A deep learning approach to identify the fetal head position using transperineal ultrasound during labor.

Objectives: To develop a deep learning (DL)-model using convolutional neural networks (CNN) to automatically identify the fetal head position at transperineal ultrasound in the second stage of labor.

Material And Methods: Prospective, multicenter study including singleton, term, cephalic pregnancies in the second stage of labor. We assessed the fetal head position using transabdominal ultrasound and subsequently, obtained an image of the fetal head on the axial plane using transperineal ultrasound and labeled it according to the transabdominal ultrasound findings.

Glycation-Driven Inflammation: COVID-19 Severity in Pregnant Women and Perinatal Outcomes.

The link between being pregnant and overweight or obese and the infectivity and virulence of the SARS CoV-2 virus is likely to be caused by SARS-CoV-2 spike protein glycosylation, which may work as a glycan shield. Methylglyoxal (MGO), an important advanced glycation end-product (AGE), and glycated albumin (GA) are the results of poor subclinical glucose metabolism and are indices of oxidative stress. Forty-one consecutive cases of SARS-CoV-2-positive pregnant patients comprising 25% pre-pregnancy overweight women and 25% obese women were recruited.