Shen Mingkui, Wang Lulu, Tang Zhongxin, Wang Xiaohu, Yang Hejun
Department of Mini-invasive Spinal Surgery, The Third People's Hospital of Henan Province, Zhengzhou, Henan, China.
Henan Engineering Research Center of Precision Diagnosis and Treatment of Intervertebral Disc Disease, Zhengzhou, Henan, China.
Front Neurol. 2025 Aug 21;16:1616590. doi: 10.3389/fneur.2025.1616590. eCollection 2025.
This study aimed to develop and validate the first nomogram model for predicting postoperative complications in thoracic spinal stenosis (TSS) patients undergoing unilateral biportal endoscopy (UBE), integrating multidimensional risk factors to provide a quantitative basis for preoperative risk evaluation and individualized treatment planning.
Patients were divided into a retrospective training cohort ( = 375) and a prospective validation cohort ( = 100). Baseline clinical data [age, diabetes, preoperative Japanese Orthopaedic Association (JOA) score], radiographic parameters (Spinal cord/canal area (SC/ECA) ratio, intramedullary high signal, thoracic kyphosis (TK) angle), and surgical variables (intraoperative blood loss, number of lesion segments, dural adhesion, etc.) were collected. Independent risk factors were identified using logistic regression analysis, and a nomogram model was constructed. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
In the training cohort, 30 patients experienced postoperative complications (37 total events), while 10 patients in the validation cohort had complications (19 total events). Major complications included cerebrospinal fluid leakage, neurological deterioration, poor wound healing, and epidural hematoma. Multivariate logistic regression analysis revealed that diabetes, SC/ECA ≥ 55%, intramedullary high signal, TK angle ≥ 45 °, dural adhesion, multisegment lesion, increased intraoperative blood loss, and prolonged hospitalization were independent risk factors, whereas a higher preoperative JOA score was protective. The nomogram demonstrated excellent discrimination (AUC = 0.964 for training cohort; 0.846 for validation cohort) and good calibration in both cohorts. DCA indicated significant clinical net benefit when the threshold probability exceeded 10%, especially for identifying high-risk patients (threshold > 40%). Risk weight analysis showed that multisegment lesion (25 points) and SC/ECA ≥ 55% (20 points) contributed most to complication risk, followed by intramedullary high signal (15 points) and TK angle (15 points).
This study successfully established a predictive nomogram for postoperative complications following UBE in TSS patients. The model demonstrated high accuracy and clinical utility, providing valuable guidance for preoperative risk stratification and perioperative management, thereby promoting precision in minimally invasive thoracic spine surgery.
本研究旨在开发并验证首个用于预测接受单侧双通道内镜（UBE）手术的胸段脊髓狭窄（TSS）患者术后并发症的列线图模型，整合多维度风险因素，为术前风险评估和个体化治疗规划提供定量依据。
将患者分为回顾性训练队列（n = 375）和前瞻性验证队列（n = 100）。收集基线临床数据[年龄、糖尿病、术前日本骨科协会（JOA）评分]、影像学参数[脊髓/椎管面积（SC/ECA）比值、脊髓内高信号、胸椎后凸（TK）角]以及手术变量（术中失血量、病变节段数、硬膜粘连等）。采用逻辑回归分析确定独立危险因素，并构建列线图模型。使用受试者工作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）评估模型性能。
在训练队列中，30例患者发生术后并发症（共37起事件），而验证队列中有10例患者出现并发症（共19起事件）。主要并发症包括脑脊液漏、神经功能恶化、伤口愈合不良和硬膜外血肿。多因素逻辑回归分析显示，糖尿病、SC/ECA≥55%、脊髓内高信号、TK角≥45°、硬膜粘连、多节段病变、术中失血量增加和住院时间延长是独立危险因素，而术前JOA评分较高具有保护作用。列线图在两个队列中均表现出出色的区分度（训练队列AUC = 0.964；验证队列AUC = 0.846）和良好的校准度。DCA表明，当阈值概率超过10%时，具有显著的临床净效益，尤其是用于识别高危患者（阈值>40%）。风险权重分析显示，多节段病变（25分）和SC/ECA≥55%（20分）对并发症风险的贡献最大，其次是脊髓内高信号（15分）和TK角（15分）。
本研究成功建立了TSS患者UBE术后并发症的预测列线图。该模型显示出高准确性和临床实用性，为术前风险分层和围手术期管理提供了有价值的指导，从而提高了微创胸段脊柱手术的精准性。
