Lanzhou University Second Hospital, Lanzhou, China.
Department of General Surgery, Lanzhou University Second Hospital, Lanzhou, China.
BMC Gastroenterol. 2024 Sep 19;24(1):321. doi: 10.1186/s12876-024-03416-3.
The relationship between lymphocyte-associated inflammatory indices and portal vein thrombosis (PVT) following splenectomy combined with esophagogastric devascularization (SED) is currently unclear. This study aims to investigate the association between these inflammatory indices and PVT, and to develop a nomogram based on these indices to predict the risk of PVT after SED, providing an early warning tool for clinical practice.
We conducted a retrospective analysis of clinical data from 131 cirrhotic patients who underwent SED at Lanzhou University's Second Hospital between January 2014 and January 2024. Independent risk factors for PVT were identified through univariate and multivariate logistic regression analyses, and the best variables were selected using the Akaike Information Criterion (AIC) to construct the nomogram. The model's predictive performance was assessed through receiver operating characteristic (ROC), calibration, decision, and clinical impact curves, with bootstrap resampling used for internal validation.
The final model incorporated five variables: splenic vein diameter (SVD), D-Dimer, platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and red cell distribution width-to-lymphocyte ratio (RLR), achieving an area under the curve (AUC) of 0.807, demonstrating high predictive accuracy. Calibration and decision curves demonstrated good calibration and significant clinical benefits. The model exhibited good stability through internal validation.
The nomogram model based on lymphocyte-associated inflammatory indices effectively predicts the risk of portal vein thrombosis after SED, demonstrating high accuracy and clinical utility. Further validation in larger, multicenter studies is needed.
脾切除联合贲门周围血管离断术(SED)后淋巴细胞相关炎症指标与门静脉血栓形成(PVT)之间的关系尚不清楚。本研究旨在探讨这些炎症指标与 PVT 的相关性,并基于这些指标建立预测 SED 后 PVT 风险的列线图,为临床实践提供早期预警工具。
我们对 2014 年 1 月至 2024 年 1 月期间在兰州大学第二医院接受 SED 的 131 例肝硬化患者的临床数据进行了回顾性分析。通过单因素和多因素逻辑回归分析确定 PVT 的独立危险因素,并使用赤池信息量准则(AIC)选择最佳变量构建列线图。通过接收者操作特征(ROC)、校准、决策和临床影响曲线评估模型的预测性能,并使用 bootstrap 重采样进行内部验证。
最终模型纳入了五个变量:脾静脉直径(SVD)、D-二聚体、血小板与淋巴细胞比值(PLR)、单核细胞与淋巴细胞比值(MLR)和红细胞分布宽度与淋巴细胞比值(RLR),曲线下面积(AUC)为 0.807,具有较高的预测准确性。校准和决策曲线表明校准良好且具有显著的临床获益。内部验证表明模型具有较好的稳定性。
基于淋巴细胞相关炎症指标的列线图模型可有效预测 SED 后 PVT 的风险,具有较高的准确性和临床实用性。需要在更大的多中心研究中进一步验证。