BUCSICS Theresa

Characterization of Disease Severity and Prognosis in Patients with Advanced Cirrhosis

This study is a retrospective cohort study. It aims at evaluating predictive values of different models for determining outcome and prognosis of patients with advanced liver cirrhosis. Patients with advanced cirrhosis often present with clinically significant portal hypertension, which is defined as a hepato-venous pressure gradient (HVPG) greater than 10mmHg. Consequently, these patients are at high risk of developing decompensating events, such as ascites (the most common), hepatic encephalopathy, acute kidney injury and/or hepatorenal syndrome, or bleeding from esophageal or gastric varices. These events severely impact life expectancy, and therefore, risk stratification is imperative in this patient cohort. As a result, in literature, one can find a multitude of different risk stratification models and variants thereof. This study is will be used for benchmarking and evaluating the most common and recent models in a large cohort of patients with advanced cirrhosis who were treated at the Medical University of Vienna. This study will thus

(i) assess the quality of the current medical care for patients with advanced cirrhosis at the Medical University of Vienna,
(ii) characterize the efficacy of current therapies, and
(iii) identify patients at highest risk of developing severe complications and mortality.

Methods: Patients with decompensated cirrhosis treated at the Medical University of Vienna since 2006 shall be retrospectively evaluated for morbidity and mortality following the first sign of decompensation (ascites, jaundice, variceal bleeding, hepatic encephalopathy, HCC). Prognostic models (i.e. Child-Turcotte-Pugh score and class, Model for End Stage Liver Disease [MELD]-score, MELD-Na score, Acute Kidney Injury Network classification for Acute Kidney Injury, diagnostic criteria for AKI and hepatorenal syndrome of the International Ascites Club, the Modified Classification for AKI in Cirrhosis [C-AKI], etc.) shall be applied where possible and tested for clinical relevance.

Methods and Skills:

Retrospective data analysis; medical statistics