Evidence map›Paper›PMID 38833138›Full record

ArticleHepatology international2024

Hepatic-associated vascular morphological assessment to predict overt hepatic encephalopathy before TIPS: a multicenter study.

Xiaoqiong Chen, Mingsheng Huang, Xiangrong Yu, Jinqiang Chen, Chunchun Xu, Yunzheng Jiang, Yiting Li, Yujie Zhao, Chongyang Duan, Yixin Luo and 8 more

Abstract readMulticenter Study
In one paragraph

Article in Hepatology international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
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  7. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Xiaoqiong Chen *Zhuhai Interventional Medical Centre, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China.
Mingsheng Huang *Department of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Xiangrong Yu *Zhuhai Engineering Technology Research Center of Intelligent Medical Imaging, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China.
Jinqiang Chen *Zhuhai Interventional Medical Centre, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China.
Chunchun XuDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China.
Yunzheng JiangDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China.
Yiting LiDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China.
Yujie ZhaoZhuhai Interventional Medical Centre, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China.
Chongyang DuanDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China.
Yixin LuoDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China.
Jiawei ZhangZhuhai Interventional Medical Centre, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China.
Weifu LvInterventional Radiology Department, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, China.
Qiyang LiDepartment of Interventional Radiology, Shenzhen People's Hospital, Shenzhen, China.
Junyang LuoDepartment of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Dandan DongZhuhai Engineering Technology Research Center of Intelligent Medical Imaging, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China.
Taixue AnDepartment of Laboratory Medicine, Nanfang Hospital, Southern Medical University, No. 1023-1063 Shatai Road, Guangzhou, 510515, Guangdong Province, China. atxhuazhong@126.com.
Ligong LuZhuhai Interventional Medical Centre, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China. llg0902@sina.com.
Sirui FuZhuhai Interventional Medical Centre, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), No. 79 Kangning Road, Zhuhai, 519000, Guangdong Province, China. bicia870428@sina.com.

Funding

Clinical Research Promotion Project of Zhuhai People's Hospital 2023LCTS-07Guangdong Basic and Applied Basic Research Foundation 202201011478Guangdong Basic and Applied Basic Research Foundation 2023A1515011384Guangdong Provincial Key Laboratory of Tumor Interventional Diagnosis and Treatment 2021B1212040004National Natural Science Foundation of China 82230067National Natural Science Foundation of China 82272069Nurture Programme of Zhuhai People's Hospital 2020XSYC-09Science and Technology Planning Project of Guangzhou 202201011478Science and Technology Planning Project of Guangzhou 202201020570Zhuhai Industrial Core and Key Technology Tackling Direction Project ZH22044702190126HJL
6 · The paper itself

Abstract

backgroundTo provide patients the chance of accepting curative transjugular intrahepatic portosystemic shunt (TIPS) rather than palliative treatments for portal hypertension-related variceal bleeding and ascites, we aimed to assess hepatic-associated vascular morphological change to improve the predictive accuracy of overt hepatic encephalopathy (HE) risks.

methodsIn this multicenter study, 621 patients undergoing TIPS were subdivided into training (413 cases from 3 hospitals) and external validation datasets (208 cases from another 3 hospitals). In addition to traditional clinical factors, we assessed hepatic-associated vascular morphological changes using maximum diameter (including absolute and ratio values). Three predictive models (clinical, hepatic-associated vascular, and combined) were constructed using logistic regression. Their discrimination and calibration were compared to test the necessity of hepatic-associated vascular assessment and identify the optimal model. Furthermore, to verify the improved performance of Model

resultsThe combined model outperformed the clinical and hepatic-associated vascular models (training: 0.814, 0.754, 0.727; validation: 0.781, 0.679, 0.776; p < 0.050) and had the best calibration. Compared to previous models, Model

conclusionHepatic-associated vascular assessment improved the predictive accuracy of overt HE, ensuring curative chances by TIPS for suitable patients and providing insights for cirrhosis-related studies.

Indexed as

Hepatic EncephalopathyPortasystemic Shunt, Transjugular IntrahepaticAgedFemaleHumansHypertension, PortalLiverLiver CirrhosisMaleMiddle AgedPredictive Value of TestsRetrospective StudiesAppletCalibrationDiscriminationMorphological changeOvert HEPopulationsPredictionSubgroupsTransjugular intrahepatic portosystemic shuntVascular

Identifiers

PMID38833138
PMCPMC11297904

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.