Background: To investigate the association between late preterm antenatal corticosteroid treatment and outcome in late preterm neonates born to mothers with gestational diabetes mellitus, Methods: All patients with gestational diabetes mellitus who had a late preterm delivery at Etlik Lady Zübeyde Hospital between 2017 and 2021 were included. Women who met the inclusion criteria and were not given antenatal corticosteroid treatment during current pregnancy before 34 0/7 weeks of gestation were divided into two groups according to whether or not they received late preterm antenatal corticosteroid treatment. The two groups were compared in terms of adverse neonatal complications. The main outcomes were composite respiratory outcome and composite neonatal outcome. Logistic regression analysis was used to determine additional potential predictors of neonatal outcome. Results: This retrospective cohort study included a total of 400 participants with gestational diabetes mellitus who had a late preterm delivery within the study period. Of these women, 196 (49%) received late preterm antenatal corticosteroid treatment. Main outcomes showed no difference. Decreasing gestational age at birth was identified as an independent risk factor predicting both composite respiratory outcome and composite neonatal outcome in multivariate logistic regression analysis. Conclusions: Antenatal corticosteroid treatment at or after 34 0/7 weeks of gestation in women with gestational diabetes mellitus who had a late preterm delivery was not associated with improvement in adverse neonatal outcomes. Decreasing gestational age at birth was the only independent risk factor predicting composite neonatal and composite respiratory outcomes.

Twins are associated with an increased risk of premature birth, a major cause of neonatal morbidity and mortality. Antenatal corticosteroid treatment (ACT) is the main intervention to improve neonatal outcomes in unavoidable preterm births. Our aim was to investigate the association between neonatal outcome and ACT in twin pregnancies with late preterm birth, where the effects of corticosteroids have not been adequately studied. Women with dichorionic-diamniotic twins who had a late preterm birth between 2017 and 2021 at a large referral hospital providing tertiary care and medical training were retrospectively analyzed. Women who met the inclusion criteria were divided into three groups: No ACT (n = 209), ACT < 34 weeks’ gestation (n = 76) and ACT ≥ 34 weeks’ gestation (n = 67). The groups were compared with regard to adverse neonatal complications. Primary outcome measures were composite respiratory and composite neonatal outcomes. Logistic regression analysis was used to determine additional potential predictors of neonatal outcome. Composite respiratory and composite neonatal outcomes did not differ significantly between groups. Birth gestational age, birthweight and ACT before 34 weeks’ gestation were independently associated with favorable composite respiratory outcome, composite neonatal outcome and a lower neonatal intensive care unit admission rate. Female sex was independently associated with favorable composite respiratory outcome and a lower neonatal intensive care unit admission rate, while birth gestational age and birthweight were independently associated with a lower rate of hypoglycemia. ACT at or after 34 weeks’ gestation was not associated with better neonatal outcomes in dichorionic-diamniotic twins born late preterm and was associated with a higher rate of neonatal hypoglycemia than those not treated with corticosteroids.

Objective: Shoulder dystocia (ShD) is a rare but serious obstetric emergency associated with significant neonatal morbidity. This study aimed to evaluate the predictive performance of machine learning (ML) models based on fetal biometric ratios and clinical characteristics for the identification of ShD in pregnancies without clinical suspicion of macrosomia. Methods: We conducted a retrospective case-control study including 284 women (84 ShD cases and 200 controls) who underwent spontaneous vaginal delivery between 37 and 42 weeks of gestation. All participants had an estimated fetal weight (EFW) below the 90th percentile according to Hadlock reference curves. Univariate and multivariate logistic regression analyses were performed on maternal and neonatal parameters, and statistically significant variables (p < 0.05) were used to construct adjusted odds ratio (aOR) models. Supervised ML models—Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGB)—were trained and tested to assess predictive accuracy. Performance metrics included AUC-ROC, sensitivity, specificity, accuracy, and F1-score. Results: The BPD/AC ratio and AC/FL ratio markedly enhanced the prediction of ShD. When added to other features in RF models, the BPD/AC ratio got an AUC of 0.884 (95% CI: 0.802–0.957), a sensitivity of 68%, and a specificity of 83%. On the other hand, the AC/FL ratio, along with other factors, led to an AUC of 0.896 (95% CI: 0.805–0.972), 68% sensitivity, and 90% specificity. Conclusions: In pregnancies without clinical suspicion of macrosomia, ML models integrating fetal biometric ratios with maternal and labor-related factors significantly improved the prediction of ShD. These models may support clinical decision-making in low-risk deliveries where ShD is often unexpected.

Infectious complications at the surgical site complicates 1–4% of cesarean deliveries. Strict aseptic technique, hand hygiene and the use of sterile surgical gloves are essential to reduce the risk of surgical site contamination. Glove perforations are observed in almost 30% of all procedures and represent an underestimated potential risk factor for postoperative infections. The aim of this prospective study was to investigate glove perforation rates in cesarean deliveries and to analyze the impact of unrecognized glove perforations during surgery on surgical site infection rates after cesarean delivery. Surgical gloves from cesarean section were collected prospectively. All gloves were inspected for perforation holes. Cases in which surgical gloves had visible (macro) perforations were excluded from the study. Remaining gloves were examined using a water-fill test. Gloves with a positive water filling test were defined as the study group and negative gloves as the control group. Superficial Surgical Site Infections (SSI) were analyzed for the groups. A total of 1,779 pairs of used surgical gloves were collected and examined for perforations across 593 cesarean operations. Macro perforation were observed in 56 (9.4%) operations. The remaining 1,611 pairs of gloves underwent water-fill testing. Of these, 505 operations had completely intact gloves, while in 32 (5.4%) cases, micro-perforations were identified. SSI occurred in 18 women (3.3%): 7 in the perforation group (21.8%) and 11 in the control group (2.2%) (p < 0.001). In multivariable logistic regression analysis, glove micro-perforation was found to be a significant independent predictor of SSI (adjusted odds ratio: 12.705; 95% CI: 4.244–38.039; p < 0.001), even after adjusting for potential confounders including diabetes, obesity, emergency cesarean, operative duration, and intraoperative blood loss. Our data show that glove perforation is unexpectedly common and underestimated in terms of unfavorable surgical outcomes. The rate of surgical site infections is increasing and we suggest that unrecognized glove perforation must be considered as a risk factor for surgical site infection after cesarean section.