单节段后路腰椎椎间融合皮质骨轨迹螺钉固定术后螺钉松动的危险因素分析及预测模型的构建与验证

Risk factors of cortical bone trajectory screw loosening after single segment posterior lumbar interbody fusion and construction and validation of a predictive model

中文关键词:  后路腰椎间融合  螺钉松动  皮质骨轨迹  列线图  冠状角  皮质骨接触层

英文关键词:Posterior lumbar interbody fusion  Screw loosening  Cortical bone trajectory  Nomogram  Coronal angle  Cortical bone contact layer

中文摘要:

  【摘要】 目的：调查分析应用皮质骨轨迹（CBT）螺钉行单节段后路腰椎间融合术（PLIF）后螺钉松动的危险因素，建立并验证可视化的列线图预测模型。方法：回顾性选择2020年3月～2023年6月我院行单节段PLIF治疗的102例患者为研究对象，应用CBT螺钉共357枚，平均3.5±0.3枚。术后随访时间2.0~35.0个月，中位时间22.5个月。根据腰椎CT扫描结果将螺钉松动定义为CT片上超过1mm的连续透明区，周围存在薄的硬化区。将102例患者分为松动组45例和无松动组57例，应用的357枚螺钉中，117枚出现松动和240枚无松动。比较两组患者的人口学资料（包括性别、年龄、体质量指数、骨密度值）、手术指标[包括时间、出血量、腰椎融合分级、Oswestry功能障碍指数（ODI）]和放射学参数[包括螺钉固定到骶椎第一节椎体S1（FS1）、螺钉小梁Houns-field单位（HU）、螺钉的矢状角（SA）、冠状角（CA）和皮质骨接触层（CBCL）]。分别采用Lasso回归和多因素Logistic回归分析模型筛选螺钉松动的最佳独立危险因素，采用R软件建立列线图模型，然后分别采用Bootstrap法、受试者工作特征（ROC）曲线、校准曲线及决策曲线分析（DCA）评估模型的预测稳定性[一致性指数（C指数）]、预测区分度（敏感性和特异性）、预测概率的准确性（吻合程度）、临床净获益。结果：松动组患者的骨密度值明显小于无松动组（P＜0.05），其他人口学资料和手术指标比较差异无统计学意义（P＞0.05）。与无松动组比较，松动组的FS1百分比和CA明显升高，CBCL显著下降（P＜0.05）。骨密度值（OR=0.44，95%CI=0.21~0.89，P＜0.001）、FS1（OR=3.12，95%CI=2.03~4.54，P＜0.001）、CA（OR=1.45，95%CI=1.12~2.03，P＜0.001）和CBCL（OR=0.67，95%CI=0.32~0.88，P＜0.001）是单节段PLIF后发生螺钉松动的独立危险因素。列线图模型总分140分，Bootstrap法计算C指数为0.856（P=0.125），ROC曲线下面积（AUC）为0.847（95%CI=0.801~0.912，P＜0.001），校准曲线和DCA均显示模型的预测结果有较好的一致性和临床净获益比。结论：骨密度值、FS1、CA和CBCL是应用CBT螺钉行单节段PLIF后发生螺钉松动的独立危险风险，据此构建的列线图模型在临床早期筛选螺钉松动高风险群体中有一定的应用价值。

英文摘要:

  【Abstract】 Objectives: To investigate and analyze the risk factors of screw loosening after single segment posterior lumbar interbody fusion(PLIF) with cortical bone trajectory(CBT) screw, and to establish and validate a visualized nomogram predictive model. Methods: A retrospective study was conducted on 102 patients undergone single-segment PLIF in our hospital from March 2020 to June 2023, and a total of 357 CBT screws were placed, averaged 3.5±0.3 per patient. The postoperative follow-up time was 2.0-35.0 months, with a median of 22.5 months. On the basis of lumbar CT scans, screw loosening was defined as a continuous transparent area exceeding 1mm, surrounded with thin sclerotic areas. The patients were divided into loosening group of 45 cases and non-loosening group of 57 cases, with 117 screws loosening and 240 screws non-loosening. The demographic data[gender, age, body mass index(BMI), bone mineral density(BMD)], operative indicators(operative time, blood loss, lumbar fusion grade, Oswestry disability index), and radiological parameters[screw fixation to S1(FS1), screw trabecular Hounsfield unit(HU), screw sagittal angle(SA), coronary angle(CA), and cortical bone contact layer(CBCL)] were compared between groups. Lasso regression and multivariate logistic regression models were used to screen the optimal independent risk factors to screw loosening, and then a nomogram predictive model was constructed with R software. The internal predictive stability[consistency index(C-index)], prediction differentiation(sensitivity and specificity), prediction probability accuracy(degree of agreement), and net clinical benefit of the model was evaluated with Bootstrap method, receiver operating curve(ROC), calibration curve, and decision curve analysis(DCA). Results: The BMD in loosening group was significantly less than that in non-loosening group(P<0.05), and there were no statistical differences in the other demographic data and surgical indexes between two groups(P>0.05). Compared with non-loosening group, the FS1 percentage and CA in the loosening group significantly increased, while CBCL significantly decreased(P<0.05). BMD(OR=0.44, 95%CI=0.21-0.89, P<0.001), FS1(OR=3.12, 95%CI=2.03-4.54, P<0.001), CA(OR=1.45, 95%CI=1.12-2.03, P<0.001), and CBCL(OR=0.67, 95%CI=0.32-0.88, P<0.001) were the independent risk factors of screw loosening after single-segment PLIF. The total score of the model was 140 points. The bootstrap method calculated the C-index of 0.856(P=0.125), ROC showed area under curve(AUC) of 0.847(95%CI=0.801-0.912, P<0.001). The calibration curve and DCA both showed good consistency in the model′s predictive result and clinical net benefit ratio. Conclusions: The BMD, FS1, CA, and CBCL are the independent risk factors for screw loosening after single-segment PLIF with CBT screws, and the nomogram model constructed has certain application values in early clinical screening of high-risk patients for screw loosening.