Objective: Global utilization of assisted reproductive technology (ART) is increasing; however, it is associated with adverse perinatal outcomes. Placental and umbilical cord abnormalities contribute significantly to these negative outcomes. However, it remains unclear whether ART independently increases the risk of such abnormalities. This study aimed to investigate the association between ART and key umbilico-placental abnormalities, after adjustment for confounders. Methods: In this retrospective cohort study, singleton pregnancies receiving routine antenatal care (January 2015 to June 2024) at the 3rd Department of Obstetrics and Gynecology, Aristotle University of Thessaloniki, Greece, were analyzed. Pregnancies conceived via ART were compared to those conceived spontaneously. To investigate placental and cord anomalies, this study employed multiple logistic regression. This approach adjusted for various confounders, including maternal age, BMI, parity, smoking status, history of previous cesarean section, diabetes mellitus, and thyroid disease. Results: This study included a total of 13,854 singleton pregnancies, of which 647 were conceived via ART. ART was significantly associated with an increased risk of placenta previa (aOR 1.99, 95% CI 1.10–3.61), low-lying placenta (aOR 1.71, 95% CI 1.38–2.11), bilobate placenta (aOR 2.81, 95% CI 1.92–4.11), single umbilical artery (aOR 2.62, 95% CI 1.022–6.715), marginal (aOR 1.63, 95% CI 1.32–2.01) and velamentous cord insertion (aOR 3.13, 95% CI 1.98–4.95), and vasa previa (aOR 5.51, 95% CI 1.28–23.76). Conclusions: ART-conceived pregnancies appear to carry a higher risk for certain placental and umbilical cord abnormalities, potentially contributing to adverse perinatal outcomes. Further studies are required to investigate the pathophysiology underlying these associations.

Background/Objectives: Preterm birth (PTB), defined as birth before 37 completed weeks of gestation, is a major global health challenge and a leading cause of neonatal mortality. PTB is broadly classified into spontaneous and medically indicated (iatrogenic), which have distinct etiologies. While prediction is key to improving outcomes, there is a lack of models that specifically differentiate between spontaneous and iatrogenic PTB subtypes. This study aimed to develop and validate predictive models for the prediction of spontaneous and iatrogenic PTB at <32, <34, and <37 weeks’ gestation using medical history and readily available second-trimester data. Methods: This was a retrospective cohort study on singleton pregnancies from a single tertiary institution (2012–2025). Predictor variables included maternal characteristics, obstetric history, and second-trimester ultrasound markers. Four algorithms, including multivariable Logistic Regression and three machine learning methods (Random Forest, XGBoost, and a Neural Network), were trained and evaluated on a held-out test set (20% of the data). Model performance was primarily assessed by the Area Under the Curve (AUC). Results: In total, 9805 singleton pregnancies were included. The models performed significantly better for iatrogenic PTB than for spontaneous PTB. For delivery <37 weeks, the highest AUC for iatrogenic PTB was 0.764 (Random Forest), while for spontaneous PTB it was 0.609 (Neural Network). Predictive accuracy improved for earlier gestations; for delivery <32 weeks, the best model for iatrogenic PTB achieved an AUC of 0.862 (Neural Network), and the best model for spontaneous PTB achieved an AUC of 0.749 (Random Forest). Model interpretation revealed that iatrogenic PTB was primarily driven by markers of placental dysfunction, such as estimated fetal weight by ultrasound scan and uterine artery pulsatility index, while spontaneous PTB was most associated with a history of PTB and a short cervical length. Conclusions: Models using routine mid-gestation data demonstrate effective prediction for iatrogenic PTB, with accuracy improving for earlier, more severe cases. In contrast, performance for spontaneous PTB was modest. Traditional Logistic Regression performed comparably to complex machine learning algorithms, highlighting that the clinical value is rooted in the subtype-specific modeling approach rather than in algorithmic complexity.

Background and Objectives: This meta-analysis aimed to determine whether pre-implantation uterine artery (UtA) Doppler measurements are associated with clinical pregnancy in women undergoing assisted reproductive technologies (ART). Materials and Methods: A systematic search of MEDLINE, Scopus, and the Cochrane Library from inception until 25 March 2025 was conducted to identify relevant studies. Additional records were retrieved through grey literature searching and manual reference checks. Eligible publications were observational studies or clinical trials that evaluated UtA Doppler indices prior to embryo transfer in adult women undergoing ART. Studies were required to report on clinical pregnancy rates, while those enrolling participants under 18 years of age, lacking Doppler data, or providing no pregnancy endpoints were excluded. Three reviewers independently assessed study quality using the Newcastle–Ottawa Scale and the Quality in Prognosis Studies tool. Meta-analyses were performed using a random-effects model to calculate mean differences (MDs) with 95% confidence intervals (CIs). Heterogeneity was examined via Cochran’s Q and the I² statistic. Sensitivity analyses excluded studies at high risk of bias. Results: In total, 12 studies met the inclusion criteria, including a population of 3317 women. Women who achieved clinical pregnancy had a lower mean UtA pulsatility index (PI) (MD, −0.26; 95% CI, −0.46 to −0.06) and a higher peak systolic velocity (PSV) (MD, 8.59; 95% CI, 2.31 to 14.87) than those who did not conceive. Subgroup analyses showed that UtA PI measured during the menstrual cycle was lower in clinical pregnancy cases (MD, −0.38; 95% CI, −0.66 to −0.10). Measurements on the day of hCG administration or the day before showed a non-significant difference in UtA PI (MD, −0.43; 95% CI, −1.03 to 0.17), while assessments on the day of embryo transfer showed no significant difference between groups (MD, −0.02; 95% CI, −0.28 to 0.24). Conclusions: This meta-analysis suggests that lower UtA PI and higher PSV prior to embryo transfer are associated with higher clinical pregnancy rates in ART, particularly when measurements are taken during the menstrual cycle. Although these findings highlight a potential role for uterine hemodynamics in successful clinical pregnancy, UtA Doppler alone may not be a reliable predictor. Future studies should focus on earlier-cycle Doppler measurements and their integration into multifactorial models to improve prognostic accuracy.

Cardiac arrhythmias are prevalent complications in pregnancy, yet their precise association with acute maternal cardiovascular morbidity and mortality remains unclear due to heterogeneous evidence. This systematic review and meta-analysis evaluated the impact of maternal arrhythmias on acute cardiovascular outcomes. We searched Medline, Scopus, and Cochrane databases for observational studies comparing pregnant women with arrhythmias to those without. Random-effects meta-analyses were used to calculate pooled risk ratios (RR) for maternal mortality and major adverse cardiovascular events (MACE). Eleven studies comprising 76,028 pregnancies with arrhythmias and over 82 million controls were included. Analysis of data, primarily derived from large administrative cohorts with low absolute event rates, indicated that arrhythmias were significantly associated with increased all-cause maternal mortality (0.78% vs. 0.01%; RR 31.94; adjusted RR 8.91) and a composite of MACE (2.90% vs. 0.03%; RR 6.48). Supraventricular tachycardia and atrial fibrillation were associated with an increased likelihood of adverse outcomes. Notably, the relative risk of mortality and heart failure in women with arrhythmias versus controls was significantly higher in the general obstetric population around delivery than in women with known structural heart disease, suggesting a “sentinel event” phenomenon. Thromboembolic events were also 15 times more likely in the arrhythmia group. Cardiac arrhythmias during pregnancy are associated with substantial maternal morbidity and mortality. New-onset arrhythmias may warrant comprehensive cardiac evaluation, as they may unmask underlying pathology and precipitate severe hemodynamic compromise, particularly in women without prior cardiac history.

Background/Objectives : To construct and compare multivariable prediction models for the early prediction of large-for-gestational-age (LGA) neonates, using ultrasound biometry and maternal characteristics. Methods: This retrospective cohort study analyzed data from singleton pregnancies that underwent routine ultrasound examinations at 30⁺⁰–34⁺⁰ weeks of gestation. Ultrasound parameters included fetal abdominal circumference (AC), head circumference (HC), femur length (FL), HC-to-AC ratio, mean uterine artery pulsatility index (mUtA-PI), and presence of polyhydramnios. LGA neonates were defined as those having a birthweight > 90th percentile. Logistic regression was used to evaluate associations between ultrasound markers and LGA after adjusting for the following maternal and pregnancy-related covariates: maternal age, body mass index, parity, gestational diabetes mellitus (GDM), pre-existing diabetes, previous cesarean section (PCS), assisted reproductive technology (ART) use, smoking, hypothyroidism, and chronic hypertension. Associations were expressed as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Three prognostic models were developed utilizing the following predictors: (i) biometric ultrasound measurements including AC, HC-to-AC ratio, FL, UtA-PI, and polyhydramnios (Model 1), (ii) a combination of biometric ultrasound measurements and clinical–maternal data (Model 2), and (iii) only the estimated fetal weight (EFW) (Model 3). Results: In total, 3808 singleton pregnancies were included in the analyses. The multivariable analysis revealed that AC (aOR 1.07, 95% CI [1.06, 1.08]), HC to AC (aOR 1.01, 95% CI [1.006, 1.01]), FL (aOR 1.01, 95% CI [1.009, 1.01]), and the presence of polyhydramnios (aOR 4.97, 95% CI [0.7, 58.8]) were associated with an increased risk of LGA, while a higher mUtA-PI was associated with a reduced risk (aOR 0.98, 95% CI [0.98, 0.99]). Maternal parameters, such as GDM, pre-existing diabetes, elevated pre-pregnancy BMI, absence of uterine artery notching, mUtA-PI, and multiparity, were significantly higher in the LGA group. Both models 1 and 2 showed similar performance (AUCs: 84.7% and 85.3%, respectively) and outperformed model 3 (AUC: 77.5%). Bootstrap and temporal validation indicated minimal overfitting and stable model performance, while decision curve analysis supported potential clinical utility. Conclusions: Models using biometric and Doppler ultrasound at 30–34 weeks demonstrated good discriminative ability for predicting LGA neonates, with an AUC up to 84.7%. Adding maternal characteristics did not significantly improve performance, while the biometric model performed better than EFW alone. Sensitivity at conventional thresholds was low but increased substantially when lower probability cut-offs were applied, illustrating the model’s threshold-dependent flexibility for early risk stratification in different clinical screening needs. Although decision curve analysis was performed to explore potential clinical utility, external validation and prospective assessment in clinical settings are still needed to confirm generalizability and to determine optimal decision thresholds for clinical application.

Introduction: The prevalence of maternal arrhythmias is increasing with advanced maternal age. Current evidence regarding the association between maternal arrhythmias and pregnancy outcomes remains inconsistent. This meta-analysis aimed to define the associations between adverse pregnancy outcomes and specific maternal arrhythmias. Methods: We conducted a systematic review and meta-analysis using the PRISMA guidelines. We searched MEDLINE, Scopus, and Cochrane on the 4th of November 2025 for cohort and case–control studies comparing pregnant women with cardiac arrhythmias to those without. Primary outcomes included preeclampsia, stillbirth, preterm delivery, and small-for-gestational-age (SGA) neonates. Data were pooled using random-effects models with subgroup analyses by arrhythmia type. Results: Nineteen studies were included. Maternal arrhythmias were associated with a significantly increased risk of preeclampsia (RR = 1.46, 95% CI [1.10, 1.93]), preterm delivery (RR = 1.39, 95% CI [1.12, 1.72]), and stillbirth (RR = 2.09, 95% CI [1.11, 3.91]). Ventricular tachycardia/fibrillation was linked to the most severe outcomes, including a four-fold increase in stillbirth (RR = 4.20, 95% CI [3.75, 4.71]) and a fifteen-fold increase in neonatal death (RR = 15.47, 95% CI [3.45, 69.45]). Supraventricular tachycardia was independently associated with preeclampsia (aRR = 1.14, 95% CI [1.04, 1.24]), preterm delivery (aRR = 1.76, 95% CI [1.39, 2.23]), and SGA neonates (aRR = 5.93, 95% CI [1.23, 28.55]). Risks were notably higher in the general population compared to women with known heart disease, supporting an “unmasking” of occult vulnerability. Conclusions: Maternal arrhythmias are associated with distinct fetal risks beyond maternal hemodynamics. Ventricular tachycardia was associated with severe outcomes, likely reflecting acute compromise, while supraventricular tachycardia was linked to signs of chronic vascular dysfunction. These findings suggest arrhythmias as possible sentinels for placental insufficiency, necessitating enhanced surveillance.