Soto-Sánchez et al. PLACENTA 2022

This was a single-centre retrospective case–control study of pregnant women who had an obstetrical ultrasound as either an outpatient or inpatient while under the care of the Department of Obstetrics and Gynecology of Hospital Universitario Infanta Leonor (HUIL) between April 1st and December 31st, 2020, during the coronavirus disease 2019 (COVID-19) pandemic. Outpatients seen at the ultrasound units were screened for SARS-CoV-2 symptoms. Fifty-seven (57) pregnant women who tested positive for SARS-CoV-2 at the time or within one month prior to the ultrasound scan (US) were evaluated. There were 8 first trimester US, 16 second trimester US and 32 third trimester US. US scans were performed either for routine fetal evaluation or indicated due to a positive SARS-CoV-2 test. SARS-CoV-2 infection was confirmed by real-time reverse transcriptase-PCR (RT–PCR) assay (FTD SARS-CoV-2 Assay by SIEMENS) from nasopharyngeal swabs (DeltaSwab by Deltalab). Foetal biometry, placental thickness (PT), and the presence of placental lakes (PL) were evaluated. Fetal biometry (biparietal diameter [BPD], head circumference [HC], abdominal circumference [AC], femur length [FL]) was measured, and the estimated fetal weight was calculated (EFW). The umbilical venous flow can be obtained directly by measuring the section and the mean velocity of the vein in a loop-free cord. Descriptive statistics for baseline clinical characteristics were applied to both groups. Continuous data were evaluated with one-way analysis of variance (ANOVA) or Student’s t test. Percentages and fractions were compared using Fisher’s exact or chi-squared tests. Associations were analysed using logistic regression models; in addition to the matching process, regression analyses were further adjusted for maternal age, weight, and parity. A p value <0.05 was considered significant.
Data were collected and managed using REDCap (Research Electronic Data Capture) electronic data capture tools hosted at the Ideas for Health Association. REDCap is a secure, web-based software platform designed to support data capture for research studies