Dept. orthopedics trauma and hand surgery, the First Affiliated Hospital of Guangxi Medical University, NO. 6 ShuangYong Road, Nanning, 530022, Guangxi, China.
Sci Rep. 2024 Oct 12;14(1):23888. doi: 10.1038/s41598-024-74644-6.
In recent years, the incidence of tibial plateau fractures (TPF) has been on the rise. Deep vein thrombosis (DVT) may lead to poor prognosis in patients. The systemic immune-inflammation index(SII) are novel biomarkers of inflammation, and this study aims to verify their predictive effect and construct the nomogram model. This study used binary logistic regression analysis to predict the predictive effect of SII on the occurrence of DVT in tibial plateau fracture patients. And use R studio to construct nomogram model. The results showed that Age (1.03 [1, 1.06], p = 0.032), SII (3.57 [1.68, 7.61], p = 0.04), and NC (7.22 [3.21, 16.26], p < 0.001) were independent predictive factors for DVT. The nomogram demonstrated good predictive performance with small errors in both the training and validation groups, and most clinical patients could benefit from them. The nomogram constructed based on SII can assist clinicians in early assessment of the probability of DVT occurrence.
近年来,胫骨平台骨折(TPF)的发病率呈上升趋势。深静脉血栓形成(DVT)可能导致患者预后不良。全身免疫炎症指数(SII)是一种新的炎症标志物,本研究旨在验证其预测效果并构建列线图模型。本研究使用二项逻辑回归分析预测 SII 对胫骨平台骨折患者 DVT 发生的预测效果。并使用 R 工作室构建列线图模型。结果表明,年龄(1.03[1, 1.06],p=0.032)、SII(3.57[1.68, 7.61],p=0.04)和 NC(7.22[3.21, 16.26],p<0.001)是 DVT 的独立预测因素。列线图在训练组和验证组中均显示出良好的预测性能,且误差较小,大多数临床患者均可从中受益。基于 SII 构建的列线图可帮助临床医生早期评估 DVT 发生的概率。