Aim: To evaluate the performance of 2D shear-wave elastography from General Electric (2D-SWE.GE) for the noninvasiveassessment of liver fibrosis and to identify liver stiffness (LS) cut-off values for predicting different stages of fibrosisusing Transient Elastography (TE) as the reference method. Material and method: We included 331 consecutive subjectswith or without chronic hepatopathies in whom LS was evaluated in the same session by means of 2 elastographic techniques:TE and 2D-SWE.GE. Reliable LS measurements were defined for TE as the median value of 10 measurements with a successrate of ≥60% and an interquartile range (IQR)<30% and for 2D-SWE.GE as the median value of 10 measurements acquiredin a homogenous area and an IQR<30%. To discriminate between TE fibrosis stages we used the following cut-offs: F2- 7;F3- 9.5 and F4- 12kPa. Results: Reliable LS measurements were obtained in 95.8% subjects by 2D-SWE.GE, and 94.2%by TE (p=0.44). Based on TE cut-off values we divided our cohort into four groups: F<2: 30.1%; F=2: 10.2%; F=3: 12.2%;F=4: 47.5%. A strong correlation was found between the LS values obtained by the 2 methods: r=0.83, p<0.0001.LS valuesobtained by 2D-SWE.GE were significantly lower than those obtained by TE: 10.14±4.24 kPa vs. 16.72±13.4 kPa (p<0.0001).The best cut-off value for F≥2, F≥3 and for F=4 were 6.7, 8.2 and 9.3 kPa. Conclusions: The best 2D-SWE.GE cut-off valuesfor predicting F≥2, F≥3 and F=4 were 6.7, 8.2 and 9.3kPa.

Studies performed using transient elastography (TE), point shear wave elastography (pSWE) and two-dimensional shear wave elastography (2D-SWE) have shown that these techniques are all feasible and accurate in children for the evaluation of liver fibrosis due to several etiologies. However, for some specific pediatric pathologies, such as biliary atresia, the evidence is still limited. As shown in adults, inflammation is a confounding factor when assessing fibrosis severity and care should be taken when interpreting the results. Due to the scarce comparative data between serological tests and elastography techniques in children, a definite conclusion regarding which is the best cannot be drawn. Neither non-invasive elastographic techniques nor laboratory scores allow determination of the presence and the degree of inflammation, necrosis, iron or copper deposits.

Background and Objectives: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This study assessed how maternal pathologies, medications, and neonatal factors affect the risk of PDA using traditional statistics and ML algorithms: Random Forest (RF) and XGBoost (XGB). Materials and Methods: A retrospective 3-year cohort study of 201 NICU neonates assessed maternal and neonatal factors. Logistic regression (LR) and chi-square analyses identified significant predictors, while ML models enhanced predictive accuracy and pinpointed key PDA factors. Results: LR identified prolonged rupture of membranes (>18 h) as the most significant predictor (OR: 13.03, p < 0.001). The ML models identified gestational age, maternal anemia, prenatal care level, birth weight, prolonged rupture of membranes, medication usage, diabetes, pregnancy-induced hypertension, SARS-CoV-2 infection, and cervical cerclage as key predictors. The RF model had 76.3% accuracy, moderate sensitivity (47.4%), and high specificity (90%). XGB performed better with 81.4% accuracy, an AUC of 0.872, sensitivity of 92.5%, and specificity of 57.9%. Conclusions: This study shows that maternal and neonatal factors significantly influence the risk of PDA. ML, particularly XGBoost, enhances predictive abilities, guiding targeted interventions and improving neonatal outcomes.

Primary lactose intolerance is caused by a genetically programmed loss in lactase production after 5‑6 years of age. Milk and dairy products are often incriminated as a cause of gastrointestinal symptoms. Recent studies show that lactase persistence in adult life correlates with higher anthropometric indexes and an altered metabolic profile. We aimed to assess whether the presence of gene polymorphisms for primary lactose intolerance has an influence on the anthropometric and metabolic profile of children. We conducted a cross‑sectional study, recruiting consecutive children evaluated at the 2nd Pediatric Clinic, Timisoara from May to August 2016. We enrolled 87 children aged 6‑17 years [mean age 10.64±3.51 years; 45 (51.72%) girls]. Subjects were asked to complete an analogue visual scale of symptoms. We measured weight, height, blood pressure and calculated body mass index. The metabolic profile included fasting blood glucose, triglycerides and HDL cholesterol levels. We used strip genotyping to identify gene polymorphisms for primary lactose intolerance. According to the results, our study population was grouped into lactose tolerant (n=42) and lactose intolerant (n=45) groups. No differences were found in regards to weight, height, body mass index and blood pressure between the two study groups. Glucose, triglycerides and HDL cholesterol were similar in the lactose intolerant and lactose tolerant children. The presence of gene polymorphisms for primary lactose intolerance did not influence the children's anthropometric and metabolic profile.

Background: Primary lactose intolerance (PLI) is characterized by the inability to digest lactose. Homozygotes for the lactase gene polymorphisms (CC or GG) are considered to be genetically predisposed to PLI. Still, symptoms may only be present later in life. The evidence supporting a link between PLI, dairy intake, and quality of life (QoL) is limited in children. Aim: This study investigates the link between LCT polymorphisms and suggestive symptoms and the influence of the genetic predisposition to PLI on dairy intake and QoL in Romanian children. Materials and methods: We recruited consecutive children evaluated in our ambulatory clinic. We asked all participants to complete a visual-analog symptoms scale, a dairy intake, and a QoL questionnaire. We used strip genotyping to identify genetic predisposition to PLI. Results: 51.7% of children had a CC genotype, and 34.5% also had a GG genotype. Most children reported no or mild symptoms. Dairy intake and QoL were similar across study groups. Conclusions: Our study shows that genetic predisposition does not necessarily assume the presence of specific symptoms. Genetic predisposition to PLI did not lead to dairy avoidance, nor did it negatively influence our children’s QoL.