Simple Online Calculator Detects Liver Cirr

picture: Thomas Reiberger, Benedikt Simbrunner, Oleksandr Petrenko, Jiří Reiniš, Stefan Kubicek
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Credit: Anna Yuwen, CeMM

Researchers from CeMM, the Medical University of Vienna (MedUni Vienna) and the Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases (LBI-RUD) have joined forces to use their expertise in machine learning and patients with cirrhosis to develop a noninvasive treatment algorithm that can help clinicians identify patients with cirrhosis most at risk for serious complications. Cirrhosis develops in response to repeated damage to the liver, such as fatty liver disease or viral hepatitis. Initially, cirrhosis is mostly asymptomatic, so early identification of risk factors for serious complications represents an unmet clinical need.

There are two clinical stages of liver cirrhosis: compensated and decompensated. Patients with compensated liver cirrhosis have very few or even no symptoms. However, patients can develop decompensated cirrhosis, which occurs with serious complications such as internal bleeding (varicose veins) or fluid buildup in the abdomen (ascites) and can even lead to death. Unfortunately, measuring the risk of decompensation in patients with compensated cirrhosis currently requires an invasive procedure. i.e. the measurement of the hepatic venous pressure gradient (HVPG). An elevated HVPG ≥10 mmHg is associated with a higher likelihood of complications. Patients with an even higher HVPG of ≥16 mmHg are at imminent risk of hepatic decompensation.

In a study conducted by first authors Jiri Reinis from Stefan Kubicek’s group at CeMM and Oleksandr Petrenko from Thomas Reiberger’s group at MedUni Vienna, CeMM and LBI-RUD, machine learning models were trained on blood test parameters obtained from patients with compensated cirrhosis to detect elevated portal vein pressure levels, thereby identifying those at risk of developing clinical complications. The study was now published prominently in the Journal of Hepatology.

Best clinical parameters for prediction

The main sources of data used in the project come from the ongoing Vienna Cirrhosis Study, conducted at the Division of Gastroenterology and Hepatology of the MedUni Vienna at the Vienna General Hospital. For this study, HVPG measurements were performed in 163 patients with compensated cirrhosis in whom blood samples were taken simultaneously to determine a range of 124 biomarkers. Of the set of clinical variables, three and five optimal parameters for the detection of high-risk patients were determined by computer. In the VICIS patient cohort, the model achieved excellent results in identifying patients with HVPG values ​​≥10 mmHg and ≥16 mmHg, respectively.

Dataset validation

To assess the diagnostic power of noninvasive models to predict complications, the researchers tested their noninvasive machine learning model on a combined cohort of 1,232 patients with compensated cirrhosis from 8 European clinical centers. The new approach was confirmed to have excellent diagnostic value across the entire cohort and, most importantly, is based only on 3 or 5 widely available laboratory parameters, is non-invasive and does not require dedicated and expensive equipment. Project leader Thomas Reiberger explains: “Although HVPG measurement is still needed for reliable identification of patients with clinically significant or severe portal hypertension, the new approach could be applied for treatment prioritization to prevent decompensation or for the selection of patients for clinical trials. Due to its simplicity, the proposed methodology could potentially be used during routine checks at little additional cost.

Online calculator

Finally, the researchers developed an online calculator allowing clinicians to calculate the risk of decompensation for their patients with compensated cirrhosis, available at

Thomas Reberger joined LBI-RUD and CeMM in November 2018 as Deputy PI. After obtaining his medical doctorate at the Medical University of Vienna, he carried out a first post-doctorate at the Department of Pathophysiology of the Medical University of Vienna focusing on ex situ liver perfusion and cell biology liverworts. During his residency in internal medicine, he pursued a career as a physician-scientist while conducting translational clinical studies in portal hypertension and fibrosis. In addition to his clinical activity, he created the Experimental Hepatic Hemodynamics Laboratory (HEPEX) and Clinic. After another postdoctoral fellowship in the United States from 2012 to 2015, Thomas Reiberger joined the Faculty of the Division of Gastroenterology and Hepatology at the Medical University of Vienna. Thomas Reiberger is also Director of the Outpatient Cirrhosis Clinic and the Vienna Hepatic Hemodynamics Laboratory at the Vienna General Hospital. In his role as coordinator of the Center for Rare Liver Diseases (RALID) of the European Reference Network (ERN) RARE-LIVER on the campus of the Medical University of Vienna, he complements the mission of the LBI-RUD with translational research on rare liver diseases.

The CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences is an international, independent and interdisciplinary research institution for molecular medicine under the scientific direction of Giulio Superti-Furga. CeMM is oriented towards medical needs and integrates fundamental research and clinical expertise to develop innovative diagnostic and therapeutic approaches for precision medicine. Research focuses on cancer, inflammation, metabolic and immune disorders, and rare diseases. The Institute’s research building is located on the campus of the Medical University and Vienna General Hospital.

The Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases (LBI-RUD) was founded in April 2016 as a joint effort of Ludwig Boltzmann Gesellschaft, the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, the Medical University of Vienna and the Institute of St. Anna Children’s Cancer Research. The three founding partner institutions and the CeRUD Vienna Center for Rare and Undiagnosed Diseases are the most important collaboration partners of the LBI-RUD. Research at the LBI-RUD focuses on deciphering rare immunological, hematopoietic, nervous, dermal, gastrointestinal and hepatic diseases. These studies provide unique insights into human biology and are the basis for the development of tailor-made therapeutic concepts in the direction of the personalized medicine of the future. The mission of the LBI-RUD is – with its partner institutions – to develop and sustainably maintain research infrastructures integrating the scientific, societal, ethical and economic aspects of rare diseases.

Medical University of Vienna (MedUni Vienna) is one of Europe’s most traditional medical education and research institutions. With nearly 8,000 students, it is currently the largest medical training center in German-speaking countries. With 6,000 employees, 30 departments and two clinical institutes, 12 medical theory centers and numerous highly specialized laboratories, it is also one of Europe’s leading research establishments in the biomedical sector.

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