Principal Component Analysis is one of the data mining methods that can be used to analyze multidimensional datasets. The main objective of this method is a reduction of the number of studied variables with the mainte- nance of as much information as possible, uncovering the structure of the data, its visualization as well as classification of the objects within the space defined by the newly created components. PCA is very often used as a preliminary step in data preparation through the creation of independent components for further analysis. We used the PCA method as a first step in analyzing data from IVF (in vitro fertilization). The next step and main purpose of the analysis was to create models that predict pregnancy. Therefore, 805 different types of IVF cy- cles were analyzed and pregnancy was correctly classified in 61-80% of cases for different analyzed groups in obtained models.

Introduction: The issue of inequalities in the use of health services and health inequalities between urban and rural dwellers is a subject of numerous scientific reports, but similar publications on dental health are scarce. Objective: The aim of this study is to assess the correlations...

Infertility is currently a common problem with causes that are often unexplained, which complicates treatment. In many cases, the use of ART methods provides the only possibility of getting pregnant. Analysis of this type of data is very complex. More and more often, data mining methods or artificial intelligence techniques are appropriate for solving such problems. In this study, classification trees were used for analysis. This resulted in obtaining a group of patients characterized most likely to get pregnant while using in vitro fertilization

The study was conducted to analyze urinary tract infections (UTI) in children by considering epidemiology and antibiotic resistance patterns of pathogens in accordance with inflammatory parameters. The research included 525 patients who demonstrated 627 episodes of UTI. The increasing resistance of bacteria was observed over the years covered by the study (p < 0.001). There was a significant increase of resistance to amoxicillin with clavulanic acid (p = 0.001), gentamicin (p = 0.017) and ceftazidime (p = 0.0005). According to the CART method, we managed to estimate C-reactive protein (CRP), procalcitonin (PCT) and white blood cell (WBC) values, in which antibiotic sensitivity was observed. In children with CRP > 97.91 mg/L, there was a high percentage of sensitive cases to amoxicillin with clavulanic acid (87.5%). Values of WBC above 14.45 K/µL were associated with E. coli more sensitivity to ampicillin. 100% of children with CRP > 0.42 mg/L and PCT ≤ 6.92 ng/mL had confirmed sensitivity to cefuroxime. Concerning sensitivity to gentamicin, the most optimal cut-off point of WBC was >7.80 K/µL, while in the case of nitrofurantoin, it was CRP value > 0.11 mg/L (which was presented in 98.50% of children). These results may guide us with antibiotic therapy and help to inhibit increasing antibiotic resistance.

Objectives To assess the impact of classical socioeconomic factors on the use and non-use of dental services on a representative sample of Polish population. Methods The study was based on face-to-face surveys conducted by GUS (Statistics Poland) on 13,376 respondents in 2010 and 12,532 individuals in 2013. Results The percentage of people using dental services in the highest income group was approximately twice as high as that in the lowest one (Q1: 7.0% vs. Q5: 16.4%), with the same being true for education (the lowest education group: 8.3% vs. the highest education group: 18.0%), and place of residence (inhabitants of rural areas: 9.2% vs. inhabitants of largest cities: 15.9%) in 2013. The analysis has shown the disparities in not using dental services when in need to be less clear-cut. Conclusions The conducted research, based on two independent periods, a representative population sample, univariate analysis and the multivariate regression model has revealed pronounced social inequalities in dental care use. It is a challenge to determine the factors which contribute most to health inequalities and the interventions which are most effective in reducing them.

It is hypothesized that growth hormone deficiency (GHD) is associated with increased oxidative stress (OS), contributing to elevated cardiovascular risk. This preliminary study evaluates changes in OS markers and cardiovascular biomarkers in 15 adult patients with severe GHD undergoing 12 months of recombinant human growth hormone (rhGH) therapy. IGF-1 concentrations increased significantly following 6 and 12 months of therapy (p = 0.0003 and p = 0.0001, respectively). These changes were accompanied by a significant decrease in endothelin-1 (ET-1) levels at 12 months (p = 0.007), as well as reductions in asymmetric dimethylarginine (ADMA) levels at both 6 and 12 months (p = 0.01 for each timepoint). Total oxidative capacity (TOC) decreased significantly after 6 months of therapy (p = 0.02), followed by a significant increase at 12 months (p = 0.04), whereas total antioxidant capacity (TAC) showed a significant increase at 12 months (p = 0.02). Tissue fat % showed significant reductions at 6 months (p = 0.006), suggesting early improvements in body composition. Correlation analyses indicated negative associations between IGF-1 and TOC (p < 0.006; R = −0.73), and positive associations with TAC (p < 0.001; R = 0.83). These findings suggest that rhGH therapy in adult patients with severe GHD reduces OS and cardiovascular risk through the modulation of biomarkers and improved body composition. This study explores the role of rhGH therapy in reducing cardiovascular risks in GHD, emphasizing the importance of individualized treatment approaches.