Cargando…
Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices
OBJECTIVES: To establish and verify a simple noninvasive model based on the left gastric vein (LGV) to predict the grade of esophageal varices (EV) and high-risk EV (HEV), to facilitate clinical follow-up and timely treatment. METHODS: We enrolled 320 patients with B-viral cirrhosis. All patients un...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641443/ https://www.ncbi.nlm.nih.gov/pubmed/33259161 http://dx.doi.org/10.14309/ctg.0000000000000262 |
_version_ | 1783605919438864384 |
---|---|
author | Xu, Xinzhi Jin, Ying Lin, Yuanqiang Hu, Dongmei Zhou, Yaoyao Li, Dianqiu Wang, Hui Jin, Chunxiang |
author_facet | Xu, Xinzhi Jin, Ying Lin, Yuanqiang Hu, Dongmei Zhou, Yaoyao Li, Dianqiu Wang, Hui Jin, Chunxiang |
author_sort | Xu, Xinzhi |
collection | PubMed |
description | OBJECTIVES: To establish and verify a simple noninvasive model based on the left gastric vein (LGV) to predict the grade of esophageal varices (EV) and high-risk EV (HEV), to facilitate clinical follow-up and timely treatment. METHODS: We enrolled 320 patients with B-viral cirrhosis. All patients underwent endoscopy, laboratory tests, liver and spleen stiffness (SS), and ultrasonography. HEV were analyzed using the χ(2) test/t test and logistic regression in the univariate and multivariate analyses, respectively. EV grades were analyzed using the variance/rank-sum test and logistic regression. A prediction model was derived from the multivariate predictors. RESULTS: In the training set, multivariate analysis showed that the independent factors of different EV grades were SS, LGV diameter, and platelet count (PLT). We developed the LGV diameter-SS to PLT ratio index (LSPI) and LGV diameter/PLT models without SS. The area under the receiver operating characteristic curve of the LSPI for diagnosis of small EV, medium EV, large EV, and HEV was 0.897, 0.899, 0.853, and 0.954, respectively, and that of the LGV/PLT was 0.882, 0.890, 0.837, and 0.942, respectively. For the diagnosis of HEV, the negative predictive value was 94.07% when LSPI < 19.8 and the positive predictive value was 91.49% when LSPI > 23.0. The negative predictive value was 95.92% when LGV/PLT < 5.15, and the positive predictive value was 86.27% when LGV/PLT > 7.40. The predicted values showed similar accuracy in the validation set. DISCUSSION: Under appropriate conditions, the LSPI was an accurate method to detect the grade of EV and HEV. Alternatively, the LGV/PLT may also be useful in diagnosing the varices when condition limited. |
format | Online Article Text |
id | pubmed-7641443 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer |
record_format | MEDLINE/PubMed |
spelling | pubmed-76414432020-11-05 Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices Xu, Xinzhi Jin, Ying Lin, Yuanqiang Hu, Dongmei Zhou, Yaoyao Li, Dianqiu Wang, Hui Jin, Chunxiang Clin Transl Gastroenterol Article OBJECTIVES: To establish and verify a simple noninvasive model based on the left gastric vein (LGV) to predict the grade of esophageal varices (EV) and high-risk EV (HEV), to facilitate clinical follow-up and timely treatment. METHODS: We enrolled 320 patients with B-viral cirrhosis. All patients underwent endoscopy, laboratory tests, liver and spleen stiffness (SS), and ultrasonography. HEV were analyzed using the χ(2) test/t test and logistic regression in the univariate and multivariate analyses, respectively. EV grades were analyzed using the variance/rank-sum test and logistic regression. A prediction model was derived from the multivariate predictors. RESULTS: In the training set, multivariate analysis showed that the independent factors of different EV grades were SS, LGV diameter, and platelet count (PLT). We developed the LGV diameter-SS to PLT ratio index (LSPI) and LGV diameter/PLT models without SS. The area under the receiver operating characteristic curve of the LSPI for diagnosis of small EV, medium EV, large EV, and HEV was 0.897, 0.899, 0.853, and 0.954, respectively, and that of the LGV/PLT was 0.882, 0.890, 0.837, and 0.942, respectively. For the diagnosis of HEV, the negative predictive value was 94.07% when LSPI < 19.8 and the positive predictive value was 91.49% when LSPI > 23.0. The negative predictive value was 95.92% when LGV/PLT < 5.15, and the positive predictive value was 86.27% when LGV/PLT > 7.40. The predicted values showed similar accuracy in the validation set. DISCUSSION: Under appropriate conditions, the LSPI was an accurate method to detect the grade of EV and HEV. Alternatively, the LGV/PLT may also be useful in diagnosing the varices when condition limited. Wolters Kluwer 2020-11-04 /pmc/articles/PMC7641443/ /pubmed/33259161 http://dx.doi.org/10.14309/ctg.0000000000000262 Text en © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Article Xu, Xinzhi Jin, Ying Lin, Yuanqiang Hu, Dongmei Zhou, Yaoyao Li, Dianqiu Wang, Hui Jin, Chunxiang Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices |
title | Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices |
title_full | Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices |
title_fullStr | Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices |
title_full_unstemmed | Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices |
title_short | Multimodal Ultrasound Model Based on the Left Gastric Vein in B-Viral Cirrhosis: Noninvasive Prediction of Esophageal Varices |
title_sort | multimodal ultrasound model based on the left gastric vein in b-viral cirrhosis: noninvasive prediction of esophageal varices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641443/ https://www.ncbi.nlm.nih.gov/pubmed/33259161 http://dx.doi.org/10.14309/ctg.0000000000000262 |
work_keys_str_mv | AT xuxinzhi multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices AT jinying multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices AT linyuanqiang multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices AT hudongmei multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices AT zhouyaoyao multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices AT lidianqiu multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices AT wanghui multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices AT jinchunxiang multimodalultrasoundmodelbasedontheleftgastricveininbviralcirrhosisnoninvasivepredictionofesophagealvarices |