Evidence map›Paper›PMID 31436367›Full record

ArticleLiver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society2019

Development of a Model to Predict Portal Vein Thrombosis in Liver Transplant Candidates: The Portal Vein Thrombosis Risk Index.

Daniel Gaballa, Dmitri Bezinover, Zakiyah Kadry, Elaine Eyster, Ming Wang, Patrick G Northup, Jonathan G Stine

Abstract read
In one paragraph

Article in Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Metabolic Disorders and Risk of Portal Vein Thrombosis in Liver Cirrhosis: A Systematic Review and Meta-Analysis.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2022
    Pooled it
  2. [Research progress on predictive models of portal vein thrombosis in liver cirrhosis].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Daniel GaballaDepartments of Medicine, Milton S. Hershey Medical Center, Pennsylvania State University, Hershey, PA.
Dmitri BezinoverDepartment of Anesthesia, Milton S. Hershey Medical Center, Pennsylvania State University, Hershey, PA.
Zakiyah KadryDivision of Transplant Surgery, Department of Surgery, Milton S. Hershey Medical Center, Pennsylvania State University, Hershey, PA.
Elaine EysterDivision of Hematology and Oncology of Medicine, Milton S. Hershey Medical Center, Pennsylvania State University, Hershey, PA.
Ming WangDepartment of Public Health Sciences, Milton S. Hershey Medical Center, Pennsylvania State University, Hershey, PA.
Patrick G NorthupCenter for the Study of Coagulation Disorders in Liver Disease, Division of Gastroenterology and Hepatology, Department of Medicine, University of Virginia Health System, Charlottesville, VA.
Jonathan G StineDepartment of Public Health Sciences, Milton S. Hershey Medical Center, Pennsylvania State University, Hershey, PA.

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Penn State Institutional Career Development CoreKL2TR002015 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI VAN SCOY, LAUREN JODI · 2016 to 2025
$7.8M
NCATS NIH HHS KL2 TR002015NCATS NIH HHS UL1 TR002014NIDDK NIH HHS L30 DK118601
6 · The paper itself

Abstract

Portal vein thrombosis (PVT) is associated with inferior pretransplantation and posttransplantation outcomes. We aimed to create a predictive model to risk stratify transplant candidates for PVT. Data on adult transplants in the United States during the Model for End-Stage Liver Disease (MELD) era through September 2016 were reviewed. We constructed and validated a scoring system composed of routine, readily available clinical information to predict the development of incident PVT at 12 months from transplantation listing. A total of 66,568 liver transplant candidates were dichotomized into 2 groups to construct (n = 34,751) and validate (n = 31,817) a scoring system. In general, the derivation and validation cohorts were clinically similar. Although nonalcoholic steatohepatitis was a significant predictor of incident PVT (hazard ratio, 1.29; 95% confidence interval, 1.08-1.54; P < 0.001), age, MELD score, and moderate-to-severe ascites were also associated with increased risk. African American race was associated with decreased risk. A scoring system (PVT risk index [RI]) of these 5 variables had an area under the curve of 0.71 and 0.70 in both derivation and validation cohorts, respectively. By applying the low cutoff score of 2.6, incident PVT could be accurately excluded (negative predictive value 94%). Using the high cutoff score of 4.6 (positive predictive value 85%), PVT could be diagnosed with high accuracy. The PVT-RI predicts which candidates awaiting lifesaving liver transplantation will and will not develop future PVT. Although this scoring system will require prospective validation, it provides a powerful new tool for the clinician when risk stratifying cirrhosis patients prior to liver transplantation for future PVT development.

Indexed as

Liver TransplantationAdultFemaleHumansIncidenceLiver CirrhosisMaleMiddle AgedPortal VeinProportional Hazards ModelsRetrospective StudiesRisk AssessmentRisk FactorsSeverity of Illness IndexVenous Thrombosis

Identifiers

PMID31436367
PMCPMC6864229

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Registered trials

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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.