Long Zongke, Hu Xiaole, Liu Jian, Zhou Peiyun, Zhang Bingyan, Zhang Simeng, Wei Huimin, Qu Wenran, Luan Xiaorong
School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
The First Operating Room, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China.
Neurosurg Rev. 2025 Jun 6;48(1):488. doi: 10.1007/s10143-025-03645-4.
Surgical site infection is a serious complication of posterior lumbar interbody fusion surgery and is influenced by various factors. To construct a predictive nomogram of the risk of surgical site infection among patients after posterior luminal interbody fusion surgery. A total of 496 patients who underwent posterior lumbar interbody fusion surgery between January 2019 and December 2023 were included, and randomly assigned to a training or a validation queue following a 7:3 ratio. A nomogram prediction model was established based on the training queue, and evaluation of its accuracy and discriminative ability was done using calibration curves and receiver operating characteristic analysis. Decision curve analysis was used to estimate the clinical value of the nomograms. Seventeen cases (3.43%) of SSI were observed. The predictive factors included preoperative hypoalbuminemia (P = 0.048), drainage tube retention time (P = 0.002), number of fusion segments(P < 0.001), and postoperative white blood cell count (P = 0.003). The receiver operating characteristic analysis indicated that the model had good predictive performance (training cohort: 0.95; validation cohort: 0.903). The calibration curves showed good consistency between the predicted and actual values, and the decision curve indicated good clinical benefits. Preoperative hypoalbuminemia, drainage tube retention time, number of fusion stages, and postoperative white blood cell count were independent risk factors of surgical site infection in patients undergoing posterior lumbar interbody fusion surgery. The nomogram model had a good predictive performance and can provide an effective evaluation method to improve prediction accuracy.
手术部位感染是腰椎后路椎间融合手术的一种严重并发症，受多种因素影响。为构建腰椎后路椎间融合手术后患者手术部位感染风险的预测列线图。纳入2019年1月至2023年12月期间接受腰椎后路椎间融合手术的496例患者，并按照7:3的比例随机分配至训练队列或验证队列。基于训练队列建立列线图预测模型，并使用校准曲线和受试者工作特征分析对其准确性和判别能力进行评估。采用决策曲线分析评估列线图的临床价值。观察到17例（3.43%）手术部位感染病例。预测因素包括术前低白蛋白血症（P = 0.048）、引流管留置时间（P = 0.002）、融合节段数（P < 0.001）和术后白细胞计数（P = 0.003）。受试者工作特征分析表明该模型具有良好的预测性能（训练队列：0.95；验证队列：0.903）。校准曲线显示预测值与实际值之间具有良好的一致性，决策曲线表明具有良好的临床效益。术前低白蛋白血症、引流管留置时间、融合节段数和术后白细胞计数是腰椎后路椎间融合手术患者手术部位感染的独立危险因素。列线图模型具有良好的预测性能，可为提高预测准确性提供有效的评估方法。
