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 study To 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 methods One hundred and seventy-four cases of...

This paper will discuss the dynamics of steel production in Poland in light of the forecasts of tendencies under conditions of decarbonization. The research presented will be an attempt, using data from 2006 to 2023, to create econometric models and forecast production volumes until 2028, along with influencing factors. The obtained models were compared by calculating their error metrics. Based on the conducted econometric models, the critical determinants of the decarbonization of the industry have been established. Forecasts of the volume of steel production in Poland are downward in the face of the increasingly clear emphasis on strategic investments in low-emission technologies. This paper consists of two research parts. The first concerns the forecasting of steel production volume, and the second concerns the modeling of the steel production process, taking into account the key determinants of technological processes (EAF and BOF). Forecasts were calculated for each econometric model. This analysis is a contribution to a broader discussion on industrial adaptation and sustainable development in the steel sector. The developed models and forecasts can provide decision-makers and industry stakeholders with important information at the stage of the decision-making process concerned with developing a strategy for the decarbonization of steelmaking processes. In Poland, two technologies of steel production are used: BOF and EAF. In accordance with the assumptions of deep decarbonization, BF-BOF technology must be replaced by DRI-EAF technology.

The transition toward human-centered innovation models, as reflected in Industry 5.0 frameworks, calls for the integration of sustainability and digital ethics into higher education. Despite the growing international discourse, little is known about how systematically these dimensions are embedded in curricula in Central and Eastern Europe. This study addresses this gap by analyzing the extent to which Polish higher education institutions (HEIs) incorporate elements of sustainable development and digital ethics into their educational programs. Drawing on survey data from 187 Polish HEIs, we employed Cramér’s V and chi-square tests to explore bivariate associations, multiple correspondence analysis (MCA) to examine patterns among categorical variables, and ordinal logistic regression to identify key predictors of curricular integration. The results reveal that institutions offering Industry 5.0-oriented specializations and maintaining regular cooperation with enterprises are significantly more likely to achieve full integration of sustainability and ethics, whereas many others remain at a stage of only partial adoption. These findings underscore the uneven progress of curricular reforms and highlight the importance of institutional capacity and external partnerships. This study contributes to theory by extending institutional and resource-based perspectives to curriculum innovation, and it contributes to practice by recommending targeted accreditation standards, cross-sector partnerships, and interdisciplinary modules (e.g., “Artificial Intelligence and Society,” “Sustainable Technology Futures”) as concrete mechanisms for embedding ethical and sustainable innovation competencies in higher education. Implications for policy, institutional practice, and future research are discussed.