Background and aim: The aim of this study was to assess the diagnostic performance of new morphology-related indices and Child–Turcotte–Pugh (CTP) and Model for End-Stage Liver Disease (MELD) scores during hospitalization in predicting the onset of bacterial infection in patients with liver cirrhosis. Material and methods: A total of 171 patients (56.9% males; median age 59 years; total number of hospitalizations 209) with liver cirrhosis were included in this observational study. The diagnosis of cirrhosis was made on the basis of clinical, biochemical, ultrasonic, histological, and endoscopic findings. The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), modified aspartate aminotransferase-to-platelet ratio index (APRI), aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), Fibrosis-4 index (FIB-4), platelet-to-lymphocyte ratio (PLR), neutrophil-to-monocyte ratio (NMR), and CTP and MELD scores were calculated for the cases of patients with cirrhosis. Results: Bacterial infection was diagnosed in 60 of the 209 (28.7%) hospitalizations of patients with cirrhosis. The most common infections were urinary tract infection (UTI), followed by pneumonia and sepsis. The more severe the liver failure, the greater the bacterial infection prevalence and mortality. Patients with decompensated liver cirrhosis were infected more often than subjects with compensated cirrhosis (50.0% vs. 12.9%, p = 0.003). The calculated MELD score, CTP, NLR, LMR, AAR, monocyte count, and C-reactive protein (CRP) concentration were also related to the bacterial infection prevalence, and mortality areas under the curve (AUC) were 0.629, 0.687, 0.606, 0.715, 0.610, 0.648, and 0.685, respectively. The combined model with two variables (LMR and CTP) had the best AUC of 0.757. The most common bacteria isolated from patients with UTI were Escherichia coli, Enterococcus faecalis, and Klebsiella pneumonia. Gram-negative bacteria were also responsible for spontaneous bacterial peritonitis (SBP), and together with gram-positive streptococci and staphylococci, these microorganisms were isolated from blood cultures of patients with sepsis. Significant differences were found between CTP classification, MELD score, NLR, LMR, AAR, CRP, and PLR in patients with cirrhosis with, or without, bacterial infection. Conclusions: Bacterial infection prevalence is relatively high in patients with liver cirrhosis. Although all analyzed scores, including the LMR, NLR, aspartate aminotransferase (AST)/alanine aminotransferase (ALT), CRP, CTP, and MELD, allowed the prediction of bacterial occurrence, the LMR had the highest clinical utility, according to the area under the curve (AUC) and odds ratio (OR).

Aim of the studyTo assess the performance of Child-Turcotte-Pugh (CTP) and Model for End-Stage Liver Disease (MELD) scores’ kinetics during hospitalization in predicting in-hospital mortality in patients with liver cirrhosis.Material and methodsOne hundred and seventy-four cases of hospitalized liver cirrhosis patients were selected. The diagnosis of cirrhosis was made based on clinical, biochemical, ultrasonic, histological, and endoscopic findings and results. CTP and MELD scores at admission and ΔCTP and ΔMELD were calculated. Univariate and multivariate logistic regression and receiver-operating characteristic (ROC) curve analysis were performed. In the models, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The area under the ROC curve (AUC) was used to measure the accuracy. For the optimal cutoff point, sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) were calculated. The Kaplan-Meier method was used to construct survival curves, and the log-rank test was used to compare time to death, with respect to MELD and CTP categories.ResultsAmong the assessed scores, the highest area under the ROC curve (AUC) in univariate logistic regression analysis was calculated for ΔMELD ≥ 1, followed by ΔCTP ≥ 1, CTP > 8, and MELD > 17. Based on the selected criteria, multivariate models were created that were characterized by an outstanding ability to predict the in-hospital mortality.ConclusionsIn-hospital mortality is relatively high in patients with liver cirrhosis. The combination of CTP and MELD scoring methods, combined with their kinetics, allows for the prediction of short-term mortality.

This research aimed to investigate how health behaviors changed during the COVID-19 pandemic and to identify the economic factors influencing these changes. There were considered income situation and labor market situation as the potential economic factors. Additionally, in the analysis, there were included other characteristics: age, gender, and education level. Health condition was considered through the prism of certain unhealthy characteristics: alcohol consumption, smoking cigarettes, lack of physical activity, and unfavorable eating habits. The study was carried out on the stratified sample of adult inhabitants of Poland (N=1067) in November 2020. To achieve the aim multiple correspondence analysis was used. The results show that the pandemic has changed health behaviors. The negative changes mainly concerned physical activity and eating habits, and only one-sixth reported an increase in alcohol use and cigarette smoking. An increase in negative health behavior was mostly associated with the following characteristics: male, lower age (between 30 and 59), employed persons, tertiary education, and higher income (the fourth and the fifth income quintile group). The exception was a physical activity, where all changes (both negative and positive) were associated with females, people with basic vocational and secondary education, the second and third quintile group, pensioners and retirees, 60 and above age.

The author used discrete-time event history methods to study poverty and non-poverty survival time of urban and rural households. To analyse there were used nonparametric estimators of hazard function and logit models, which are discrete-time survival models. On the basis on conducted analysis it can be concluded that rural households survive shorter in non-poverty and simultaneously longer in poverty than urban households. Besides, urban households have more chance of poverty exit and less chance of poverty entry than rural households.

The health of individuals and communities depends on various factors. Medical condition is