| 林渺满,文雪梅,黄宗伟,于晓兵.骨质疏松性椎体压缩骨折椎体强化术后残余腰背痛风险预测模型的构建与验证[J].中国脊柱脊髓杂志,2022,(8):720-728. |
| 骨质疏松性椎体压缩骨折椎体强化术后残余腰背痛风险预测模型的构建与验证 |
| 中文关键词: 骨质疏松性椎体压缩骨折 椎体强化术 残余腰背痛 预测模型 |
| 中文摘要: |
| 【摘要】 目的：分析骨质疏松性椎体压缩骨折（osteoporotic vertebral compression fractures，OVCFs）患者椎体强化术（vertebral augmentation，VA）后残余腰背痛的独立危险因素，建立相关风险预测模型并进行验证。方法：本研究回顾了2016年12月～2021年2月在本院接受VA的377例OVCFs患者的临床资料，平均年龄75.63±7.27岁（65～94岁），男性52例，女性325例。收集患者的一般资料[性别、年龄、骨密度（bone mineral density，BMD）等]、手术和影像学资料、术前及术后合并症等相关信息，术前、术后1d、出院前、术后3个月、6个月时的视觉模拟（visual analog scale，VAS）评分和Oswestry功能障碍指数（Oswestry disability index，ODI）。将术后残余腰背痛定义为术后1d原疼痛部位附近仍存在中等程度以上的腰背部疼痛（VAS评分≥4分），按照定义将患者分为残余痛组64例，对照组313例。通过单因素分析联合Lasso回归确定最佳Logistic回归模型后进行多因素分析，探寻术后残余腰背痛的独立危险因素，进而构建Nomogram模型。应用Bootstrap完成模型内部验证，采用受试者工作特征（receiver operating characteristic，ROC）曲线、校准曲线及决策曲线分析（decision curve analysis，DCA）分别评估模型预测性能与临床实用性。结果：单因素分析及Lasso回归交叉验证最佳模型显示患者术前BMD、术前腰椎间盘突出症、术前胸腰筋膜（thoracolumbar fascia，TLF）损伤、术中小关节损伤（facet joint injury，FJI）、术后骨水泥未完全粘合骨折线是残余痛的潜在危险因素。进一步行多因素Logistic回归分析，发现上述变量仍是术后残余腰背痛的独立危险因素（P<0.05）。构建Logistic回归的可视化Nomogram模型，利用ROC曲线求出模型的C指数为0.8384（95%CI：0.7855～0.8912），经过200次Bootstrap抽样内部验证，得出C指数为0.8326；校准曲线显示预测概率曲线与实际概率曲线接近；DCA曲线显示在1%～53%的阈值范围内，决策曲线位于None线与All线上方。结论：术前低BMD、术前腰椎间盘突出症、术前TLF损伤、术中FJI、术后骨水泥未完全粘合骨折线是OVCFs患者行VA术后残余腰背痛的独立危险因素。上述5个因素作为预测因子构建的风险预测模型对术后残余腰背痛的预测性能及临床实用性较好。 |
Development and validation of a prediction model for the risk of residual low back pain after vertebral augmentation for osteoporotic vertebral compression fractures |
| 英文关键词:Osteoporotic vertebral compression fractures Vertebral augmentation Residual low back pain Prediction model |
| 英文摘要: |
| 【Abstract】 Objectives: To investigate the independent risk factors of residual lower back pain after vertebral augmentation(VA) in patients with osteoporotic vertebral compression fractures(OVCFs), and to develop and validate an associated risk prediction model. Methods: This study reviewed clinical data of 377 patients with OVCFs who received VA at our hospital from December 2016 to February 2021. There were 52 males and 325 females, aged 75.63±7.27(65-94) years old. Information regarding patients′ general information[gender, age, bone mineral density(BMD), et al], surgical and imaging data, preoperative and postoperative comorbidities, as well as visual analog scale(VAS) scores and Oswestry disability index(ODI) at preoperation, postoperative 1 day, pre-discharge, 3 months and 6 months postoperatively were collected. Postoperative residual low back pain was defined as moderate or more low back pain(VAS≥4) near the original pain site 1 day after surgery, and according to such definition, the patients were divided into residual pain group with 64 cases and the control group with 313 cases. The univariate analysis was combined with Lasso regression to determine the optimal Logistic regression model for multivariate analysis to explore the independent risk factors of postoperative residual low back pain, after which a Nomogram model was constructed. Bootstrap was applied to complete the internal validation of the model. The receiver operating characteristic(ROC) curve, calibration curve, and decision curve analysis(DCA) were used to evaluate the predictive performance and clinical practicability of the model, respectively. Results: Univariate analysis and Lasso regression cross-validation of the best model showed that preoperative BMD, preoperative lumbar disc herniation, preoperative thoracolumbar fascia(TLF) injury, intraoperative facet joint injury(FJI), and postoperative incomplete cementing of the fracture line were the potential risk factors for residual pain. Further multivariate Logistic regression analysis showed that the above variables were also the independent risk factors for postoperative residual low back pain(P<0.05). The visual Nomogram model of the Logistic regression was constructed, of which the C index calculated by using the ROC curve was 0.8384(95%CI: 0.7855-0.8912). After 200 times of Bootstrap sampling internal verification, the C index was 0.8326. The calibration curve showed that the predicted probability curve was close to the actual probability curve. And the DCA curve was within the threshold range of 1%-53%, the decision curve was above the None line and the All line. Conclusions: Preoperative low BMD, preoperative lumbar disc herniation, preoperative TLF injury, intraoperative FJI, and postoperative incomplete cementing of the fracture line are independent risk factors for residual low back pain after VA in patients with OVCFs. The prediction model, constructed with the above five predictive factors, has good predictive performance and clinical practicability in predicting postoperative residual low back pain. |
| 投稿时间：2022-05-05 修订日期：2022-08-05 |
| DOI： |
| 基金项目:大连市科技创新基金项目（2021JJ13SN68）；大连市医学重点专科“登峰计划”建设项目（大卫发[2021]243号） |
|
| 摘要点击次数: 3412 |
| 全文下载次数: 2542 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |
|
|
|
