Evidence map›Paper›PMID 40415980›Full record

ArticleHealth science reports2025

Can "Attenuation Subtraction", a Computed Tomography Scan-Based Factor, be Used as a Predictor of High-Risk Esophageal Varices in Cirrhotic Patients? A Retrospective Cohort Study.

Mohammad Mersad Mansouri Tehrani, Nasser Bahari, Kian Goudarzi, Faeze Salahshour, Babak Shekarchi, Mohammad Masih Mansouri-Tehrani, Majid Nouri

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Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mohammad Mersad Mansouri TehraniRadiation Sciences Research Center Aja University of Medical Sciences Tehran Iran.ORCID https://orcid.org/0000-0002-2987-2254
Nasser BahariCancer Research Center Shahid Beheshti University of Medical Science Tehran Iran.
Kian GoudarziFaculty of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran.
Faeze SalahshourDepartment of Radiology, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Imam-Khomeini Hospital Complex Tehran University of Medical Science Tehran Iran.
Babak ShekarchiInfectious Diseases Research Center Aja University of Medical Sciences Tehran Iran.ORCID https://orcid.org/0009-0004-2251-8385
Mohammad Masih Mansouri-TehraniDepartment of Radiology, School of Medicine Iran University of Medical Sciences Tehran Iran.
Majid NouriInfectious Diseases Research Center Aja University of Medical Sciences Tehran Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Liver cirrhosis is a severe condition that can result in complications such as portal hypertension and esophageal varices (EVs). While current guidelines recommend screening for EVs, existing procedures are often invasive, costly, and occasionally unreliable. This study aims to develop a CT-based predictor for identifying high-risk esophageal varices group (HRG) in cirrhotic patients, offering a noninvasive, safe, and cost-effective alternative that integrates seamlessly into routine follow-up without requiring additional resources or time. Methods: The study retrospectively analyzed data from 2016 to 2021 of cirrhotic patients referred to a hospital in Tehran. Experienced professionals analyzed factors related to CT scans, and patients were categorized into high-risk and non-high-risk varicose veins groups by endoscopy. The main sample size for the study was 62 patients with an average age of 50.2 ± 11.5 years. Also, we aimed to determine a diagnostic cutoff and externally validated it in a separate statistical population (29 patients). Result: The study found that liver attenuation subtraction, Child-Pugh score, and direct visualization of esophageal varices in CT scans were significant factors in predicting high-risk esophageal varices. The study showed that a liver attenuation subtraction of 14.5 HU (CI 95%: 0.949-1) with an inverse relationship could predict high-risk esophageal varices with high accuracy. Conclusion: The study indicated that liver "Attenuation Subtraction" in CT scans distinguishes high-risk and non-high-risk esophageal varices. Furthermore, external validation demonstrated that this cutoff value is generalizable to other statistical populations. We pinpoint an indicator of high-risk esophageal varices in patients with cirrhosis devoid of invasiveness and peril and do not impose supplementary expenses or time beyond the customary monitoring of cirrhotic patients.

Indexed as

attenuation subtractionCThigh‐risk esophago‐gastric varicesliver diseasepredictor

Identifiers

PMID40415980
PMCPMC12098957

What Socratic holds

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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 Socratic graph.