Impact of COVID-19 on Patients with Decompensated Liver Cirrhosis.
Tudor Voicu MogaCamelia FonceaRenata BendeAlina PopescuAdrian BurdanDarius HeredeaMirela DanilăBogdan MiutescuIulia RatiuTeofana Otilia Bizerea-MogaIoan SporeaRoxana Lucia SirliPublished in: Diagnostics (Basel, Switzerland) (2023)
The aim of this study was to assess the impact of COVID-19 infection on patients with decompensated liver cirrhosis (DLC) in terms of acute-on-chronic liver failure (ACLF), chronic liver failure acute decompensation (CLIF-AD), hospitalization, and mortality. In this retrospective study, we analyzed patients with known DLC who were admitted to the Gastroenterology Department with COVID-19. Clinical and biochemical data were obtained to compare the development of ACLF, CLIF-AD, days of hospitalization, and the presence of independent factors of mortality in comparison with a non-COVID-19 DLC group. All patients enrolled were not vaccinated for SARS-CoV-2. Variables used in statistical analyses were obtained at the time of hospital admission. A total of 145 subjects with previously diagnosed liver cirrhosis were included; 45/145 (31%) of the subjects were confirmed with COVID-19, among which 45% had pulmonary injury. The length of hospital stay (days) was significantly longer in patients with pulmonary injury compared to those without ( p = 0.0159). In the group of patients with COVID-19 infection, the proportion of associated infections was significantly higher ( p = 0.0041). Additionally, the mortality was 46.7% in comparison with only 15% in the non-COVID-19 group ( p = 0.0001). Pulmonary injury was associated with death during admission in multivariate analysis in both the ACLF ( p < 0.0001) and the non-ACLF ( p = 0.0017) group. COVID-19 significantly influenced disease progression in patients with DLC in terms of associated infections, hospitalization length, and mortality.
Keyphrases
- liver failure
- sars cov
- coronavirus disease
- hepatitis b virus
- respiratory syndrome coronavirus
- pulmonary hypertension
- cardiovascular events
- heart failure
- emergency department
- risk factors
- ejection fraction
- newly diagnosed
- machine learning
- artificial intelligence
- drug induced
- coronary artery disease
- deep learning
- acute respiratory distress syndrome
- big data
- aortic dissection
- mechanical ventilation