Peng Hai, Yuan Ruofei, Zhang Zhe, Wang Ying, Wang Xingchao, Wang Bo, Li Peng
Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District 100070, Beijing, China.
Neural Reconstruction Department, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Sci Rep. 2025 Jan 25;15(1):3221. doi: 10.1038/s41598-025-87656-7.
Deep vein thrombosis (DVT) in patients undergoing endoscopic endonasal surgery remains underexplored, despite its potential impact on postoperative recovery. This study aimed to develop and validate a predictive nomogram for assessing the risk of lower-limb DVT in such patients without chemoprophylaxis. A retrospective analysis was conducted on 935 patients with postoperative lower-limb vein ultrasonography. Clinical data, including potential risk factors, were used to construct a predictive model via multivariate logistic regression analysis. The resulting nomogram was validated using an independent cohort and evaluated through concordance index (C-index), calibration plots, and decision curve analysis. The incidence of postoperative DVT was 28.9%, with most cases being distal (27.2%). Significant predictors included older age, intraoperative bleeding, female gender, prolonged surgery duration, elevated postoperative APTT and D-dimer levels, and disturbance of consciousness. The nomogram demonstrated good predictive performance, with C-index values of 0.81 in the training cohort and 0.75 in the validation cohort. Calibration and decision curve analyses confirmed the model's clinical applicability. This nomogram offers a practical tool for individualized DVT risk assessment in patients undergoing endoscopic endonasal surgery, facilitating more targeted prophylactic measures.
尽管内镜鼻内手术患者发生深静脉血栓形成（DVT）对术后恢复有潜在影响，但其相关研究仍较少。本研究旨在建立并验证一种预测列线图，用于评估此类未接受化学预防患者发生下肢DVT的风险。对935例行术后下肢静脉超声检查的患者进行了回顾性分析。利用包括潜在危险因素在内的临床数据，通过多因素逻辑回归分析构建预测模型。使用独立队列对所得列线图进行验证，并通过一致性指数（C指数）、校准图和决策曲线分析进行评估。术后DVT发生率为28.9%，大多数病例为远端DVT（27.2%）。显著的预测因素包括年龄较大、术中出血、女性、手术时间延长、术后活化部分凝血活酶时间（APTT）和D-二聚体水平升高以及意识障碍。该列线图显示出良好的预测性能，训练队列的C指数值为0.81，验证队列的C指数值为0.75。校准和决策曲线分析证实了该模型的临床适用性。此列线图为内镜鼻内手术患者的个体化DVT风险评估提供了一种实用工具，有助于采取更有针对性的预防措施。
