A new model combining the liver/spleen volume ratio and classification of varices predicts HVPG in hepatitis B patients with cirrhosis

医学 门静脉压 肝硬化 静脉曲张 内科学 胃肠病学 门脉高压 食管静脉曲张 预测值
作者
Shi‐Ping Yan,Hao Wu,Guang-chuan Wang,Yong Chen,Chunqing Zhang,Qiang Zhu
出处
期刊:European Journal of Gastroenterology & Hepatology [Ovid Technologies (Wolters Kluwer)]
卷期号:27 (3): 335-343 被引量:26
标识
DOI:10.1097/meg.0000000000000269
摘要

Although the therapy of varices in liver cirrhosis has improved, the mortality during a variceal hemorrhage episode remains high. Patients with hepatic venous pressure gradient (HVPG) greater than 12 mmHg have been identified as being at a higher risk for the first hemorrhage episode.The aim of this study was to find an accurate method to predict HVPG greater than 12 mmHg.A total of 150 hepatitis B patients with liver cirrhosis were enrolled and analyzed retrospectively. The patients were randomly divided into the experiment group and the validation group. The experiment group was used to construct a model to predict HVPG greater than 12 mmHg. The validation group was used to verify the predictive equation.The predictive model combined with the liver/spleen volume ratio and classification of varices was constructed to predict HVPG greater than 12 mmHg. The area under the curve of this predictive equation was 0.919. The values of sensitivity, specificity, positive predictive value, and negative predictive value were 92.9, 87.0, 89.7, and 90.9%, respectively. The following equation was used to calculate the HVPG score: HVPG score = 13.651 - 6.187×ln (liver/spleen volume)+2.755×[classification of varices score (classification of varices : small, 1; large; 2].The new model combining the liver/spleen volume ratio and classification of varices can accurately predict HVPG in hepatitis B patients with cirrhosis.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Amanda发布了新的文献求助10
1秒前
2秒前
3秒前
3秒前
3秒前
4秒前
ricardo应助李大达采纳,获得10
5秒前
莫小烦完成签到,获得积分10
5秒前
6秒前
new发布了新的文献求助10
7秒前
刘澳发布了新的文献求助10
7秒前
SciGPT应助灵ling采纳,获得10
7秒前
8秒前
汤圆发布了新的文献求助10
8秒前
完美世界应助阿拉采纳,获得10
9秒前
二萌发布了新的文献求助10
9秒前
10秒前
10秒前
轨迹应助远_09采纳,获得20
11秒前
科研通AI2S应助无辜的醉波采纳,获得10
11秒前
tejing1158发布了新的文献求助10
12秒前
星鱼发布了新的文献求助20
12秒前
英俊的铭应助家欣采纳,获得10
13秒前
13秒前
Ava应助Lionnn采纳,获得10
14秒前
傲娇而又骄傲完成签到 ,获得积分10
14秒前
科研通AI6.2应助Amanda采纳,获得30
15秒前
小蚊子完成签到,获得积分10
15秒前
16秒前
16秒前
jijijibibibi完成签到,获得积分10
17秒前
kl完成签到,获得积分10
18秒前
18秒前
CodeCraft应助医学小牛马采纳,获得10
19秒前
沐啊完成签到 ,获得积分10
20秒前
20秒前
20秒前
CodeCraft应助汤圆采纳,获得10
20秒前
20秒前
本草石之寒温完成签到 ,获得积分10
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Kinesiophobia : a new view of chronic pain behavior 2000
Research for Social Workers 1000
Mastering New Drug Applications: A Step-by-Step Guide (Mastering the FDA Approval Process Book 1) 800
The Social Psychology of Citizenship 600
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5912187
求助须知:如何正确求助?哪些是违规求助? 6831436
关于积分的说明 15785215
捐赠科研通 5037204
什么是DOI,文献DOI怎么找? 2711599
邀请新用户注册赠送积分活动 1661950
关于科研通互助平台的介绍 1603905