Can a presepsin (SCD14-ST) obtained from tracheal aspirate be a biomarker for early-onset neonatal sepsis

© 2020, University of Kragujevac, Faculty of Science. All rights reserved. In absence of clear clinical signs and clear definition, neonatal sepsis is still one of the major cause of morbidity and mortality. Most researchs in past time was directional on finding new biomarkers with greater sensitivity and specific-ity in detection of neonatal sepsis. The aim of our study was to investigate if presepsin obtained from tracheal asprate in intubated newborns, can be a novel biomarker of systemic bacterial infection. Our ‘’case control’’ study included 60 newborns, 11 with suspected neonatal sepsis. Tracheal aspirate for examination was taken in the usual toilets, in asep-tic conditions, by lavage with 2 ml of 0.9% NaCl in Mucus suction set. In the same day were mesured presepsin (blood), CRP, PCT, leukocytes and neutrophyls, as well as blood cul-ture. Our research showed higher levels for PCT and prese-psin (blood) in septic newborns, as well as in newborns with clinical signs of SIRS. Presepsin obtained from a tracheal aspirate had high score for septic newborns. As the coefficients of simple linear correlation showed, there was quantitative agreement between presepsin (blood) with presepsin (trache-al aspirate)-increase in the value of one leads to an increase in other. In conjunction with an already validated markers of infection, presepsin obtained from tracheal aspirate cam be turned on in diagnostic procedures

Wandering spleen-a possible cause of adrenal ”mass“-case report

Wandering spleen is a very rare clinical condition character-ized by spleen absence in the normal anatomical location in the upper left quadrant of the abdomen and its presence at another location in the abdomen or pelvis. The ectopic spleen is extremely rare in children, where its increased mobility is the result of a congenital disturbance of the fixation for the anterior wall due to the absence or weakness of the supporting ligaments. Wandering spleen is usually asymptomatic, but its torsion is possible, as well as infarction or rupture which demand an urgent diagnosis and surgical treatment. The diagnosis of wandering spleen can easily be overlooked due to low incidence and insufficient clinical experience, which multiplies patient's risk from life-threatening conditions. We present a case of wandering spleen in an 11-year-old girl with acute abdominal pain, which after ultrasound examination raised suspicion on the right adrenal gland tumor. Additional diagnostics verified an ectopic spleen in the right adrenal box, after which the recommended preventive splenopexy was seriously considered. Due to the fixation of the vital spleen in the new position, but also the negative attitude of the parents towards the surgical intervention, clinical monitoring was selected, with exclusion of intense physical activity that carries the risk of traumatization of the spleen. As the girl has been in good health for over 3 years and without symptoms, we consider that the selection of conservative access although difficult, was correct. We hope that our experience in treating wandering spleen in girls will increase the number of valid facts about this rare condition

A Novel Approach of Determining the Risks for the Development of Hyperinsulinemia in the Children and Adolescent Population Using Radial Basis Function and Support Vector Machine Learning Algorithm

Hyperinsulinemia is a condition with extremely high levels of insulin in the blood. Various factors can lead to hyperinsulinemia in children and adolescents. Puberty is a period of significant change in children and adolescents. They do not have to have explicit symptoms for prediabetes, and certain health indicators may indicate a risk of developing this problem. The scientific study is designed as a cross-sectional study. In total, 674 children and adolescents of school age from 12 to 17 years old participated in the research. They received a recommendation from a pediatrician to do an OGTT (Oral Glucose Tolerance test) with insulinemia at a regular systematic examination. In addition to factor analysis, the study of the influence of individual factors was tested using RBF (Radial Basis Function) and SVM (Support Vector Machine) algorithm. The obtained results indicated statistically significant differences in the values of the monitored variables between the experimental and control groups. The obtained results showed that the number of adolescents at risk is increasing, and, in the presented research, it was 17.4%. Factor analysis and verification of the SVM algorithm changed the percentage of each risk factor. In addition, unlike previous research, three groups of children and adolescents at low, medium, and high risk were identified. The degree of risk can be of great diagnostic value for adopting corrective measures to prevent this problem and developing potential complications, primarily type 2 diabetes mellitus, cardiovascular disease, and other mass non-communicable diseases. The SVM algorithm is expected to determine the most accurate and reliable influence of risk factors. Using factor analysis and verification using the SVM algorithm, they significantly indicate an accurate, precise, and timely identification of children and adolescents at risk of hyperinsulinemia, which is of great importance for improving their health potential, and the health of society as a whole

Unveiling the Comorbidities of Chronic Diseases in Serbia Using ML Algorithms and Kohonen Self-Organizing Maps for Personalized Healthcare Frameworks

In previous years, significant attempts have been made to enhance computer-aided diagnosis and prediction applications. This paper presents the results obtained using different machine learning (ML) algorithms and a special type of a neural network map to uncover previously unknown comorbidities associated with chronic diseases, allowing for fast, accurate, and precise predictions. Furthermore, we are presenting a comparative study on different artificial intelligence (AI) tools like the Kohonen self-organizing map (SOM) neural network, random forest, and decision tree for predicting 17 different chronic non-communicable diseases such as asthma, chronic lung diseases, myocardial infarction, coronary heart disease, hypertension, stroke, arthrosis, lower back diseases, cervical spine diseases, diabetes mellitus, allergies, liver cirrhosis, urinary tract diseases, kidney diseases, depression, high cholesterol, and cancer. The research was developed as an observational cross-sectional study through the support of the European Union project, with the data collected from the largest Institute of Public Health “Dr. Milan Jovanovic Batut” in Serbia. The study found that hypertension is the most prevalent disease in Sumadija and western Serbia region, affecting 9.8% of the population, and it is particularly prominent in the age group of 65 to 74 years, with a prevalence rate of 33.2%. The use of Random Forest algorithms can also aid in identifying comorbidities associated with hypertension, with the highest number of comorbidities established as 11. These findings highlight the potential for ML algorithms to provide accurate and personalized diagnoses, identify risk factors and interventions, and ultimately improve patient outcomes while reducing healthcare costs. Moreover, they will be utilized to develop targeted public health interventions and policies for future healthcare frameworks to reduce the burden of chronic diseases in Serbia

Ensemble Model for Predicting Chronic Non-Communicable Diseases using Latin Square Extraction and Fuzzy-Artificial Neural Networks from 2013 to 2019

Background: The presented study tracks the increase or decrease in the prevalence of seventeen different chronic non-communicable diseases in Serbia. This analysis considers factors such as region, age, and gender and is based on data from two national cross-sectional studies conducted in 2013 and 2019. The research aims to accurately identify the regions with the highest percentage of affected individuals, as well as their respective age and gender groups. The ultimate goal is to facilitate organized, free preventive screenings for these population categories within a very short time-frame in the future. Materials and methods: The study analyzed two cross-sectional studies conducted between 2013 and 2019, using data obtained from the Institute of Public Health of Serbia. Both studies involved a total of 27801 participants. The study compared the performance of Decision Tree and Support Vector Regressor models with artificial neural network (ANN) models that employed two encoding functions. The new methodology for the ANN-L36 model was based on artificial neural networks constructed using a Latin square (L36) design, incorporating Taguchi's robust design optimization. Results: The results of the analysis from three different models have shown that cardiovascular diseases are the most prevalent illnesses among the population in Serbia, with hypertension as the leading condition in all regions, particularly among individuals aged 64 to 75 years, and more prevalent among females. In 2019, there was a decrease in the percentage of the leading disease, hypertension, compared to 2013, with a decrease from 34.0% to 32.2%. The ANN-L36 model with Fuzzy encoding function demonstrated the highest precision, achieving the smallest relative error of 0.1%. Conclusion: To date, no studies have been conducted at the national level in Serbia to comprehensively track and identify chronic diseases in the manner proposed by this study. The model presented in this research will be implemented in practice and is set to significantly contribute to the future healthcare framework in Serbia, shaping and advancing the approach towards addressing these conditions. Furthermore, experimental evidence has shown that Taguchi's optimization approach yields the best results for identifying various chronic non-communicable diseases.</p

Internet Addiction among Secondary School Students Conditioned By Gender and Age

Modern forms of addiction are present very much in adolescents today. Internet dependency is a form of addiction that manifests itself as an individual's state of affairs. The use of the Internet has become the most important activity in life in relation to other everyday tasks and activities, to this extent and in that way, to isolate him from other social activities and to bring harmful consequences both to himself and to his family and the environment. Characteristic cases in adolescents that occur are insomnia, family disagreements, delays in school, or the absence and neglect of school obligations, nervousness, fatigue, physical changes such as neglecting personal hygiene, weight loss or other obesity, and etc. The number of Internet users and their addicts is growing every day. With this research, we want to determine whether it depends on gender and age and to what extent does it exist among high school students

Internet Addiction among Secondary School Students Conditioned By Gender and Age

Modern forms of addiction are present very much in adolescents today. Internet dependency is a form of addiction that manifests itself as an individual's state of affairs. The use of the Internet has become the most important activity in life in relation to other everyday tasks and activities, to this extent and in that way, to isolate him from other social activities and to bring harmful consequences both to himself and to his family and the environment. Characteristic cases in adolescents that occur are insomnia, family disagreements, delays in school, or the absence and neglect of school obligations, nervousness, fatigue, physical changes such as neglecting personal hygiene, weight loss or other obesity, and etc. The number of Internet users and their addicts is growing every day. With this research, we want to determine whether it depends on gender and age and to what extent does it exist among high school students