Wang Yijin, Wang Qiyang, Zuo Huayan, Gong Xiarong, Yang Yong, Bi Guoli, Bi Qiu
The Affiliated Hospital of Kunming University of Science and Technology, Department of MRI, the First People's Hospital of Yunnan Province, Kunming, China.
Department of Orthopedic Surgery, the Key Laboratory of Digital Orthopaedics of Yunnan Provincial, Yunnan Province Spinal Cord Disease Clinical Medical Center, the First People's Hospital of Yunnan Province, the Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
Eur Spine J. 2025 Jun 5. doi: 10.1007/s00586-025-08971-1.
To devise a scoring model that integrates clinical parameters and Dixon MRI markers to predict the probability of surgical site infections (SSI) occurrence after lumbar surgery.
A retrospective analysis was conducted on 1307 patients who underwent lumbar surgery, with 63 SSI patients and 1244 non-SSI patients. Clinical characteristics and the quantitative parameters on Dixon MRI, such as fat fraction (FF), functional cross-sectional area (FCSA), and psoas to lumbar vertebral index (PLVI), were assessed for differences between the two groups. A multivariate logistic regression model was applied to identify independent predictors that could be utilized in developing of a scoring system, and the performance was assessed through the receiver operating characteristic (ROC) curve.
The incidence of SSI was 4.82% (63/1307). The preoperative risk factors for SSI included age (OR 4.442, P = 0.049), duration of surgery (OR 2.872, P = 0.029), multi-segment surgery (OR 3.463, P = 0.021), surgical approach (OR 8.223, P = 0.045), and FCSA (OR 2.152, P = 0.004). When the overall scores of these five predictors were greater than or equal to 3.5 points, the area under the curve (AUC) was 0.823, with sensitivity, specificity, positive predictive value, and negative predictive value of 56.6%, 91.9%, 26.1%, and 97.7%, respectively.
The scoring system based on clinical parameters and Dixon MRI indicators is promising for predicting post-lumbar surgery SSI.
设计一种整合临床参数和迪克森磁共振成像（Dixon MRI）标志物的评分模型，以预测腰椎手术后手术部位感染（SSI）的发生概率。
对1307例行腰椎手术的患者进行回顾性分析，其中63例发生SSI，1244例未发生SSI。评估两组患者的临床特征以及Dixon MRI的定量参数，如脂肪分数（FF）、功能横截面积（FCSA）和腰大肌与腰椎指数（PLVI）的差异。应用多因素逻辑回归模型确定可用于建立评分系统的独立预测因素，并通过受试者工作特征（ROC）曲线评估其性能。
SSI发生率为4.82%（63/1307）。SSI的术前危险因素包括年龄（OR 4.442，P = 0.049）、手术时长（OR 2.872，P = 0.029）、多节段手术（OR 3.463，P = 0.021）、手术入路（OR 8.223，P = 0.045）和FCSA（OR 2.152，P = 0.004）。当这五个预测因素的总得分大于或等于3.5分时，曲线下面积（AUC）为0.823，敏感性、特异性、阳性预测值和阴性预测值分别为56.6%、91.9%、26. and 97.7%。
基于临床参数和Dixon MRI指标的评分系统在预测腰椎手术后SSI方面具有前景。
