Prediction of Intrauterine Growth Restriction and Preeclampsia Using Machine Learning-Based Algorithms: A Prospective Study

(1) Background: Prenatal care providers face a continuous challenge in screening for intrauterine growth restriction (IUGR) and preeclampsia (PE). In this study, we aimed to assess and compare the predictive accuracy of four machine learning algorithms in predicting the occurrence of PE, IUGR, and their associations in a group of singleton pregnancies; (2) Methods: This observational prospective study included 210 singleton pregnancies that underwent first trimester screenings at our institution. We computed the predictive performance of four machine learning-based methods, namely decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF), by incorporating clinical and paraclinical data; (3) Results: The RF algorithm showed superior performance for the prediction of PE (accuracy: 96.3%), IUGR (accuracy: 95.9%), and its subtypes (early onset IUGR, accuracy: 96.2%, and late-onset IUGR, accuracy: 95.2%), as well as their association (accuracy: 95.1%). Both SVM and NB similarly predicted IUGR (accuracy: 95.3%), while SVM outperformed NB (accuracy: 95.8 vs. 94.7%) in predicting PE; (4) Conclusions: The integration of machine learning-based algorithms in the first-trimester screening of PE and IUGR could improve the overall detection rate of these disorders, but this hypothesis should be confirmed in larger cohorts of pregnant patients from various geographical areas.

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.

Fresh vs. frozen embryo transfers in patients with KIR Bx haplotype: impact on reproductive outcomes

OBJECTIVE

A controversy persists over whether or not the type of embryo transfer (ET) influences reproductive outcomes. This study aimed to evaluate the reproductive outcomes of pregnant patients undergoing their first in vitro fertilization procedure and explore the influence of various KIR genotypes on these reproductive outcomes.

PATIENTS AND METHODS

Prospective enrollment of patients with infertility who sought treatment at Origyn Fertility Center in Iasi, Romania, was conducted between January 2019 and March 2023. Descriptive statistics and average treatment effects (ATE) using propensity-score matching were employed to analyze our data.

RESULTS

Our results indicated that both groups were homogenous regarding baseline characteristics. When we evaluated the ATE of fresh vs. frozen ET on the main outcomes, we discovered that only frozen ET significantly improved the pregnancy rates (ATE: 0.17, 95% CI: 0.04-0.30, p=0.011) and live birth rates (ATE: 0.36, 95% CI: 0.02-1.19, p=0.03). The miscarriage rates were similar between the two groups. None of the evaluated KIR genotypes had a significant influence on the ATE corresponding to fresh and frozen ET.

CONCLUSIONS

KIR screening is not necessary before an IVF cycle, except for specific situations such as recurrent pregnancy loss or recurrent implantation failure.

The Effects of Perilla frutescens Extracts on IgA Nephropathy: A Systematic Review and Meta-Analysis

(1) Background: Chronic renal disorders (CRD) are associated with significant comorbidities and necessitate complex therapeutic management. As time passed, Perilla frutescens (PF) became a promising therapeutic option for CRD. The aim of this systematic review and meta-analysis was to outline the therapeutic effects of PF extracts on various models of immunoglobulin a (IgA) nephropathy; (2) Methods: Medline, Embase, and Cochrane databases were used to find relevant studies. All prospective interventional studies that evaluated the effect of PF extract versus placebo on rat models of chronic renal disorders were assessed according to the international guidelines; (3) Results: Our search yielded 23 unique records, out of which only five were included in the analysis. Our results showed that administration of PF extracts led to a statistically significant reduction in proteinuria and PCNA levels in rats that received high doses of the extract as well as in the PCNA level and DNA synthesis in rats that received low doses of the extract. The evaluated outcomes benefited from a low degree of heterogeneity; (4) Conclusions: Some of the evaluated outcomes were significantly reduced by both high and low doses of extracts from Perilla frutescens. Further studies are needed to determine the exact effect over IgA nephropathy in human subjects.

Predicting Preterm Birth with Strain Ratio Analysis of the Internal Cervical Os: A Prospective Study

(1) Background: Cervical elastography is a new concept that could allow clinicians to assess cervical consistency in various clinical scenarios. We aimed to evaluate the predictive performance of the strain ratio (SR) at the level of the internal os, either individually or in combination with other parameters, in the prediction of spontaneous preterm birth (PTB) at various gestational ages. (2) Methods: This prospective study included 114 pregnant patients with a high-risk profile for PTB who underwent cervical elastography during the second trimester. Clinical and paraclinical data were assessed using univariate analysis, logistic regression, and sensitivity analysis. (3) Results: The SR achieved an area under the receiver operating curve (AUROC) value of 0.850, a sensitivity of 85.71%, and a specificity of 84.31% in the prediction of PTB before 37 weeks of gestation. The combined model showed superior results in terms of accuracy (AUROC = 0.938), sensitivity (92.31%), and specificity (95.16%). When considering PTB subtypes, the highest AUROC value (0.80) and accuracy (95.61%) of this marker were achieved in the prediction of extremely preterm birth, before 28 weeks of gestation. (4) Conclusions: The SR achieved an overall good predictive performance in the prediction of PTB and could be further evaluated in various cohorts of patients.

Unraveling the Efficacy of Therapeutic Interventions for Short Cervix: Insights from a Retrospective Study for Improved Clinical Management

Background and Objectives: Preterm birth (PTB) is associated with important neonatal mortality and morbidity. The aim of this study was to retrospectively evaluate the average treatment effects on the treated and the efficacity of various therapeutic interventions for PTB in a cohort of patients with singleton pregnancies and short cervical lengths. Materials and Methods: This observational retrospective study included 1146 singleton pregnancies at risk of PTB that were segregated into the following groups: intravaginal progesterone (group 1), Arabin pessary (group 2), McDonald cerclage (group 3), intravaginal progesterone and Arabin pessary (group 4), and intravaginal progesterone and cerclage (group 5). Their treatment effects were evaluated and compared. Results: All evaluated therapeutic interventions significantly reduced the occurrence of late and early preterm births. The risk of late and early PTB was lowered for those pregnant patients who received progesterone and pessaries or progesterone and cerclage in comparison with those who received only progesterone. The extremely PTB risk of occurrence was significantly lowered only by the administration of progesterone in association with cervical cerclage in comparison with progesterone monotherapy. Conclusions: The combined therapeutic interventions had the highest efficacy in preventing preterm birth. An individualized evaluation is needed to establish the best therapeutic approach in particular cases.

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.

Biochemical Effects and Therapeutic Application of Vitamin C (C6H8O6) on COVID-19 Infection

The current pandemic of COVID-19 infection worries the world, due to high morbidity and mortality. Various strategies for infection control, including nutritional interventions, have been considered, given the extremely rapid spread of the disease, the lack of specific effective and safe antiviral treatment and the difficulty of having a vaccine in the near future. Vitamin C, long known for its antioxidant and anti-infective effects, has been analyzed from the perspective of biochemical mechanisms with potential benefits in patients with severe COVID-19 infection. Favorable clinical results have been reported after intravenous administration of high doses of Vitamin C, but confirmation of these data requires extensive studies.

Urethane suppresses rat lung inducible cyclooxygenase and nitric oxide synthase mRNA levels

OBJECTIVE AND DESIGN

The purpose of the present study was to evaluate the effect of urethane, pentobarbital sodium and ketamine-xylazine anesthesia upon constitutive and inducible cyclooxygenase (COX-1; COX-2) and nitric oxide synthase (eNOS; iNOS) mRNA levels in the lung.

METHODS

mRNA levels were determined by the semiquantitative RT-PCR technique.

TREATMENT

Urethane (1.1 g/kg ip), Pentobarbital Sodium (40 mg/kg ip), and ketamine (85 mg/kg) - xylazine (15 mg/kg, im). Non-anesthetized animals served as controls.

MATERIAL

Sprague-Dawley rat lungs

RESULTS

Urethane significantly decreased COX-1 and COX-2 mRNA levels to 30% of control values. This agent had no effect upon eNOS, but completely suppressed iNOS mRNA levels. Pentobarbital sodium and ketamine had no effect on the mRNA levels for COX-1 and COX-2 the lung.

CONCLUSIONS

Urethane has a suppressive effect on COX and iNOS RNA message in the lung and for this reason it should be avoided as an anesthetic when lung inflammatory processes are experimentally evaluated in the rat.