Using machine learning to predict the risk of developing hypertensive disorders of pregnancy using a contemporary nulliparous cohort.

Background: Hypertensive disorders of pregnancy (HDP) are significant drivers of maternal and neonatal morbidity and mortality. Current management strategies include early identification and initiation of risk mitigating interventions facilitated by a rules-based checklist. Advanced analytic techniques, such as machine learning, can potentially offer improved and refined predictive capabilities. Objective: To develop and internally validate a machine learning prediction model for hypertensive disorders of pregnancy (HDP) when initiating prenatal care. Study Design: We developed a prediction model using data from the prospective multisite cohort Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) among low-risk individuals without a prior history of aspirin utilization for preeclampsia prevention. The primary outcome was the development of HDP. Random forest modeling was utilized to develop predictive models. Recursive feature elimination (RFE) was employed to create a reduced model for each outcome. Area under the curve (AUC), 95% confidence intervals (CI), and calibration curves were utilized to assess discrimination and accuracy. Sensitivity analyses were conducted to compare the sensitivity and specificity of the reduced model compared to existing risk factor-based algorithms. Results: Of 9,124 assessed low risk nulliparous individuals, 21% (n=1,927) developed HDP. The prediction model for HDP had satisfactory discrimination with an AUC of 0.73 (95% CI: 0.70, 0.75). After RFE, a parsimonious reduced model with 30 features was created with an AUC of 0.71 (95% CI: 0.68, 0.74). Variables included in the model after RFE included body mass index at the first study visit, pre-pregnancy weight, first trimester complete blood count results, and maximum systolic blood pressure at the first visit. Calibration curves for all models revealed relatively stable agreement between predicted and observed probabilities. Sensitivity analysis noted superior sensitivity (AUC 0.80 vs 0.65) and specificity (0.65 vs 0.53) of the model compared to traditional risk factor-based algorithms. Conclusion: In cohort of low-risk nulliparous pregnant individuals, a prediction model may accurately predict HDP diagnosis at the time of initiating prenatal care and aid employment of close interval monitoring and prophylactic measures earlier in pregnancy.

Comparative effectiveness trial of metformin versus insulin for the treatment of gestational diabetes in the USA: clinical trial protocol for the multicentre DECIDE study.

INTRODUCTION: Gestational diabetes mellitus (GDM) is one of the most common medical complications of pregnancy. Glycaemic control decreases the risk of adverse pregnancy outcomes for the affected pregnant individual and the infant exposed in utero. One in four individuals with GDM will require pharmacotherapy to achieve glycaemic control. Injectable insulin has been the mainstay of pharmacotherapy. Oral metformin is an alternative option increasingly used in clinical practice. Both insulin and metformin reduce the risk of adverse pregnancy outcomes, but comparative effectiveness data from a well-characterised, adequately powered study of a diverse US population remain lacking. Because metformin crosses the placenta, long-term safety data, in particular, the risk of childhood obesity, from exposed children are also needed. In addition, the patient-reported experiences of individuals with GDM requiring pharmacotherapy remain to be characterised, including barriers to and facilitators of metformin versus insulin use. METHODS AND ANALYSIS: In a two-arm open-label, pragmatic comparative effectiveness randomised controlled trial, we will determine if metformin is not inferior to insulin in reducing adverse pregnancy outcomes, is comparably safe for exposed individuals and children, and if patient-reported factors, including facilitators of and barriers to use, differ between metformin and insulin. We plan to recruit 1572 pregnant individuals with GDM who need pharmacotherapy at 20 US sites using consistent diagnostic and treatment criteria for oral metformin versus injectable insulin and follow them and their children through delivery to 2 years post partum. More information is available at www.decidestudy.org. ETHICS AND DISSEMINATION: The Institutional Review Board at The Ohio State University approved this study (IRB: 2024H0193; date: 7 December 2024). We plan to submit manuscripts describing the results of each study aim, including the pregnancy outcomes, the 2-year follow-up outcomes, and mixed-methods assessment of patient experiences for publication in peer-reviewed journals and presentations at international scientific meetings. TRIAL REGISTRATION NUMBER: NCT06445946.

Birthing Parent Experiences of Postpartum at-Home Blood Pressure Monitoring Versus Office-Based Follow up After Diagnosis of Hypertensive Disorders of Pregnancy.

Hypertensive disorders of pregnancy are a leading cause of pregnancy-related morbidity and mortality. The primary objective of this study was to compare the frequency of documentation of postpartum blood pressure through remote blood pressure monitoring with text-message delivered reminders versus office-based follow-up 7-10 days postpartum. The secondary objective was to examine barriers and facilitators of both care strategies from the perspectives of individuals who experienced a hypertensive disorder of pregnancy. We conducted a randomized controlled trial at a tertiary care academic medical center in the southeastern US with 100 postpartum individuals (50 per arm) from 2018 to 2019. Among 100 trial participants, blood pressure follow-up within 7-10 days postpartum was higher albeit not statistically significant between postpartum individuals randomized to the remote assessment intervention versus office-based standard care (absolute risk difference 18.0%, 95% CI -0.1 to 36.1%, p = 0.06). Patient-reported facilitators for remote blood pressure monitoring were maternal convenience, clarity of instructions, and reassurance from the health assessments. These positive aspects occurred alongside barriers, which included constraints due to newborn needs and the realities of daily postpartum life.

Enhancing Clinical Diagnosis With Convolutional Neural Networks: Developing High-Accuracy Deep Learning Models for Differentiating Thoracic Pathologies.

Background The use of computational technology in medicine has allowed for an increase in the accuracy of clinical diagnosis, reducing errors through additional layers of oversight. Artificial intelligence technologies present the potential to further augment and expedite the accuracy, quality, and efficiency at which diagnosis can be made when used as an adjunctive tool. Such techniques, if found to be accurate and reliable in their diagnostic acuity, can be implemented to foster better clinical decision-making, improving patient quality of care while reducing healthcare costs. Methodology This study implemented convolution neural networks to develop a deep learning model capable of differentiating normal chest X-rays from those indicating pneumonia, tuberculosis, cardiomegaly, and COVID-19. There were 3,063 normal chest X-rays, 3,098 pneumonia chest X-rays, 2,920 COVID-19 chest X-rays, 2,214 chest X-rays, and 554 tuberculosis chest X-rays from Kaggle that were used for training and validation. The model was trained to recognize patterns within the chest X-rays to efficiently recognize these diseases within patients to be treated on time. Results The results indicated a success rate of 98.34% incorrect detections, exemplifying a high degree of accuracy. There are limitations to this study. Training models require hundreds to thousands of samples, and due to potential variability in image scanning equipment and techniques from which the images are sourced, the model could have learned to interpret external noise and unintended details which can adversely impact accuracy. Conclusions Further studies that implement more universal database-sourced images with similar image scanning techniques, assess diverse but related medical conditions, and the utilization of repeat trials can help assess the reliability of the model. These results highlight the potential of machine learning algorithms for disease detection with chest X-rays.

Social Determinants of Health and Diabetes in Pregnancy.

Social determinants of health (SDOH) are the conditions in which people are born, grow, work, live, and age. SDOH are systemic factors that may explain, perpetuate, and exacerbate disparities in health outcomes for different populations and can be measured at both an individual and neighborhood or community level (iSDOH, nSDOH). In pregnancy, increasing evidence shows that adverse iSDOH and/or nSDOH are associated with a greater likelihood that diabetes develops, and that when it develops, there is worse glycemic control and a greater frequency of adverse pregnancy outcomes. Future research should not only continue to examine the relationships between SDOH and adverse pregnancy outcomes with diabetes but should determine whether multi-level interventions that seek to mitigate adverse SDOH result in equitable maternal care and improved patient health outcomes for pregnant individuals living with diabetes. KEY POINTS: · SDOH are conditions in which people are born, grow, work, live, and age.. · SDOH are systemic factors that may explain, perpetuate, and exacerbate disparities in health outcomes.. · SDOH can be measured at the individual and neighborhood level.. · Adverse SDOH are associated with worse outcomes for pregnant individuals living with diabetes.. · Interventions that mitigate adverse SDOH to improve maternal health equity and outcomes are needed..

Elevated Blood Pressure in Pregnancy and Long-Term Cardiometabolic Health Outcomes.

OBJECTIVE: To examine the association between elevated blood pressure (BP) in the early third trimester and cardiometabolic health 10-14 years after delivery. METHODS: This is a secondary analysis from the prospective HAPO FUS (Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study). Blood pressure in the early third trimester was categorized per American College of Cardiology/American Heart Association thresholds for: normal BP below 120/80 mm Hg (reference), elevated BP 120-129/below 80 mm Hg, stage 1 hypertension 130-139/80-89 mm Hg, and stage 2 hypertension 140/90 mm Hg or higher. Cardiometabolic outcomes assessed 10-14 years after the index pregnancy were type 2 diabetes mellitus and measures of dyslipidemia, including low-density lipoprotein (LDL) cholesterol 130 mg/dL or higher, total cholesterol 200 mg/dL or higher, high-density lipoprotein (HDL) cholesterol 40 mg/dL or lower, and triglycerides 200 mg/dL or higher. Adjusted analysis was performed with the following covariates: study field center, follow-up duration, age, body mass index (BMI), height, family history of hypertension and diabetes, smoking and alcohol use, parity, and oral glucose tolerance test glucose z score. RESULTS: Among 4,692 pregnant individuals at a median gestational age of 27.9 weeks (interquartile range 26.6-28.9 weeks), 8.5% (n=399) had elevated BP, 14.9% (n=701) had stage 1 hypertension, and 6.4% (n=302) had stage 2 hypertension. At a median follow-up of 11.6 years, among individuals with elevated BP, there was a higher frequency of diabetes (elevated BP: adjusted relative risk [aRR] 1.88, 95% CI, 1.06-3.35; stage 1 hypertension: aRR 2.58, 95% CI, 1.62-4.10; stage 2 hypertension: aRR 2.83, 95% CI, 1.65-4.95) compared with those with normal BP. Among individuals with elevated BP, there was a higher frequency of elevated LDL cholesterol (elevated BP: aRR 1.27, 95% CI, 1.03-1.57; stage 1 hypertension: aRR 1.22, 95% CI, 1.02-1.45, and stage 2 hypertension: aRR 1.38, 95% CI, 1.10-1.74), elevated total cholesterol (elevated BP: aRR 1.27, 95% CI, 1.07-1.52; stage 1 hypertension: aRR 1.16, 95% CI, 1.00-1.35; stage 2 hypertension: aRR 1.41 95% CI, 1.16-1.71), and elevated triglycerides (elevated BP: aRR 2.24, 95% CI, 1.42-3.53; stage 1 hypertension: aRR 2.15, 95% CI, 1.46-3.17; stage 2 hypertension: aRR 3.24, 95% CI, 2.05-5.11) but not of low HDL cholesterol. CONCLUSION: The frequency of adverse cardiometabolic outcomes at 10-14 years after delivery was progressively higher among pregnant individuals with BP greater than 120/80 in the early third trimester.

Diet quality, community food access, and glycemic control among nulliparous individuals with diabetes.

Better diet quality regardless of community food access was associated with a higher likelihood of glycemic control in early pregnancy among nulliparous individuals with pregestational diabetes. These findings highlight the need for interventions that address nutrition insecurity for pregnant individuals living with diabetes.

Diabetic Ketoacidosis and Adverse Outcomes Among Pregnant Individuals With Pregestational Diabetes in the United States, 2010-2020.

OBJECTIVE: To assess the frequency of, risk factors for, and adverse outcomes associated with diabetic ketoacidosis (DKA) at delivery hospitalization among individuals with pregestational diabetes (type 1 and 2 diabetes mellitus) and secondarily to evaluate the frequency of and risk factors for antepartum and postpartum hospitalizations for DKA. METHODS: We conducted a serial, cross-sectional study using the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project Nationwide Readmissions Database from 2010 to 2020 of pregnant individuals with pregestational diabetes hospitalized for delivery. The exposures were 1) sociodemographic and clinical risk factors for DKA and 2) DKA. The outcomes were DKA at delivery hospitalization, maternal morbidity (nontransfusion severe maternal morbidity (SMM), critical care procedures, cardiac complications, acute renal failure, and transfusion), and adverse pregnancy outcomes (preterm birth, hypertensive disorders of pregnancy, and cesarean delivery) and secondarily DKA at antepartum and postpartum hospitalizations. RESULTS: Of 392,796 deliveries in individuals with pregestational diabetes (27.2% type 1 diabetes, 72.8% type 2 diabetes), there were 4,778 cases of DKA at delivery hospitalization (89.1% type 1 diabetes, 10.9% type 2 diabetes). The frequency of DKA at delivery hospitalization was 1.2% (4.0% with type 1 diabetes, 0.2% with type 2 diabetes), and the mean annual percentage change was 10.8% (95% CI, 8.2-13.2%). Diabetic ketoacidosis at delivery hospitalization was significantly more likely among those who had type 1 diabetes compared with those with type 2 diabetes, who were younger in age, who delivered at larger and metropolitan hospitals, and who had Medicaid insurance, lower income, multiple gestations, and prior psychiatric illness. Diabetic ketoacidosis during the delivery hospitalization was associated with an increased risk of nontransfusion SMM (20.8% vs 2.4%, adjusted odds ratio [aOR] 8.18, 95% CI, 7.20-9.29), critical care procedures (7.3% vs 0.4%, aOR 15.83, 95% CI, 12.59-19.90), cardiac complications (7.8% vs 0.8%, aOR 8.87, 95% CI, 7.32-10.76), acute renal failure (12.3% vs 0.7%, aOR 9.78, 95% CI, 8.16-11.72), and transfusion (6.2% vs 2.2%, aOR 2.27, 95% CI, 1.87-2.75), as well as preterm birth (31.9% vs 13.5%, aOR 2.41, 95% CI, 2.17-2.69) and hypertensive disorders of pregnancy (37.4% vs 28.1%, aOR 1.11, 95% CI, 1.00-1.23). In secondary analyses, the overall frequency of antepartum DKA was 3.1%, and the mean annual percentage change was 4.1% (95% CI, 0.3-8.6%); the overall frequency of postpartum DKA was 0.4%, and the mean annual percentage change was 3.5% (95% CI, -1.6% to 9.6%). Of 3,092 antepartum hospitalizations among individuals with DKA, 15.7% (n=485) had a recurrent case of DKA at delivery hospitalization. Of 1,419 postpartum hospitalizations among individuals with DKA, 20.0% (n=285) previously had DKA at delivery hospitalization. The above risk factors for DKA at delivery hospitalization were similar for DKA at antepartum and postpartum hospitalizations. CONCLUSION: The frequency of DKA at delivery hospitalization and antepartum hospitalizations for DKA increased between 2010 and 2020 among deliveries in individuals with pregestational diabetes in the United States. Diabetic ketoacidosis is associated with an increased risk of maternal morbidity and adverse pregnancy outcomes. Risk factors for DKA at delivery were similar to those for DKA during the antepartum and postpartum periods.

Clinical Presentation and Outcomes of Diabetic Ketoacidosis in Pregnancy.

OBJECTIVE: To examine the presentation, management, and outcomes of pregnancies complicated by diabetic ketoacidosis (DKA) in a contemporary obstetric population. METHODS: This is a case series of all admissions for DKA during pregnancy at a single Midwestern academic medical center over a 10-year period. Diabetic ketoacidosis was defined per the following diagnostic criteria: anion gap more than 12 mEq/L, pH less than 7.30 or bicarbonate less than 15 mEq/L, and elevated serum or urine ketones. Demographic information, clinical characteristics, and maternal and neonatal outcomes were assessed. Patient characteristics and clinical outcomes were compared between individuals with type 1 and those with type 2 diabetes mellitus. RESULTS: Between 2012 and 2021, there were 129 admissions for DKA in 103 pregnancies in 97 individuals. Most individuals (n=75, 77.3%) admitted for DKA during pregnancy had type 1 diabetes. The majority of admissions occurred in the third trimester (median gestational age 29 3/7 weeks). The most common precipitating factors were vomiting or gastrointestinal illness (38.0%), infection (25.6%), and insulin nonadherence (20.9%). Median glucose on admission was 252 mg/dL (interquartile range 181-343 mg/dL), and 21 patients (17.6%) were admitted with euglycemic DKA. Fifteen admissions (11.6%) were to the intensive care unit. Pregnancy loss was diagnosed during admission in six individuals (6.3%, 95% CI, 2.3-13.7%). Among pregnant individuals with at least one admission for DKA, the median gestational age at delivery was 34 6/7 weeks (interquartile range 33 2/7-36 3/7 weeks). Most neonates (85.7%, 95% CI, 76.8-92.2%) were admitted to the neonatal intensive care unit and required treatment for hypoglycemia. The cesarean delivery rate was 71.9%. Despite similar hemoglobin A1C values before pregnancy and at admission, individuals with type 1 diabetes had higher serum glucose (median [interquartile range], 256 mg/dL [181-353 mg/dL] vs 216 mg/dL [136-258 mg/dL], P=.04) and higher serum ketones (3.78 mg/dL [2.13-5.50 mg/dL] vs 2.56 mg/dL [0.81-4.69 mg/dL] mg/dL, P=.03) on admission compared with those with type 2 diabetes. Individuals with type 2 diabetes required intravenous insulin therapy for a longer duration (55 hours [29.5-91.5 hours] vs 27 hours [19-38 hours], P=.004) and were hospitalized longer (5 days [4-9 days] vs 4 days [3-6 days], P=.004). CONCLUSION: Diabetic ketoacidosis occurred predominantly in pregnancies affected by type 1 diabetes. Individuals with type 1 diabetes presented with greater DKA severity but achieved clinical resolution more rapidly than those with type 2 diabetes. These results may provide a starting point for the development of interventions to decrease maternal and neonatal morbidity related to DKA in the modern obstetric population.

Special Supplemental Nutrition Program for Women, Infants, and Children Enrollment and Adverse Pregnancy Outcomes Among Nulliparous Individuals.

OBJECTIVE: To evaluate the relationship between changes in Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) enrollment during pregnancy from 2016 to 2019 and rates of adverse pregnancy outcomes in U.S. counties in 2019. METHODS: We conducted a serial, cross-sectional ecologic study at the county level using National Center for Health Statistics natality data from 2016 to 2019 of nulliparous individuals eligible for WIC. The exposure was the change in county-level WIC enrollment from 2016 to 2019 (increase [more than 0%] vs no change or decrease [0% or less]). Outcomes were adverse pregnancy outcomes assessed in 2019 and included maternal outcomes (ie, gestational diabetes mellitus [GDM], hypertensive disorders of pregnancy, cesarean delivery, intensive care unit [ICU] admission, and transfusion) and neonatal outcomes (ie, large for gestational age [LGA], small for gestational age [SGA], preterm birth, and neonatal intensive care unit [NICU] admission). RESULTS: Among 1,945,914 deliveries from 3,120 U.S. counties, the age-standardized rate of WIC enrollment decreased from 73.1 (95% CI, 73.0-73.2) per 100 live births in 2016 to 66.1 (95% CI, 66.0-66.2) per 100 live births in 2019, for a mean annual percent change decrease of 3.2% (95% CI, -3.7% to -2.9%) per year. Compared with individuals in counties in which WIC enrollment decreased or did not change, individuals living in counties in which WIC enrollment increased had lower rates of maternal adverse pregnancy outcomes, including GDM (adjusted odds ratio [aOR] 0.71, 95% CI, 0.57-0.89), ICU admission (aOR 0.47, 95% CI, 0.34-0.65), and transfusion (aOR 0.68, 95% CI, 0.53-0.88), and neonatal adverse pregnancy outcomes, including preterm birth (aOR 0.71, 95% CI, 0.56-0.90) and NICU admission (aOR 0.77, 95% CI, 0.60-0.97), but not cesarean delivery, hypertensive disorders of pregnancy, or LGA or SGA birth. CONCLUSION: Increasing WIC enrollment during pregnancy at the county level was associated with a lower risk of adverse pregnancy outcomes. In an era when WIC enrollment has decreased and food and nutrition insecurity has increased, efforts are needed to increase WIC enrollment among eligible individuals in pregnancy.

Impact of hypertensive disorders of pregnancy and gestational diabetes mellitus on offspring cardiovascular health in early adolescence.

BACKGROUND: Adverse pregnancy outcomes, including hypertensive disorders of pregnancy and gestational diabetes mellitus, influence maternal cardiovascular health long after pregnancy, but their relationship to offspring cardiovascular health following in-utero exposure remains uncertain. OBJECTIVE: To examine associations of hypertensive disorders of pregnancy or gestational diabetes mellitus with offspring cardiovascular health in early adolescence. STUDY DESIGN: This analysis used data from the prospective Hyperglycemia and Adverse Pregnancy Outcome Study from 2000 to 2006 and the Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study from 2013 to 2016. This analysis included 3317 mother-child dyads from 10 field centers, comprising 70.8% of Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study participants. Those with pregestational diabetes and chronic hypertension were excluded. The exposures included having any hypertensive disorders of pregnancy or gestational diabetes mellitus vs not having hypertensive disorders of pregnancy or gestational diabetes mellitus, respectively (reference). The outcome was offspring cardiovascular health when aged 10-14 years, on the basis of 4 metrics: body mass index, blood pressure, total cholesterol level, and glucose level. Each metric was categorized as ideal, intermediate, or poor using a framework provided by the American Heart Association. The primary outcome was defined as having at least 1 cardiovascular health metric that was nonideal vs all ideal (reference), and the second outcome was the number of nonideal cardiovascular health metrics (ie, at least 1 intermediate metric, 1 poor metric, or at least 2 poor metrics vs all ideal [reference]). Modified poisson regression with robust error variance was used and adjusted for covariates at pregnancy enrollment, including field center, parity, age, gestational age, alcohol or tobacco use, child's assigned sex at birth, and child's age at follow-up. RESULTS: Among 3317 maternal-child dyads, the median (interquartile) ages were 30.4 (25.6-33.9) years for pregnant individuals and 11.6 (10.9-12.3) years for children. During pregnancy, 10.4% of individuals developed hypertensive disorders of pregnancy, and 14.6% developed gestational diabetes mellitus. At follow-up, 55.5% of offspring had at least 1 nonideal cardiovascular health metric. In adjusted models, having hypertensive disorders of pregnancy (adjusted risk ratio, 1.14 [95% confidence interval, 1.04-1.25]) or having gestational diabetes mellitus (adjusted risk ratio, 1.10 [95% confidence interval, 1.02-1.19]) was associated with a greater risk that offspring developed less-than-ideal cardiovascular health when aged 10-14 years. The above associations strengthened in magnitude as the severity of adverse cardiovascular health metrics increased (ie, with the outcome measured as ≥1 intermediate, 1 poor, and ≥2 poor adverse metrics), albeit the only statistically significant association was with the "1-poor-metric" exposure. CONCLUSION: In this multinational prospective cohort, pregnant individuals who experienced either hypertensive disorders of pregnancy or gestational diabetes mellitus were at significantly increased risk of having offspring with worse cardiovascular health in early adolescence. Reducing adverse pregnancy outcomes and increasing surveillance with targeted interventions after an adverse pregnancy outcome should be studied as potential avenues to enhance long-term cardiovascular health in the offspring exposed in utero.

Socioeconomic disadvantage in pregnancy and postpartum risk of cardiovascular disease.

BACKGROUND: Pregnancy is an educable and actionable life stage to address social determinants of health (SDOH) and lifelong cardiovascular disease (CVD) prevention. However, the link between a risk score that combines multiple neighborhood-level social determinants in pregnancy and the risk of long-term CVD remains to be evaluated. OBJECTIVE: To examine whether neighborhood-level socioeconomic disadvantage measured by the Area Deprivation Index (ADI) in early pregnancy is associated with a higher 30-year predicted risk of CVD postpartum, as measured by the Framingham Risk Score. STUDY DESIGN: An analysis of data from the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be Heart Health Study longitudinal cohort. Participant home addresses during early pregnancy were geocoded at the Census-block level. The exposure was neighborhood-level socioeconomic disadvantage using the 2015 ADI by tertile (least deprived [T1], reference; most deprived [T3]) measured in the first trimester. Outcomes were the predicted 30-year risks of atherosclerotic cardiovascular disease (ASCVD, composite of fatal and nonfatal coronary heart disease and stroke) and total CVD (composite of ASCVD plus coronary insufficiency, angina pectoris, transient ischemic attack, intermittent claudication, and heart failure) using the Framingham Risk Score measured 2 to 7 years after delivery. These outcomes were assessed as continuous measures of absolute estimated risk in increments of 1%, and, secondarily, as categorical measures with high-risk defined as an estimated probability of CVD ≥10%. Multivariable linear regression and modified Poisson regression models adjusted for baseline age and individual-level social determinants, including health insurance, educational attainment, and household poverty. RESULTS: Among 4309 nulliparous individuals at baseline, the median age was 27 years (interquartile range [IQR]: 23-31) and the median ADI was 43 (IQR: 22-74). At 2 to 7 years postpartum (median: 3.1 years, IQR: 2.5, 3.7), the median 30-year risk of ASCVD was 2.3% (IQR: 1.5, 3.5) and of total CVD was 5.5% (IQR: 3.7, 7.9); 2.2% and 14.3% of individuals had predicted 30-year risk ≥10%, respectively. Individuals living in the highest ADI tertile had a higher predicted risk of 30-year ASCVD % (adjusted ß: 0.41; 95% confidence interval [CI]: 0.19, 0.63) compared with those in the lowest tertile; and those living in the top 2 ADI tertiles had higher absolute risks of 30-year total CVD % (T2: adj. ß: 0.37; 95% CI: 0.03, 0.72; T3: adj. ß: 0.74; 95% CI: 0.36, 1.13). Similarly, individuals living in neighborhoods in the highest ADI tertile were more likely to have a high 30-year predicted risk of ASCVD (adjusted risk ratio [aRR]: 2.21; 95% CI: 1.21, 4.02) and total CVD ≥10% (aRR: 1.35; 95% CI: 1.08, 1.69). CONCLUSION: Neighborhood-level socioeconomic disadvantage in early pregnancy was associated with a higher estimated long-term risk of CVD postpartum. Incorporating aggregated SDOH into existing clinical workflows and future research in pregnancy could reduce disparities in maternal cardiovascular health across the lifespan, and requires further study.

Adverse Pregnancy Outcomes and Predicted 30-Year Risk of Maternal Cardiovascular Disease 2-7 Years After Delivery.

OBJECTIVE: To determine whether adverse pregnancy outcomes are associated with a higher predicted 30-year risk of atherosclerotic cardiovascular disease (CVD; ie, coronary artery disease or stroke). METHODS: This was a secondary analysis of the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be Heart Health Study longitudinal cohort. The exposures were adverse pregnancy outcomes during the first pregnancy (ie, gestational diabetes mellitus [GDM], hypertensive disorder of pregnancy, preterm birth, and small- and large-for-gestational-age [SGA, LGA] birth weight) modeled individually and secondarily as the cumulative number of adverse pregnancy outcomes (ie, none, one, two or more). The outcome was the 30-year risk of atherosclerotic CVD predicted with the Framingham Risk Score assessed at 2-7 years after delivery. Risk was measured both continuously in increments of 1% and categorically, with high predicted risk defined as a predicted risk of atherosclerotic CVD of 10% or more. Linear regression and modified Poisson models were adjusted for baseline covariates. RESULTS: Among 4,273 individuals who were assessed at a median of 3.1 years after delivery (interquartile range 2.5-3.7), the median predicted 30-year atherosclerotic CVD risk was 2.2% (interquartile range 1.4-3.4), and 1.8% had high predicted risk. Individuals with GDM (least mean square 5.93 vs 4.19, adjusted ß=1.45, 95% CI, 1.14-1.75), hypertensive disorder of pregnancy (4.95 vs 4.22, adjusted ß=0.49, 95% CI, 0.31-0.68), and preterm birth (4.81 vs 4.27, adjusted ß=0.47, 95% CI, 0.24-0.70) were more likely to have a higher absolute risk of atherosclerotic CVD. Similarly, individuals with GDM (8.7% vs 1.4%, adjusted risk ratio [RR] 2.02, 95% CI, 1.14-3.59), hypertensive disorder of pregnancy (4.4% vs 1.4%, adjusted RR 1.91, 95% CI, 1.17-3.13), and preterm birth (5.0% vs 1.5%, adjusted RR 2.26, 95% CI, 1.30-3.93) were more likely to have a high predicted risk of atherosclerotic CVD. A greater number of adverse pregnancy outcomes within the first birth was associated with progressively greater risks, including per 1% atherosclerotic CVD risk (one adverse pregnancy outcome: 4.86 vs 4.09, adjusted ß=0.59, 95% CI, 0.43-0.75; two or more adverse pregnancy outcomes: 5.51 vs 4.09, adjusted ß=1.16, 95% CI, 0.82-1.50), and a high predicted risk of atherosclerotic CVD (one adverse pregnancy outcome: 3.8% vs 1.0%, adjusted RR 2.33, 95% CI, 1.40-3.88; two or more adverse pregnancy outcomes: 8.7 vs 1.0%, RR 3.43, 95% CI, 1.74-6.74). Small and large for gestational age were not consistently associated with a higher atherosclerotic CVD risk. CONCLUSION: Individuals who experienced adverse pregnancy outcomes in their first birth were more likely to have a higher predicted 30-year risk of CVD measured at 2-7 years after delivery. The magnitude of risk was higher with a greater number of adverse pregnancy outcomes experienced.

A growth chart of brain function from infancy to adolescence based on EEG.

BACKGROUND: In children, objective, quantitative tools that determine functional neurodevelopment are scarce and rarely scalable for clinical use. Direct recordings of cortical activity using routinely acquired electroencephalography (EEG) offer reliable measures of brain function. METHODS: We developed and validated a measure of functional brain age (FBA) using a residual neural network-based interpretation of the paediatric EEG. In this cross-sectional study, we included 1056 children with typical development ranging in age from 1 month to 18 years. We analysed a 10- to 15-min segment of 18-channel EEG recorded during light sleep (N1 and N2 states). FINDINGS: The FBA had a weighted mean absolute error (wMAE) of 0.85 years (95% CI: 0.69-1.02; n = 1056). A two-channel version of the FBA had a wMAE of 1.51 years (95% CI: 1.30-1.73; n = 1056) and was validated on an independent set of EEG recordings (wMAE = 2.27 years, 95% CI: 1.90-2.65; n = 723). Group-level maturational delays were also detected in a small cohort of children with Trisomy 21 (Cohen's d = 0.36, p = 0.028). INTERPRETATION: A FBA, based on EEG, is an accurate, practical and scalable automated tool to track brain function maturation throughout childhood with accuracy comparable to widely used physical growth charts. FUNDING: This research was supported by the National Health and Medical Research Council, Australia, Helsinki University Diagnostic Center Research Funds, Finnish Academy, Finnish Paediatric Foundation, and Sigrid Juselius Foundation.

Effective connectivity of working memory performance: a DCM study of MEG data.

Visual working memory (WM) engages several nodes of a large-scale network that includes frontal, parietal, and visual regions; however, little is understood about how these regions interact to support WM behavior. In particular, it is unclear whether network dynamics during WM maintenance primarily represent feedforward or feedback connections. This question has important implications for current debates about the relative roles of frontoparietal and visual regions in WM maintenance. In the current study, we investigated the network activity supporting WM using MEG data acquired while healthy subjects performed a multi-item delayed estimation WM task. We used computational modeling of behavior to discriminate correct responses (high accuracy trials) from two different types of incorrect responses (low accuracy and swap trials), and dynamic causal modeling of MEG data to measure effective connectivity. We observed behaviorally dependent changes in effective connectivity in a brain network comprising frontoparietal and early visual areas. In comparison with high accuracy trials, frontoparietal and frontooccipital networks showed disrupted signals depending on type of behavioral error. Low accuracy trials showed disrupted feedback signals during early portions of WM maintenance and disrupted feedforward signals during later portions of maintenance delay, while swap errors showed disrupted feedback signals during the whole delay period. These results support a distributed model of WM that emphasizes the role of visual regions in WM storage and where changes in large scale network configurations can have important consequences for memory-guided behavior.