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(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.

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.

(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: 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.