Pregnancy Outcomes in Patients with Urosepsis and Uncomplicated Urinary Tract Infections-A Retrospective Study.

Background and Objectives: Urinary tract infections (UTIs) are an important cause of perinatal and maternal morbidity and mortality. The aim of this study was to describe and compare the main pregnancy outcomes among pregnant patients with complicated and uncomplicated UTIs; Materials and Methods: This retrospective study included 183 pregnant patients who were evaluated for uncomplicated UTIs and urosepsis in the Urology Department of 'C.I. Parhon' University Hospital, and who were followed up at a tertiary maternity hospital-'Cuza-voda' from Romania between January 2014 and October 2023. The control group (183 patients) was randomly selected from the patient's cohort who gave birth in the same time frame at the maternity hospital without urinary pathology. Clinical and paraclinical data were examined. Descriptive statistics and a conditional logistic regression model were used to analyze our data. Results: Our results indicated that patients with urosepsis had increased risk of premature rupture of membranes (aOR: 5.59, 95%CI: 2.02-15.40, p < 0.001) and preterm birth (aOR: 2.47, 95%CI: 1.15-5.33, p = 0.02). We could not demonstrate a statistically significant association between intrauterine growth restriction and pre-eclampsia with the studied urological pathologies. Conclusions: Careful UTI screening during pregnancy is needed for preventing maternal-fetal complications.

Investigating the Association between Serum and Hematological Biomarkers and Neonatal Sepsis in Newborns with Premature Rupture of Membranes: A Retrospective Study.

(1) Background: Neonatal early-onset sepsis (EOS) is associated with important mortality and morbidity. The aims of this study were to evaluate the association between serum and hematological biomarkers with early onset neonatal sepsis in a cohort of patients with prolonged rupture of membranes (PROM) and to calculate their diagnostic accuracy. (2) Methods: A retrospective cohort study was conducted on 1355 newborns with PROM admitted between January 2017 and March 2020, who were divided into two groups: group A, with PROM ≥ 18 h, and group B, with ROM < 18 h. Both groups were further split into subgroups: proven sepsis, presumed sepsis, and no sepsis. Descriptive statistics, analysis of variance (ANOVA) and a Random Effects Generalized Least Squares (GLS) regression were used to evaluate the data. (3) Results: The statistically significant predictors of neonatal sepsis were the high white blood cell count from the first (p = 0.005) and third day (p = 0.028), and high C-reactive protein (CRP) values from the first day (p = 0.004). Procalcitonin (area under the curve-AUC = 0.78) and CRP (AUC = 0.76) measured on the first day had the best predictive performance for early-onset neonatal sepsis. (4) Conclusions: Our results outline the feasibility of using procalcitonin and CRP measured on the first day taken individually in order to increase the detection rate of early-onset neonatal sepsis, in the absence of positive blood culture.

Comparative Epidemiological and Clinical Outcomes on COVID-19 and Seasonal Influenza Hospitalized Patients during 2023.

COVID-19 and influenza are highly contagious respiratory viral diseases and priority global public health concerns. We conducted a retrospective observational study of COVID-19 and/or influenza hospitalized cases, during 2023. We identified 170 influenza cases, 150 COVID-19 cases and 3 co-infections. Overall, 29.10% of patients had at least one COVID-19 vaccine dose and 4.6% received the seasonal Flu vaccine. The demographic data found older patients in the COVID-19 group and a higher index of the comorbidities, mainly due to chronic heart diseases, hypertension, and diabetes. Fever, chills, and rhinorrhea were more frequently related to influenza, while cough was prevalent in COVID-19. Antibiotics were more used in influenza than COVID-19, either pre-hospital or in-hospital. The mortality rate within the first 30 days from the onset of the respiratory infection was higher in influenza compared to COVID-19. We concluded that the COVID-19 clinical picture in hospitalized patients is changing to influenza-like symptoms. The evolution is variable, related to chronic comorbidities, but influenza had more frequent severe forms. All through 2023, due to poor vaccination rates, COVID-19 and influenza have continued to cause numerous hospitalizations, and a new strategy for efficient vaccinations is required.

Metal Oxide Nanoparticles in Food Packaging and Their Influence on Human Health.

It is a matter of common knowledge in the literature that engineered metal oxide nanoparticles have properties that are efficient for the design of innovative food/beverage packages. Although nanopackages have many benefits, there are circumstances when these materials are able to release nanoparticles into the food/beverage matrix. Once dispersed into food, engineered metal oxide nanoparticles travel through the gastrointestinal tract and subsequently enter human cells, where they display various behaviors influencing human health or wellbeing. This review article provides an insight into the antimicrobial mechanisms of metal oxide nanoparticles as essential for their benefits in food/beverage packaging and provides a discussion on the oral route of these nanoparticles from nanopackages to the human body. This contribution also highlights the potential toxicity of metal oxide nanoparticles for human health. The fact that only a small number of studies address the issue of food packaging based on engineered metal oxide nanoparticles should be particularly noted.

Machine Learning Approaches for the Prediction of Hepatitis B and C Seropositivity.

(1) Background: The identification of patients at risk for hepatitis B and C viral infection is a challenge for the clinicians and public health specialists. The aim of this study was to evaluate and compare the predictive performances of four machine learning-based models for the prediction of HBV and HCV status. (2) Methods: This prospective cohort screening study evaluated adults from the North-Eastern and South-Eastern regions of Romania between January 2022 and November 2022 who underwent viral hepatitis screening in their family physician's offices. The patients' clinical characteristics were extracted from a structured survey and were included in four machine learning-based models: support vector machine (SVM), random forest (RF), naïve Bayes (NB), and K nearest neighbors (KNN), and their predictive performance was assessed. (3) Results: All evaluated models performed better when used to predict HCV status. The highest predictive performance was achieved by KNN algorithm (accuracy: 98.1%), followed by SVM and RF with equal accuracies (97.6%) and NB (95.7%). The predictive performance of these models was modest for HBV status, with accuracies ranging from 78.2% to 97.6%. (4) Conclusions: The machine learning-based models could be useful tools for HCV infection prediction and for the risk stratification process of adult patients who undergo a viral hepatitis screening program.

Risk Factors Associated with Severe Disease and Intensive Care Unit Admission of Pregnant Patients with COVID-19 Infection-A Retrospective Study.

(1) Background: Pregnant patients with severe forms of coronavirus disease 2019 (COVID-19) can experience adverse pregnancy outcomes. The aim of this study was to retrospectively assess the risk factors associated with admission to the intensive care unit (ICU) of pregnant patients with COVID-19, as well as the pregnancy outcomes of these patients; (2) Methods: Medical records of 31 pregnant patients with COVID-19 admitted to three clinical hospitals from Romania, between October 2020 and November 2021 were examined. The patients were segregated into two groups depending on their clinical evolution: non-ICU admission (n = 19) or ICU admission (n = 12). Clinical and paraclinical findings were evaluated using univariate analysis, and the association of significant risk factors with maternal ICU admission was assessed using a multivariate analysis. Pregnancy outcomes of these patients were also recorded; (3) Results: Pulmonary disease, cough, dyspnea, leukocytosis, thrombocytosis, high serum values of transaminases, serum ferritin, and increased duration of hospital admission were identified as significant risk factors associated with maternal admission to the ICU. No significant differences regarding pregnancy outcomes were noted between the evaluated patients; (4) Conclusions: Specific risk factor identification in pregnant patients with severe forms of COVID-19 could improve the patient's management.