Predictive analysis and risk assessment of Kümmell's disease in patients with osteoporotic vertebral compression fractures
10.3760/cma.j.cn121113-20231129-00341
- VernacularTitle:骨质疏松性椎体压缩骨折患者发生Kümmell病的风险预测
- Author:
Zengjing LIU
1
;
Linghong WU
;
Jiarui CHEN
;
Mingbo WANG
;
Xianglong ZHUO
;
Xiaozhong PENG
;
Xiangtao XIE
Author Information
1. 柳州市工人医院脊柱外科（广西骨科生物材料研发与临床转化重点实验室），柳州 545000
- Keywords:
Vertebral body;
Osteoporotic fractures;
Risk assessment;
Forecasting;
Kümmell's disease
- From:
Chinese Journal of Orthopaedics
2024;44(11):756-763
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze predictive risk indicators associated with the development of Kümmell's disease (KD) in patients with osteoporotic vertebral compression fractures (OVCFs).Methods:A 1∶1 frequency-matched case-control study design was employed, selecting patients who visited the Department of Spine Surgery at Liuzhou Workers' Hospital from January 2021 to June 2023. Patients were divided into case and control groups based on whether they progressed to Kümmell's disease (KD). Detailed demographic information, comorbidities, and laboratory data were collected, and baseline characteristics of the two groups were compared. Initial predictive variables significantly associated with the target variable were preliminarily screened through univariate analysis. A correlation heatmap was then constructed to assess collinearity among these variables, followed by further selection of potential predictors using the Lasso regression model. Finally, a multivariable logistic regression model was used for the prediction and analysis of KD-related risk indicators.Results:Univariate analysis identified significant predictors of Kümmell's disease, including patient age, bone mineral density, kyphotic Cobb angle, and multiple vertebral fractures. These were included in the subsequent Lasso regression analysis, which identified key predictors with non-zero coefficients: age, bone density, Cobb angle, multiple vertebral fractures, platelet count (PLT), aspartate aminotransferase/alanine aminotransferase (AST/ALT), albumin (Alb), albumin/globulin ratio (Alb/Glb), alkaline phosphatase (ALP), urea (UREA), serum uric acid (SUA), fibrinogen (Fn), blood glucose (BG), and C-reactive protein (CRP). The correlation heatmap revealed the correlation and collinearity risks between these variables, with ALT and AST/ALT showing a high correlation ( r=0.750) and PLT and Alb showing a low correlation ( r=-0.110). Multivariable logistic regression indicated that the presence of multiple vertebral fractures [ OR=2.078, 95% CI (1.072, 4.025), P=0.030], increased Cobb angle [ OR=1.033, 95% CI (1.008, 1.058), P=0.009], elevated levels of ALP [ OR=1.013, 95% CI(1.004, 1.023), P=0.006], and SUA [ OR=1.004, 95% CI (1.000, 1.007), P=0.043] were associated with an increased risk of KD in patients with OVCFs. Conversely, decreased levels of Fn [ OR=0.996, 95% CI (0.992, 0.999), P=0.008] were linked to an increased risk of KD. Conclusion:Multiple vertebral fractures, increased Cobb angle, elevated levels of ALP and SUA, along with decreased levels of Fn, can be used as early-warning indicators to predict whether patients with OVCFs will develop KD. Monitoring these indicators is crucial for the early detection and intervention in these patients.
