428 patients suffered a refracture. A total of 11 factors were identified as candidates for predicting refracture were age, rehabilitate, treatment regimen, alcohol consumption, BMI, duration of medication use, history of comorbidities, fall risk, and levels of BGP, TALP, and Hcy. The average AUC of the nomogram was 0.936 (0.92–0.952) in the training set and 0.922 (0.894–0.949) in the validation set. The values for sensitivity, specificity, and accuracy were 0.825, 0.908, and 0.885, respectively.Conclusion We identified 11 independent risk factors that impact refracture risk. These factors were diagramed in a nomogram and transform into online calculator, which can be used to evaluate the risk of refracture among patients with initial vertebral osteoporotic fractures.