Establishing Cut-Offs for Non-Invasive Liver Tests to Detect Cirrhosis at a High Sensitivity-Reference-Cited by-同舟云学术

Establishing Cut-Offs for Non-Invasive Liver Tests to Detect Cirrhosis at a High Sensitivity

Published:2020-04-01 Issue:2 Volume:74 Page:118-124
ISSN:2255-890X
Container-title:Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences.
language:en
Short-container-title:

Author:

Zirnis Andrejs Ernests¹,Straume Zane¹²,Bērziņa Raisa¹,Māliņa-Bambīte Justīne¹,Derovs Aleksejs¹²,Zeltiņa Inese¹²

Affiliation:

1. Rīga Stradiņš University , 16 Dzirciema Str., Rīga , LV- 1007 , Latvia

2. Rīga East Clinical University Hospital , 2 Hipokrāta Str., Rīga , LV- 1038 , Latvia

Abstract

Abstract Liver cirrhosis is the end stage of chronic liver diseases. The current gold standard for diagnosing this condition, liver biopsy, has too many drawbacks, and research for better alternatives is ongoing. One major diagnostic arsenal includes various serological composition scores or so-called formulas. They are constantly being validated for development of new formulas. In our retrospective study of 215 patients case files who had confirmed cirrhosis of various etiologies, we examined the sensitivity and set new cut-offs for five of the most well-documented formulas. Data was obtained from the Rīga East University Hospital from 2012 to 2017 and analysed using SPSS V.22.00. In our study we found that FIB-4 at cut-off > 1.45 had over 95% sensitivity for excluding advanced fibrosis regardless of cirrhosis etiology. None of evaluated formulas had high sensitivity for detecting cirrhosis of alcohol etiology. For the viral hepatitis C genesis group, the best choice was deRitis index with almost 90% sensitivity. FIB-4 at cut-off > 2.75 was the best choice for the combined alcohol and viral hepatitis C group; BONACINI at score 8+ and FIB-4 at > 3.25 were the most sensitive in the main group containing all patients irrespective of cirrhosis etiology.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/prolas-2020-0019

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