Background Previous outbreaks of severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and Middle East respiratory syndrome coronavirus (MERS-CoV) have been associated with unfavourable pregnancy outcomes. SARS-CoV-2 belongs to the human coronavirus family, and since this infection shows a pandemic trend it will involve many pregnant women. Aims This systematic review and meta-analysis aimed to assess the impact of coronavirus disease 19 (COVID-19) on maternal and neonatal outcomes. Sources PubMed, EMBASE, MedRxiv, Scholar, Scopus, and Web of Science databases were searched up to 8th May 2020. Articles focusing on pregnancy and perinatal outcomes of COVID-19 were eligible. Participants were pregnant women with COVID-19. Content The meta-analysis was conducted following the PRISMA and MOOSE reporting guidelines. Bias risk was assessed using the Joanna Briggs Institute (JBI) manual. The protocol was registered with PROSPERO (CRD42042020184752). Twenty-four articles, including 1100 pregnancies, were selected. The pooled prevalence of pneumonia was 89% (95%CI 70–100), while the prevalence of women admitted to the intensive care unit was 8% (95%CI 1–20). Three stillbirths and five maternal deaths were reported. A pooled prevalence of 85% (95%CI 72–94) was observed for caesarean deliveries. There were three neonatal deaths. The prevalence of COVID-19-related admission to the neonatal intensive care unit was 2% (95%CI 0–6). Nineteen out of 444 neonates had a positive nasopharyngeal swab; one out of five neonates had elevated concentrations of serum IgM and IgG, but a negative swab. Implications Although adverse outcomes such as ICU admission or patient death can occur, the clinical course of COVID-19 in most women is not severe, and the infection does not significantly influence the pregnancy. A high caesarean delivery rate is reported, but there is no clinical evidence supporting this mode of delivery. Indeed, in most cases the disease does not threaten the mother, and vertical transmission has not been clearly demonstrated. Therefore, COVID-19 should not be considered as an indication for elective caesarean section.
BackgroundIt is crucial to identify in large population samples the most important determinants of excessive fetal growth. The aim of the study was to evaluate the independent role of pre-pregnancy body mass index (BMI), gestational weight gain and gestational diabetes on the risk of macrosomia.MethodsA prospective study collected data on mode of delivery and maternal/neonatal outcomes in eleven Hospitals in Italy. Multiple pregnancies and preterm deliveries were excluded. The sample included 14109 women with complete records. Associations between exposure variables and newborn macrosomia were analyzed using Pearson’s chi squared test. Multiple logistic regression models were built to assess the independent association between potential predictors and macrosomia.ResultsMaternal obesity (adjusted OR 1.7, 95% CI 1.4-2.2), excessive gestational weight gain (adjusted OR 1.9, 95% CI 1.6-2.2) and diabetes (adjusted OR 2.1, 95% CI 1.5-3.0 for gestational; adjusted OR 3.0, 95% CI 1.2-7.6 for pre-gestational) resulted to be independent predictors of macrosomia, when adjusted for other recognized risk factors. Since no significant interaction was found between pre-gestational BMI and gestational weight gain, excessive weight gain should be considered an independent risk factor for macrosomia. In the sub-group of women affected by gestational or pre-gestational diabetes, pre-gestational BMI was not significantly associated to macrosomia, while excessive pregnancy weight gain, maternal height and gestational age at delivery were significantly associated. In this sub-population, pregnancy weight gain less than recommended was not significantly associated to a reduction in macrosomia.ConclusionsOur findings indicate that maternal obesity, gestational weight gain excess and diabetes should be considered as independent risk factors for newborn macrosomia. To adequately evaluate the clinical evolution of pregnancy all three variables need to be carefully assessed and monitored.
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