目的 探讨骨质疏松性椎体压缩骨折(osteoporotic vertebral compression fracture，OVCF)术后再骨折风险，构建风险预测模型，确定有效防治措施。方法 选取2021年8月至2022年6月北京积水潭医院收治的119例OVCF患者作为研究对象，根据术后再骨折与否分为再发组和非再发组，其中再发组22例，男11例，女11例;年龄55～86岁，平均(72。02±5。58)岁。非再发组97例，男50例，女47例;年龄55～86岁，平均(70。79±6。81)岁。统计两组一般资料，采用Lasso-Logistic回归模型筛选OVCF术后再发骨折自变量，采用赤池信息准则(Akaike's information criterion，AIC)、贝叶斯信息准则(Bayesian information criterion，BIC)比较全变量 Logistic 回归、逐步Logistic、Lasso-Logistic回归预测效能，构建诺莫图模型，采用受试者工作特征曲线(receiver operating characteristic，ROC)、校准曲线分析OVCF术后再发骨折诺莫图模型效能。结果 术后随访8～20个月，平均(12。00±2。40)个月。单因素分析显示，再发组身体质量指数(body mass index，BMI)、骨密度T值、抗酒石酸酸性磷酸酶(tartrate-resistant acid phosphatase 5b，TPACP-5b)、核因子 kB 受体激活因子配体(receptor acti-vator nuclear factor kappa B ligand，RANKL)、骨保护素(osteoprotegrin，OPG)、术后抗骨质疏松治疗、白细胞介素(interleukin，IL)-17、长期糖皮质激素使用史、脊柱畸形指数(spinal deformity index，SDI)值、手术段Cobb角、后凸角度与非再发组比较，差异有统计学意义(P＜0。05);Lasso-Logistic回归模型分析显示lambda。lse值0。049为最优模型，此时进入模型的变量涉及骨密度、SDI值、IL-17、术后抗骨质疏松治疗，经BIC、AIC验证表明所构建模型拟合和预测效果相对较好;诺莫图模型的ROC下面积(area under the curve，AUC)为0。865，敏感度及特异度分别为95。45％、68。04％，且校准曲线显示，其预测效能与实际吻合较好。结论 OVCF术后再骨折的发生受围手术期多方面影响，涉及骨密度T值、SDI值、IL-17、术后抗骨质疏松治疗，基于以上因素可有效预测患者再骨折风险，为临床防治再骨折提供参考依据。
Establishing a Prediction Model for Post-Operative Refracture of Osteoporotic Vertebral Compression Fractures
Objective To investigate the risk of refracture after osteoporotic vertebral compression fracture(OVCF)surgery,construct a risk prediction model,and identify effective prevention and treatment measures.Methods A total of 119 patients with OVCF admitted to Beijing Jishuitan Hospital from August 2021 to June 2022 were selected as the research subjects.According to the occurrence of postoperative refracture,they were divided into a recurrent group and a non-recurrent group.The recurrent group comprised 22 patients(11 males and 11 females)with a mean age of(72.02±5.58)years,while the non-recurrent group consisted of 97 patients(50 males and 47 females)with a mean age of(70.79±6.81)years.Statistical analysis was conducted on the general characteristics of both groups.The Lasso-Logistic regression model was used to screen the independent variables of recurrent fractures after OVCF surgery.The Akaike's information criterion(AIC)and Bayesian information criterion(BIC)were used to compare the predictive performance of full variable logistic regression,stepwise logistic regression,and Lasso-Logistic regression.The nomogram model was constructed,and the receiver operating characteristic(ROC)and calibration curve were used to analyze the performance of the nomogram model for recurrent fractures after OVCF surgery.Results After a follow-up period ranging from 8 to 20 months,with a mean duration of(12.00±2.40)months.Univariate analysis revealed significant differences between the refracture and non-refracture groups in terms of body mass index(BMI),bone mineral density T-score,tartrate-resistant acid phosphatase 5b(TPACP-5b),receptor activator of nuclear factor kappa B ligand(RANKL),osteoprotegerin(OPG),postoperative anti-osteoporosis treatment,interleukin(IL)-17,history of long-term glucocorticoid use,spinal deformity index(SDI)value,surgical segment Cobb angle,kyphosis angle,and number of operated vertebral bodies(P＜0.05).The Lasso-Logistic regression model analysis identified an optimal lambda.lse value of 0.049,at which point the variables included in the model were bone density,SDI value,IL-17,and postoperative anti-osteoporosis treatment.Validation using BIC and AIC confirmed the good fitting and predictive capabilities of the constructed model.The nomogram model demonstrated an area under the receiver operating characteristic curve(AUC)of 0.865,with a sensitivity of 95.45％and a specificity of 68.04％.Additionally,the calibration curve indicated a close alignment between the model's predictions and actual outcomes.Conclusion The occurrence of postoperative re-fracture after OVCF is affected by various aspects during the perioperative period,including BMD T-value,SDI value,Cobb angle of the operated segment,IL-17,posterior convexity angle,postoperative anti-osteoporosis treatment,and the number of operated vertebral bodies,based on which the risk of re-fracture of the patients can be predicted effectively,providing a reference basis for the prevention and treatment of re-fracture in the clinic.
spinal deformity index valueosteoporotic vertebral compression fracturepostoperative refractureriskprediction model
万方数据
维普
