This JAMA Insights Clinical Update discusses general adaptations for pregnancy after bariatric surgery, including recommendations regarding nutrition, maternal health, and fetal and neonatal risks.
Prior studies have reported decreases in the preterm delivery incidence during the COVID-19 pandemic. However, the findings are inconsistent. Given the wide disparities in the pandemic's impact across communities, neighborhood deprivation may explain the observed variation in the relationship between the COVID-19 pandemic and preterm delivery.To characterize the changes in the incidence of preterm delivery during the COVID-19 pandemic with attention to the effect modification introduced by neighborhood hardship.This retrospective cohort study included all the pregnant patients who delivered at an urban tertiary care hospital during the pandemic (April-November 2020) or before the pandemic (April-November 2019). We compared the incidence of preterm delivery, spontaneous preterm delivery, and medically indicated preterm delivery before 37 weeks' gestation across epochs. Planned analyses stratified the cohorts by neighborhood deprivation metrics defined by the residential zip code; the metrics included the median neighborhood household income and the hardship index (a composite index including dependency, educational attainment, unemployment, poverty, per capita income, and crowded housing). The Breslow-Day test for homogeneity assessed the association of the delivery epoch and neighborhood deprivation with the preterm delivery outcomes.Of 16,544 eligible deliveries, 8.7% occurred preterm. The incidences of preterm delivery (8.4% vs 9.0%; P=.17), spontaneous preterm delivery (5.0 vs 5.4%; P=.27), and medically indicated preterm delivery (3.2% vs 3.5%; P=.47) were similar in the pandemic and prepandemic epochs. However, the preterm delivery (odds ratio, 0.78; 95% confidence interval, 0.64-0.96) and spontaneous preterm delivery (odds ratio, 0.76; 95% confidence interval, 0.59-0.99) decreased from the prepandemic to the pandemic epoch in those living in neighborhoods <50th percentile for median income (Breslow-Day P values.047 and.036, respectively). Similarly, the preterm delivery (odds ratio, 0.78; 95% confidence interval, 0.64-0.97) and spontaneous preterm delivery (odds ratio, 0.74; 95% confidence interval, 0.57-0.98) decreased for those inhabiting the neighborhoods in the highest-hardship quartile (Breslow-Day P values.045 and.029, respectively).The populations residing in socioeconomically disadvantaged neighborhoods experienced reductions in preterm delivery during the COVID-19 pandemic. Neighborhood-level social determinants of health offer insight into the complex etiologies that contribute to preterm delivery and provide opportunities for public health and equity-focused prevention strategies.
Importance Being born either small for gestational age (SGA) or large for gestational age (LGA) and experiencing rapid or slow growth after birth are associated with later-life obesity. Understanding the associations of dietary quality during pregnancy with infant growth may inform obesity prevention strategies. Objective To evaluate the associations of prenatal dietary quality according to the Healthy Eating Index (HEI) and the Empirical Dietary Inflammatory Pattern (EDIP) with infant size at birth and infant growth from birth to age 24 months. Design, Setting, and Participants This cohort study used data from birthing parent–child dyads in 8 cohorts participating in the Environmental influences on Child Health Outcomes program between 2007 and 2021. Data were analyzed from March 2021 to August 2024. Exposures The HEI and the EDIP dietary patterns. Main Outcomes and Measures Outcomes of interest were infant birth weight, categorized as SGA, reference range, or LGA, and infant growth from birth to ages 6, 12, and 24 months, categorized as slow growth (weight-for-length z score [WLZ] score difference &lt;−0.67), within reference range (WLZ score difference −0.67 to 0.67), or rapid (WLZ score difference, &gt;0.67). Results The study included 2854 birthing parent–child dyads (median [IQR] maternal age, 30 [25-34] years; 1464 [51.3%] male infants). The cohort was racially and ethnically diverse, including 225 Asian or Pacific Islander infants (7.9%), 640 Black infants (22.4%), 1022 Hispanic infants (35.8%), 664 White infants (23.3%), and 224 infants (7.8%) with other race or multiple races. A high HEI score (&gt;80), indicative of a healthier diet, was associated with lower odds of LGA (adjusted odds ratio [aOR], 0.88 [95% CI, 0.79-0.98]), rapid growth from birth to age 6 months (aOR, 0.80 [95% CI, 0.37-0.94]) and age 24 months (aOR 0.82 [95% CI, 0.70- 0.96]), and slow growth from birth to age 6 months (aOR, 0.65 [95% CI, 0.50-0.84]), 12 months (aOR, 0.74 [95% CI, 0.65-0.83]), and 24 months (OR, 0.65 [95% CI, 0.56-0.76]) compared with an HEI score 80 or lower. There was no association between high HEI and SGA (aOR, 1.14 [95% CI, 0.95-1.35]). A low EDIP score (ie, ≤63.6), indicative of a less inflammatory diet, was associated with higher odds of LGA (aOR, 1.24 [95% CI, 1.13-1.36]) and rapid infant growth from birth to age 12 months (aOR, 1.50 [95% CI, 1.18-1.91]) and lower odds of rapid growth to age 6 months (aOR, 0.77 [95% CI, 0.71-0.83]), but there was no association with SGA (aOR, 0.80 [95% CI, 0.51-1.25]) compared with an EDIP score of 63.6 or greater. Conclusions and Relevance In this cohort study, a prenatal diet that aligned with the US Dietary Guidelines was associated with reduced patterns of rapid and slow infant growth, known risk factors associated with obesity. Future research should examine whether interventions to improve prenatal diet are also beneficial in improving growth trajectory in children.
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Within the evolving field of obstetrics and gynecology, providers should possess the ability to effectively and critically evaluate medical literature in order to best adapt and incorporate evidence-based practice. For both clinicians and researchers alike, we provide a systematic approach for reviewing a journal article published in the medical literature. We summarize the various types of study designs, with dedicated attention to observational and experimental studies, and examine sources of bias inherent to these study designs. Finally, we review important considerations when interpreting the validity and significance of the results and conclusions of a research study.
Inflammatory biomarkers have been used to portend disease severity in nonpregnant individuals with SARS-CoV-2 infection. However, currently, limited data are available, and with mixed results, to elucidate which inflammatory biomarkers may be most associated with clinical phenotype in pregnant patients.We aimed to compare laboratory findings among pregnant patients with SARS-CoV-2 infection by symptom status and disease severity.We retrospectively evaluated pregnant patients with positive SARS-CoV-2 infection, confirmed through polymerase chain reaction testing, at an urban academic US hospital between March 2020 and October 2020, performed for reported symptoms or universal screening on admission. In our hospital, all patients with SARS-CoV-2 infection were recommended to have baseline laboratory testing, including leukocyte, neutrophil, and lymphocyte counts; aspartate aminotransferase and alanine aminotransferase; high-sensitivity C-reactive protein; procalcitonin; lactate dehydrogenase; D-dimer; and ferritin. We performed multivariable logistic regression to evaluate peak laboratory abnormalities significantly associated with symptomatic SARS-CoV-2 infection and disease severity with gestational age at diagnosis, maternal age, and obesity as covariates. The sensitivity and specificity of laboratory abnormalities were calculated to identify symptomatic vs asymptomatic infection and severe to critical disease vs mild to moderate disease.We identified 175 pregnant patients with SARS-CoV-2 infection, of whom 100 (57%) were symptomatic; 17 (17%) of those who were symptomatic had a severe to critical disease. Laboratory data were available for 128 patients, of whom 67 (52%) were symptomatic. Compared with asymptomatic individuals, symptomatic individuals were more likely to exhibit elevated high-sensitivity C-reactive protein levels after adjusting for gestational age (adjusted odds ratio, 5.67; 95% confidence interval, 1.42-22.52; sensitivity, 81%; specificity, 43%). In symptomatic individuals, transaminitis (adjusted odds ratio, 5.67; 95% confidence interval, 1.27-25.43), elevated procalcitonin levels (adjusted odds ratio, 16.60; 95% confidence interval, 2.61-105.46), and elevated lactate dehydrogenase levels (adjusted odds ratio, 17.55; 95% confidence interval, 2.51-122.78) were independently associated with severe to critical disease rather than mild to moderate disease after adjusting for maternal age and obesity. For differentiating disease severity, sensitivity rates for transaminitis, procalcitonin elevation, and lactate dehydrogenase elevation were 47%, 87%, and 53%, respectively, whereas the specificity rates were 89%, 63%, and 90%, respectively.Inflammatory biomarkers in pregnant patients with SARS-CoV-2 infection exhibited vast heterogeneity, poor discriminative ability, and thereby limited clinical utility. Larger registry studies should evaluate which inflammatory biomarkers may be most useful for risk stratification and prognostication of pregnant patients with SARS-CoV-2 infection, taking into account the physiology of pregnancy.
Abstract Using pooled vaginal microbiota data from pregnancy cohorts (N = 683 participants) in the Environmental influences on Child Health Outcomes (ECHO) Program, we analyzed 16S rRNA gene amplicon sequences to identify clinical and demographic host factors that associate with vaginal microbiota structure in pregnancy both within and across diverse cohorts. Using PERMANOVA models, we assessed factors associated with vaginal community structure in pregnancy, examined whether host factors were conserved across populations, and tested the independent and combined effects of host factors on vaginal community state types (CSTs) using multinomial logistic regression models. Demographic and social factors explained a larger amount of variation in the vaginal microbiome in pregnancy than clinical factors. After adjustment, lower education, rather than self-identified race, remained a robust predictor of L. iners dominant (CST III) and diverse (CST IV) (OR = 8.44, 95% CI = 4.06–17.6 and OR = 4.18, 95% CI = 1.88–9.26, respectively). In random forest models, we identified specific taxonomic features of host factors, particularly urogenital pathogens associated with pregnancy complications ( Aerococcus christensenii and Gardnerella spp.) among other facultative anaerobes and key markers of community instability ( L. iners ). Sociodemographic factors were robustly associated with vaginal microbiota structure in pregnancy and should be considered as sources of variation in human microbiome studies.
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