Analysis of the natural collapse course of non-traumatic osteonecrosis of the femoral head based on the matrix model

Author:

Zhao Rushun,Wang Mengfei,Hao Yangquan,Xu Peng,Lu Chao

Abstract

Abstract Background There are many predictions about the progression of natural collapse course of osteonecrosis of the femoral head. Here, we aimed to combine the three classical prediction methods to explore the progression of the natural collapse course. Methods This retrospective study included 127 patients admitted to our hospital from October 2016 to October 2017, in whom the femoral head had not collapsed. Logistic regression analysis was performed to determine the collapse risk factors, and Kaplan–Meier survival curves were used for femoral head survival analysis. The collapse rate of the femoral head was recorded within 5 years based on the matrix model. The specificity of the matrix model was analyzed using the receiver operating characteristic curve. Results A total of 127 patients with a total of 202 hips were included in this study, and 98 hips collapsed during the follow-up period. Multivariate logistics regression analysis showed that the predictive ability of the matrix model was stronger than Association Research Circulation Osseous staging, Japanese Investigation Committee classification, and area (P < 0.05). Kaplan–Meier survival curve showed that the median survival time of femoral head in patients was 3 years. The result of the receiver operating characteristic curve analysis showed that the area under the curve (AUC) of the matrix model had better predictive value (AUC = 0.771, log-rank test: P < 0.001). Conclusion We creatively combined the three classical prediction methods for evaluating the progression of the natural collapse course based on the matrix model and found that the higher the score of the matrix model, the higher the femoral head collapse rate. Specifically, the matrix model has a potential value in predicting femoral head collapse and guiding treatment selection.

Funder

the National Postdoctoral Fund of China

Publisher

Springer Science and Business Media LLC

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