Zhang Yu-Hang, Hu Bing
Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
World J Gastrointest Endosc. 2024 Mar 16;16(3):108-111. doi: 10.4253/wjge.v16.i3.108.
In this editorial, we comment on the minireview by Martino A, published in the recent issue of 2023; 15 (12): 681-689. We focused mainly on the possibility of replacing the hepatic venous pressure gradient (HVPG) and endoscopy with noninvasive methods for predicting esophageal variceal bleeding. The risk factors for bleeding were the size of the varices, the red sign and the Child-Pugh score. The intrinsic core factor that drove these changes was the HVPG. Therefore, the present studies investigating noninvasive methods, including computed tomography, magnetic resonance imaging, elastography, and laboratory tests, are working on correlating imaging or serum marker data with intravenous pressure and clinical outcomes, such as bleeding. A single parameter is usually not enough to construct an efficient model. Therefore, multiple factors were used in most of the studies to construct predictive models. Encouraging results have been obtained, in which bleeding prediction was partly reached. However, these methods are not satisfactory enough to replace invasive methods, due to the many drawbacks of different studies. There is still plenty of room for future improvement. Prediction of the precise timing of bleeding using various models, and extracting the texture of variceal walls using high-definition imaging modalities to predict the red sign are interesting directions to lay investment on.
在这篇社论中,我们对Martino A发表于2023年最新一期、第15卷第12期、第681 - 689页的小型综述进行评论。我们主要关注用非侵入性方法替代肝静脉压力梯度(HVPG)和内镜检查来预测食管静脉曲张出血的可能性。出血的危险因素包括静脉曲张的大小、红色征和Child - Pugh评分。导致这些变化的内在核心因素是HVPG。因此,目前研究非侵入性方法,包括计算机断层扫描、磁共振成像、弹性成像和实验室检查,致力于将成像或血清标志物数据与静脉压力及临床结局(如出血)相关联。通常单个参数不足以构建一个有效的模型。因此,大多数研究使用多个因素来构建预测模型。已经取得了令人鼓舞的结果,部分实现了出血预测。然而,由于不同研究存在诸多缺陷,这些方法尚不足以令人满意地替代侵入性方法。未来仍有很大的改进空间。利用各种模型预测出血的精确时间,以及使用高清成像模式提取静脉曲张壁的纹理以预测红色征,都是值得投入研究的有趣方向。