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(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.

(1) Background: SARS-CoV-2 infection during pregnancy could determine important maternal and fetal complications. We aimed to prospectively assess placental immunohistochemical changes, immunophenotyping alterations, and pregnancy outcomes in a cohort of patients with COVID-19; (2) Methods: 52 pregnant patients admitted to a tertiary maternity center between October 2020 and November 2021 were segregated into two equal groups, depending on the presence of SARS-CoV-2 infection. Blood samples, fragments of umbilical cord, amniotic membranes, and placental along with clinical data were collected. Descriptive statistics and a conditional logistic regression model were used for data analysis; (3) Results: Adverse pregnancy outcomes such as preterm labor and neonatal intensive care unit admission did not significantly differ between groups. The immunophenotyping analysis indicated that patients with moderate–severe forms of COVID-19 had a significantly reduced population of T lymphocytes, CD4+ T cells, CD8+ T cells (only numeric), CD4+/CD8+ index, B lymphocytes, and natural killer (NK) cells. Our immunohistochemistry analysis of tissue samples failed to demonstrate positivity for CD19, CD3, CD4, CD8, and CD56 markers; (4) Conclusions: Immunophenotyping analysis could be useful for risk stratification of pregnant patients, while further studies are needed to determine the extent of immunological decidual response in patients with various forms of COVID-19.

(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.

(1) Background: HELLP (hemolysis, elevated liver enzymes, and low platelets) syndrome is a rare and life-threatening complication of preeclampsia. The aim of this study was to evaluate and compare the predictive performances of four machine learning-based models for the prediction of HELLP syndrome, and its subtypes according to the Mississippi classification; (2) Methods: This retrospective case-control study evaluated pregnancies that occurred in women who attended a tertiary maternity hospital in Romania between January 2007 and December 2021. The patients’ clinical and paraclinical characteristics were included in four machine learning-based models: decision tree (DT), naïve Bayes (NB), k-nearest neighbors (KNN), and random forest (RF), and their predictive performance were assessed; (3) Results: Our results showed that HELLP syndrome was best predicted by RF (accuracy: 89.4%) and NB (accuracy: 86.9%) models, while DT (accuracy: 91%) and KNN (accuracy: 87.1%) models had the highest performance when used to predict class 1 HELLP syndrome. The predictive performance of these models was modest for class 2 and 3 of HELLP syndrome, with accuracies ranging from 65.2% and 83.8%; (4) Conclusions: The machine learning-based models could be useful tools for predicting HELLP syndrome, and its most severe form—class 1.

(1) Background: Preeclampsia (PE) prediction in the first trimester of pregnancy is a challenge for the clinicians. The aim of this study was to evaluate and compare the predictive performances of machine-learning based models for the prediction of preeclampsia, and its subtypes; (2) Methods: This prospective case-control study evaluated pregnancies that occurred in women who attended a tertiary maternity hospital in Romania between November 2019 and September 2022. The patients’ clinical and paraclinical characteristics were evaluated in the first trimester, and were included in 4 machine learning based models: decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF), and their predictive performance was assessed; (3) Results: early-onset PE was best predicted by DT (accuracy: 94.1%), and SVM (accuracy: 91.2%) models, while NB (accuracy: 98.6%), and RF (accuracy: 92.8%) models had the highest performance when used to predict all types of PE. The predictive performance of these models was modest for moderate and severe types of PE, with accuracies ranging from 70.6% and 82.4%; (4) The machine learning-based models could be useful tools for PE prediction in the first trimester of pregnancy.

(1) Background: Isotretinoin (ISO) is a systemic retinoid known for its teratogenic effects on embryos and fetuses. The aim of this study was to compare the pregnancy outcomes of women who were exposed to isotretinoin with those of women without such exposure from a teratogenic point of view. (2) Methods: A total of 1459 female patients from three clinical hospitals in Poland and Romania, segregated into two groups depending on their ISO exposure, were evaluated between January and December 2019. Medical records were screened to identify the pregnancy outcomes and congenital malformation rates. (3) Results: The congenital malformation rate for the exposed group was 1.2% (four cases), and no specific signs of Accutane embryopathy were identified. Women from the unexposed group were more likely to deliver preterm and through cesarean deliveries and had a higher rate of newborn congenital malformations as compared to women from the exposed group. (4) Conclusions: Even though we could not find a significant association between ISO exposure and teratogenic effects in newborns, effective contraceptive measures are key to preventing unfavorable pregnancy outcomes.

(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.

(1) Background: Low patient’s adherence to conventional cervical cancer screening methods determined the need to take into consideration alternative approaches, and vaginal HPV self-sampling is one of them. We aimed to evaluate, using an online survey, the Romanian women’s acceptability of vaginal HPV self-sampling. (2) Methods: A 13-questions online survey was distributed on three Facebook groups, and the results were summarized. (3) Results: Despite of good educational background, 10.8% (n = 60) of the respondents did not know what a Pap smear is, and 33% (n = 183) were not informed about the free national cervical cancer screening program. Multivariate analysis revealed an increased likelihood of vaginal self-sampling acceptance among respondents who did not know about Pap test (OR: 7.80; 95%CI: 1.062–57.431; p = 0.021), national cervical cancer screening program (OR: 1.96; 95%CI: 1.010–3.806; p = 0.02), HPV infection (OR: 7.35; 95%CI: 3.099–17.449; p< 0.001) or HPV test (OR: 1.67; 95%CI: 0.950–2.948; p = 0.03). Moreover, women who did not previously undergo a cervical cancer screening program were more likely to accept the new screening method (OR: 1.62; 95%CI: 0.878–3.015; p = 0.04). (4) Conclusions: Our results showed high acceptability rates of vaginal HPV self-sampling among participants.

Placental protein-13 (PP-13) is a member of the galectin group involved in placental implantation, maternal artery remodeling, and placental inflammatory processes. Its levels are lower in the first trimester for pregnancies later affected by ischemic placental disease, and slowly increase during the second and third trimesters of pregnancy. The aim of the present meta-analysis is to assess the predictive performance of PP-13 in first trimester preeclampsia screening. PubMed, Web of Science, Scopus, Embase, BIOSIS, and Cochrane databases were used to find relevant studies. All prospective and retrospective observational studies that evaluated the accuracy of PP-13 in predicting preeclampsia were assessed. The investigation revealed that the quantitative synthesis was based on 14 studies with a total number of 8,239 women. The pooled sensitivity of PP-13 for the prediction of preeclampsia was 0.53 [95% (confidence interval (CI), 0.08-0.99], and the pooled specificity was 0.83 (95% CI, 0.38-1.29). Further analysis revealed a higher accuracy of PP-13 for the screening of late-onset preeclampsia [pooled sensitivity of 0.58 [95% CI, -0.17-1.33) with a specificity of 0.85 (95% CI, 0.10-1.60)] when compared with early-onset preeclampsia [pooled sensitivity of 0.51 (95% CI, -0.04-1.05) with a specificity of 0.88 (95% CI, 0.33-1.42)]. In conclusion, PP-13 appears to be a promising biomarker for evaluating the risk of developing preeclampsia during the first trimester of pregnancy. As a result, incorporating it into future predictive models is a viable option.

Background: Pregnancy in women with systemic lupus erythematosus (SLE) is accompanied by adverse pregnancy outcomes (APOs). We aimed to investigate the association between clinical, sonographic, and laboratory parameters and APOs (preeclampsia, intrauterine growth restriction, premature birth, and maternal mortality). Methods: This observational retrospective study included all pregnancies in women with SLE who attended two tertiary maternity hospitals from Romania between January 2013 and December 2020. Clinical, sonographic, and laboratory variables were examined. Bivariate associations of APO status and each predictor variable were evaluated, and significant predictors were further included in a classification model based on discriminant analysis. Results: Predictors of APOs included BMI > 25 kg/m2, personal history of lupus nephritis or chronic hypertension, proteinuria, low C3, SLE Disease Activity Index 2000 (SLEDAI-2k score ≥ 4 and physician’s global-assessment (PGA) score ≥ 1 throughout pregnancy, increased mean uterine arteries pulsatility index in the first and second trimesters, cerebroplacental ratio < 1 in the second and third trimesters, and small fetal abdominal circumference in the third trimester. Glucocorticoids, methyldopa, and aspirin use appeared to be protective against APOs. Conclusions: This study provides a comprehensive analysis of the most important predictors for APOs in pregnant patients with SLE, which could constitute a basis for further research.

Background and Objectives: Minimally invasive procedures, such as double-J ureteric stenting, could be a promising therapeutic alternative to conservative management of obstructive urinary tract pathology. We aimed to evaluate the safety and effectiveness of double-J ureteric stenting in pregnant women with ureterohydronephrosis or urolithiasis, along with their infectious complications, and to assess the pregnancy outcomes of this cohort of patients in comparison with a control group. Materials and Methods: This observational retrospective study included 52 pregnant patients who underwent double-J ureteric stenting for urologic disorders in the Urology Department of ‘C.I. Parhon’ University Hospital, and who were followed up at a tertiary maternity hospital- ‘Cuza-Voda’, Iasi, Romania. The control group (63 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, sonographic, and laboratory variables were examined. Descriptive statistics, non-parametric tests, and a one-to-one propensity score-matched analysis were used to analyze our data. Results: The univariate analysis indicated a significant statistical difference between the control group and the interventional group regarding maternal age (p = 0.018), previous maternal history of renal colic (p = 0.005) or nephrolithiasis (p = 0.002). After applying the propensity score-matched analysis, cesarean delivery rates (p < 0.001), preterm labour (p = 0.039), premature rupture of membranes (p = 0.026), preterm birth rates (p = 0.002), and post-partum UTI rates (p = 0.012) were significantly different between the control group and the matched treatment group. Ureterohydronephrosis, whether simple (n = 37; 71.2%) or infected (n = 13; 25%), was the main indication for double-J ureteric stenting. Complications such as pain (n = 21; 40.3%), stent migration (n = 3; 5.76%) or encrustation (n = 2; 3.84%), as well as reflux pyelonephritis (n = 2; 3.84%) and gross hematuria (n = 1; 1.92%) were recorded during follow-up. Conclusions: Our results show that double-J stenting is a safe and effective treatment option for pregnant patients with obstructive urological disorders.

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.

Background and Objectives: Fetal ovarian cysts (FOCs) are a very rare pathology that can be associated with maternal–fetal and neonatal complications. The aim of this study was to assess the influence of ultrasound characteristics on FOC evolution and therapeutic management. Materials and Methods: We included cases admitted to our perinatal tertiary center between August 2016 and December 2022 with a prenatal or postnatal ultrasound evaluation indicative of FOC. We retrospectively analyzed the pre- and postnatal medical records, sonographic findings, operation protocols, and pathology reports. Results: This study investigated 20 cases of FOCs, of which 17 (85%) were diagnosed prenatally and 3 (15%) postnatally. The mean size of prenatally diagnosed ovarian cysts was 34.64 ± 12.53 mm for simple ovarian cysts and 55.16 ± 21.01 mm for complex ovarian cysts (p = 0.01). The simple FOCs ≤ 4 cm underwent resorption (n = 7, 70%) or size reduction (n = 3, 30%) without complications. Only 1 simple FOC greater than 4 cm reduced its size during follow-up, while 2 cases (66.6%) were complicated with ovarian torsion. Complex ovarian cysts diagnosed prenatally underwent resorption in only 1 case (25%), reduced in size in 1 case (25%), and were complicated with ovarian torsion in 2 cases (50%). Moreover, 2 simple (66.6%) and 1 complex (33.3%) fetal ovarian cysts were postnatally diagnosed. All of these simple ovarian cysts had a maximum diameter of ≤4 cm, and all of them underwent size reduction. The complex ovarian cyst of 4 cm underwent resorption during follow-up. Conclusions: Symptomatic neonatal ovarian cysts, as well as those that grow in size during sonographic follow-up, are in danger of ovarian torsion and should be operated on. Complex cysts and large cysts (with >4 cm diameter) could be followed up unless they become symptomatic or increase in dimensions during serial ultrasounds.

(1) Background: Perilla frutescens (L.) Britt. is an important pharmaceutical crop that remains a focus point for researchers worldwide due to its complex phytochemical constituents, medicinal effects, and nutraceutical properties. The literature data are based on animal and cell culture studies, so the clinical evidence for the therapeutic effects is poorly outlined. The aim of this review was to provide an updated and thorough understanding of Perilla frutescens applications in clinical practice using data derived from human studies, and to outline the potential directions and perspectives for further studies on this crop. (2) Methods: Medline, Embase, and Cochrane databases were used to find relevant studies. All interventional studies that evaluated the effect of Perilla frutescens in human subjects were assessed. (3) Results: The main perspectives that can be contoured from the presented literature evaluation are an important clinical effect of Perilla frutescens extracts on allergic rhinoconjuctivitis, especially in young populations, a potent hypolipemiant effect that, in conjunction with increased serum biological antioxidant potential, determines significant improvements in cognitive function and a wide variety of miscellaneous clinical effects that need further exploration. (4) Conclusions: Supplementary research is needed in order to demonstrate the therapeutic effects of Perilla frutescens in controlled clinical settings.

(1) Background: Retinopathy of prematurity (ROP) can cause severe visual impairment or even blindness. We aimed to assess the hematological risk factors that are associated with different stages of ROP in a cohort of preterm newborns, and to compare the clinical characteristics and therapeutic interventions between groups. (2) Methods: This retrospective study included 149 preterm newborns from a tertiary maternity hospital in Romania between January 2018 and December 2018, who were segregated into: Group 1 (with ROP, n = 59 patients), and Group 2 (without ROP, n = 90 patients). The patients that were affected by ROP were subsequently divided into the following subgroups: Subgroup 1 (Stage 1, n = 21), Subgroup 2 (Stage 2, n = 35), and Subgroup 3 (Stage 3, n = 25). The associations were analyzed using multivariate logistic regression and sensitivity analysis. (3) Results: Platelet mass indexes (PMI) that were determined in the first, seventh, and tenth days of life were significantly associated with Stage 1 ROP. PMI determined in the first day of life was also significantly associated with Stage 2 ROP. The sensitivity and specificity of these parameters were modest, ranging from 44 to 57%, and 59 to 63%. (4) Conclusions: PMI has a modest ability to predict the development of ROP.

(1) Background: Preeclampsia (PE) prediction in the first trimester of pregnancy is a challenge for clinicians. The aim of this study was to evaluate and compare the predictive performances of machine learning-based models for the prediction of preeclampsia and its subtypes. (2) Methods: This prospective case-control study evaluated pregnancies that occurred in women who attended a tertiary maternity hospital in Romania between November 2019 and September 2022. The patients’ clinical and paraclinical characteristics were evaluated in the first trimester and were included in four machine learning-based models: decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF), and their predictive performance was assessed. (3) Results: Early-onset PE was best predicted by DT (accuracy: 94.1%) and SVM (accuracy: 91.2%) models, while NB (accuracy: 98.6%) and RF (accuracy: 92.8%) models had the highest performance when used to predict all types of PE. The predictive performance of these models was modest for moderate and severe types of PE, with accuracies ranging from 70.6% and 82.4%. (4) Conclusions: The machine learning-based models could be useful tools for EO-PE prediction and could differentiate patients who will develop PE as early as the first trimester of pregnancy.

(1) Background: Neonatal cerebral sinovenous thrombosis (CSVT) is a rare disorder, associated with long-term neurological sequelae. The aim of this study was to retrospectively evaluate the most commonly encountered perinatal risk factors for this disease in a cohort of newborns from Romania. (2) Methods: The medical records of neonatal CSVT patients treated between January 2017 and December 2021 were descriptively assessed. (3) Results: The study included nine neonates, five males (55.56%) and four females (44.44%), who were born at term. The most commonly presented clinical manifestations were feeding difficulties, lethargy, respiratory distress, loss of consciousness, and seizures. Maternal-inherited thrombophilia, male sex, complicated delivery, perinatal asphyxia, and mechanical ventilation were frequently identified as potential risk factors for developing CSVT. The lesions were more frequently localized in the superior sagittal sinus (n = 7; 77.78%), followed by the transverse (n = 4; 44.44%), sigmoid (n = 2; 22.22%), and cavernous (n = 1; 11.11%) sinuses. Low-molecular-weight heparin was administered to all patients, and two of them died from thrombotic complications. (4) Conclusions: Recognition of potential risk factors and a prompt diagnosis of neonatal CSVT could lead to better patient management and to a reduction of severe complications.

(1) Background: From the recent variants of concern of the SARS-CoV-2 virus, in which the delta variant generated more negative outcomes than the alpha, we hypothesized that lung involvement, clinical condition deterioration and blood alterations were also more severe in autumn infection, when the delta variant dominated (compared with spring infections, when the alpha variant dominated), in severely infected pregnant patients. (2) Methods: In a prospective study, all pregnant patients admitted to the ICU of the Elena Doamna Obstetrics and Gynecology Hospital with a critical form of COVID-19 infection—spring group (n = 11) and autumn group (n = 7)—between 1 January 2021 and 1 December 2021 were included. Brixia scores were calculated for every patient: A score, upon admittance; H score, the highest score throughout hospitalization; and E score, at the end of hospitalization. For each day of Brixia A, H or E score, the qSOFA (quick sepsis-related organ failure assessment) score was calculated, and the blood values were also considered. (3) Results: Brixia E score, C-reactive protein, GGT and LDH were much higher, while neutrophil count was much lower in autumn compared with spring critical-form pregnant patients. (4) Conclusions: the autumn infection generated more dramatic alterations than the spring infection in pregnant patients with critical forms of COVID-19. Larger studies with more numerous participants are required to confirm these results.