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. But 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. METHODS: An analysis of data from the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be (nuMoM2b) 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 CVD (ASCVD, composite of fatal and non-fatal 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 4,309 nulliparous individuals at baseline, the median age was 27 years (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 % (adj. ß: 0.41; 95% CI: 0.19, 0.63) compared with those in the lowest tertile; and those living in the top two 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 (aRR: 2.21; 95% CI: 1.21, 4.02) and total CVD ≥10% (aRR: 1.35; 95% CI: 1.08, 1.69). CONCLUSIONS: 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.

AI-enabled left atrial volumetry in coronary artery calcium scans (AI-CACTM) predicts atrial fibrillation as early as one year, improves CHARGE-AF, and outperforms NT-proBNP: The multi-ethnic study of atherosclerosis.

BACKGROUND: Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported. METHODS: We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CACTM) to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA). AI-CAC took on average 21 â€‹s per CAC scan. We used the 5-year outcomes data for incident atrial fibrillation (AF) and assessed discrimination using the time-dependent area under the curve (AUC) of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP. The mean follow-up time to an AF event was 2.9 â€‹± â€‹1.4 years. RESULTS: At 1,2,3,4, and 5 years follow-up 36, 77, 123, 182, and 236 cases of AF were identified, respectively. The AUC for AI-CAC LA volume was significantly higher than CHARGE-AF for Years 1, 2, and 3 (0.83 vs. 0.74, 0.84 vs. 0.80, and 0.81 vs. 0.78, respectively, all p â€‹< â€‹0.05), but similar for Years 4 and 5, and significantly higher than NT-proBNP at Years 1-5 (all p â€‹< â€‹0.01), but not for combined CHARGE-AF and NT-proBNP at any year. AI-CAC LA significantly improved the continuous Net Reclassification Index for prediction of AF over years 1-5 when added to CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and NT-proBNP (0.68, 0.44, 0.42, 0.30, 0.37) (all p â€‹< â€‹0.01). CONCLUSION: AI-CAC LA volume enabled prediction of AF as early as one year and significantly improved on risk classification of CHARGE-AF Risk Score and NT-proBNP.

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.

Prediction of metabolic syndrome following a first pregnancy.

BACKGROUND: The prevalence of metabolic syndrome is rapidly increasing in the United States. We hypothesized that prediction models using data obtained during pregnancy can accurately predict the future development of metabolic syndrome. OBJECTIVE: This study aimed to develop machine learning models to predict the development of metabolic syndrome using factors ascertained in nulliparous pregnant individuals. STUDY DESIGN: This was a secondary analysis of a prospective cohort study (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be Heart Health Study [nuMoM2b-HHS]). Data were collected from October 2010 to October 2020, and analyzed from July 2023 to October 2023. Participants had in-person visits 2 to 7 years after their first delivery. The primary outcome was metabolic syndrome, defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, which was measured within 2 to 7 years after delivery. A total of 127 variables that were obtained during pregnancy were evaluated. The data set was randomly split into a training set (70%) and a test set (30%). We developed a random forest model and a lasso regression model using variables obtained during pregnancy. We compared the area under the receiver operating characteristic curve for both models. Using the model with the better area under the receiver operating characteristic curve, we developed models that included fewer variables based on SHAP (SHapley Additive exPlanations) values and compared them with the original model. The final model chosen would have fewer variables and noninferior areas under the receiver operating characteristic curve. RESULTS: A total of 4225 individuals met the inclusion criteria; the mean (standard deviation) age was 27.0 (5.6) years. Of these, 754 (17.8%) developed metabolic syndrome. The area under the receiver operating characteristic curve of the random forest model was 0.878 (95% confidence interval, 0.846-0.909), which was higher than the 0.850 of the lasso model (95% confidence interval, 0.811-0.888; P<.001). Therefore, random forest models using fewer variables were developed. The random forest model with the top 3 variables (high-density lipoprotein, insulin, and high-sensitivity C-reactive protein) was chosen as the final model because it had the area under the receiver operating characteristic curve of 0.867 (95% confidence interval, 0.839-0.895), which was not inferior to the original model (P=.08). The area under the receiver operating characteristic curve of the final model in the test set was 0.847 (95% confidence interval, 0.821-0.873). An online application of the final model was developed (https://kawakita.shinyapps.io/metabolic/). CONCLUSION: We developed a model that can accurately predict the development of metabolic syndrome in 2 to 7 years after delivery.

Reporting Health Consequences of War in Medical Journals: First, Do No Harm.

This Viewpoint suggests that medical and public health journals should publish articles focused singularly on health without political bias when reporting on the health consequences of war.

MRI Investigation of the Association of Left Atrial and Left Atrial Appendage Hemodynamics with Silent Brain Infarction.

BACKGROUND: Left atrial (LA) myopathy is thought to be associated with silent brain infarctions (SBI) through changes in blood flow hemodynamics leading to thrombogenesis. 4D-flow MRI enables in-vivo hemodynamic quantification in the left atrium (LA) and LA appendage (LAA). PURPOSE: To determine whether LA and LAA hemodynamic and volumetric parameters are associated with SBI. STUDY TYPE: Prospective observational study. POPULATION: A single-site cohort of 125 Participants of the multiethnic study of atherosclerosis (MESA), mean age: 72.3 ± 7.2 years, 56 men. FIELD STRENGTH/SEQUENCE: 1.5T. Cardiac MRI: Cine balanced steady state free precession (bSSFP) and 4D-flow sequences. Brain MRI: T1- and T2-weighted SE and FLAIR. ASSESSMENT: Presence of SBI was determined from brain MRI by neuroradiologists according to routine diagnostic criteria in all participants without a history of stroke based on the MESA database. Minimum and maximum LA volumes and ejection fraction were calculated from bSSFP data. Blood stasis (% of voxels <10 cm/sec) and peak velocity (cm/sec) in the LA and LAA were assessed by a radiologist using an established 4D-flow workflow. STATISTICAL TESTS: Student's t test, Mann-Whitney U test, one-way ANOVA, chi-square test. Multivariable stepwise logistic regression with automatic forward and backward selection. Significance level P < 0.05. RESULTS: 26 (20.8%) had at least one SBI. After Bonferroni correction, participants with SBI were significantly older and had significantly lower peak velocities in the LAA. In multivariable analyses, age (per 10-years) (odds ratio (OR) = 1.99 (95% confidence interval (CI): 1.30-3.04)) and LAA peak velocity (per cm/sec) (OR = 0.87 (95% CI: 0.81-0.93)) were significantly associated with SBI. CONCLUSION: Older age and lower LAA peak velocity were associated with SBI in multivariable analyses whereas volumetric-based measures from cardiac MRI or cardiovascular risk factors were not. Cardiac 4D-flow MRI showed potential to serve as a novel imaging marker for SBI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Associations between 3D-based Left Atrial Volumetric and Blood Flow Parameters in a Single-Site Cohort of the Multi-Ethnic Study of Atherosclerosis.

Purpose To investigate associations between left atrial volume (LAV) and function with impaired three-dimensional hemodynamics from four-dimensional flow MRI. Materials and Methods A subcohort of participants from the Multi-Ethnic Study of Atherosclerosis from Northwestern University underwent prospective 1.5-T cardiac MRI including whole-heart four-dimensional flow and short-axis cine imaging between 2019 and 2020. Four-dimensional flow MRI analysis included manual three-dimensional segmentations of the LA and LA appendage (LAA), which were used to quantify LA and LAA peak velocity and blood stasis (% voxels < 0.1 m/sec). Short-axis cine data were used to delineate LA contours on all cardiac time points, and the resulting three-dimensional-based LAVs were extracted for calculation of LA emptying fractions (LAEFtotal, LAEFactive, LAEFpassive). Stepwise multivariable linear models were calculated for each flow parameter (LA stasis, LA peak velocity, LAA stasis, LAA peak velocity) to determine associations with LAV and LAEF. Results This study included 158 participants (mean age, 73 years ± 7 [SD]; 83 [52.5%] female and 75 [47.4%] male participants). In multivariable models, a 1-unit increase of LAEFtotal was associated with decreased LA stasis (ß coefficient, -0.47%; P < .001), while increased LAEFactive was associated with increased LA peak velocity (ß coefficient, 0.21 cm/sec; P < .001). Furthermore, increased minimum LAV indexed was most associated with impaired LAA flow (higher LAA stasis [ß coefficient, 0.65%; P < .001] and lower LAA peak velocity [ß coefficient, -0.35 cm/sec; P < .001]). Conclusion Higher minimum LAV and reduced LA function were associated with impaired flow characteristics in the LA and LAA. LAV assessment might therefore be a surrogate measure for LA and LAA flow abnormalities. Keywords: Atherosclerosis, Left Atrial Volume, Left Atrial Blood Flow, 4D Flow MRI Supplemental material is available for this article. © RSNA, 2024.

AI-enabled Left Atrial Volumetry in Cardiac CT Scans Improves CHARGE-AF and Outperforms NT-ProBNP for Prediction of Atrial Fibrillation in Asymptomatic Individuals: Multi-Ethnic Study of Atherosclerosis.

Background: Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported. Methods: We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CAC), taking on average 21 seconds per CAC scan, to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA). We used the 5-year outcomes data for incident atrial fibrillation (AF) and compared the time-dependent AUC of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP (BNP). The mean follow-up time to an AF event was 2.9±1.4 years. Results: At 1,2,3,4, and 5 years follow-up 36, 77, 123, 182, and 236 cases of AF were identified, respectively. The AUC for AI-CAC LA volume was significantly higher than CHARGE-AF or BNP at year 1 (0.836, 0.742, 0.742), year 2 (0.842, 0.807,0.772), and year 3 (0.811, 0.785, 0.745) (p<0.02), but similar for year 4 (0.785, 0.769, 0.725) and year 5 (0.781, 0.767, 0.734) respectively (p>0.05). AI-CAC LA volume significantly improved the continuous Net Reclassification Index for prediction of AF over years 1-5 when added to CAC score (0.74, 0.49, 0.53, 0.39, 0.44), CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and BNP (0.68, 0.44, 0.42, 0.30, 0.37) respectively (p<0.01). Conclusion: AI-CAC LA volume enabled prediction of AF as early as one year and significantly improved on risk classification of CHARGE-AF Risk Score and BNP.

Prevalence of frequent premature ventricular contractions and nonsustained ventricular tachycardia in older women screened for atrial fibrillation in the Women's Health Initiative.

BACKGROUND: Frequent premature ventricular contractions (PVCs) and nonsustained ventricular tachycardia (NSVT) have been associated with cardiovascular disease and mortality. Their prevalence, especially in ambulatory populations, is understudied and limited by few female participants and the use of short-duration (24- to 48-hour) monitoring. OBJECTIVE: The objective of this study was to report the prevalence of frequent PVCs and NSVT in a community-based population of women likely to undergo electrocardiogram (ECG) screening by sequential patch monitoring. METHODS: Participants from the Women's Health Initiative Strong and Healthy (WHISH) trial with no history of atrial fibrillation (AF) but 5-year predicted risk of incident AF ≥5% by CHARGE-AF score were randomly selected to undergo screening with 7-day ECG patch monitors at baseline, 6 months, and 12 months. Recordings were reviewed for PVCs and NSVT (>5 beats); data were analyzed with multivariate regression models. RESULTS: There were 1067 participants who underwent ECG screening at baseline, 866 at 6 months, and 777 at 12 months. Frequent PVCs were found on at least 1 patch from 4.3% of participants, and 1 or more episodes of NSVT were found in 12 (1.1%) women. PVC frequency directly correlated with CHARGE-AF score and NSVT on any patch. Detection of frequent PVCs increased with sequential monitoring. CONCLUSION: In postmenopausal women at high risk for AF, frequent PVCs were relatively common (4.3%) and correlated with higher CHARGE-AF score. As strategies for AF screening continue to evolve, particularly in those individuals at high risk of AF, the prevalence of incidental ventricular arrhythmias is an important benchmark to guide clinical decision-making.

Epigenetic Aging Is Associated With Measures of Midlife Muscle Volume and Attenuation in CARDIA Study.

BACKGROUND: GrimAge acceleration (GAA), an epigenetic marker that represents physiologic aging, is associated with age-related diseases including cancer and cardiovascular diseases. However, the associations between GAA and muscle mass and function are unknown. METHODS: We estimated measures of GAA in 1 118 Black and White participants from the Coronary Artery Risk Development in Young Adults (CARDIA) Study at exam years (Y) 15 (2000-2001) and 20 (2005-2006). Abdominal muscle composition was measured using CT scans at the Y25 (2010-2011) visit. We used multivariate regression models to examine associations of GAA estimates with muscle imaging measurements. RESULTS: In the CARDIA study, each 1-year higher GAA was associated with an average 1.1% (95% confidence interval [CI]: 0.6%, 1.5%) higher intermuscular adipose tissue (IMAT) volume for abdominal muscles. Each 1-year higher GAA was associated with an average -0.089 Hounsfield unit (HU; 95% CI: -0.146, -0.032) lower lean muscle attenuation and an average -0.049 HU (95% CI: -0.092, -0.007) lower IMAT attenuation for abdominal muscles. Stratified analyses showed that GAA was more strongly associated with higher abdominal muscle IMAT volume in females and significantly associated with lower lean muscle attenuation for White participants only. CONCLUSIONS: Higher GAA is associated with higher abdominal muscle IMAT volume and lower lean muscle attenuation in a midlife population.

A Proposed Pediatric Clinical Cardiovascular Health Reference Standard.

INTRODUCTION: Clinical cardiovascular health is a construct that includes 4 health factors-systolic and diastolic blood pressure, fasting glucose, total cholesterol, and body mass index-which together provide an evidence-based, more holistic view of cardiovascular health risk in adults than each component separately. Currently, no pediatric version of this construct exists. This study sought to develop sex-specific charts of clinical cardiovascular health for age to describe current patterns of clinical cardiovascular health throughout childhood. METHODS: Data were used from children and adolescents aged 8-19 years in six pooled childhood cohorts (19,261 participants, collected between 1972 and 2010) to create reference standards for fasting glucose and total cholesterol. Using the models for glucose and cholesterol as well as previously published reference standards for body mass index and blood pressure, clinical cardiovascular health charts were developed. All models were estimated using sex-specific random-effects linear regression, and modeling was performed during 2020-2022. RESULTS: Models were created to generate charts with smoothed means, percentiles, and standard deviations of clinical cardiovascular health for each year of childhood. For example, a 10-year-old girl with a body mass index of 16 kg/m2 (30th percentile), blood pressure of 100/60 mm Hg (46th/50th), glucose of 80 mg/dL (31st), and total cholesterol of 160 mg/dL (46th) (lower implies better) would have a clinical cardiovascular health percentile of 62 (higher implies better). CONCLUSIONS: Clinical cardiovascular health charts based on pediatric data offer a standardized approach to express clinical cardiovascular health as an age- and sex-standardized percentile for clinicians to assess cardiovascular health in childhood to consider preventive approaches at early ages and proactively optimize lifetime trajectories of cardiovascular health.

Discordance of patient-reported outcome measures with objectively assessed walking decline in peripheral artery disease.

OBJECTIVE: Among people with peripheral artery disease (PAD), perceived change in walking difficulty over time, compared with people without PAD, is unclear. Among people reporting no change in walking difficulty over time, differences in objectively measured change in walking performance between people with and without PAD are unknown. METHODS: A total of 1289 participants were included. Eight hundred seventy-four participants with PAD (aged 71.1 ± 9.1 years) were identified from noninvasive vascular laboratories and 415 without PAD (aged 69.9 ± 7.6 years) were identified from people with normal vascular laboratory testing or general medical practices in Chicago. The Walking Impairment Questionnaire and 6-minute walk were completed at baseline and 1-year follow-up. The Walking Impairment Questionnaire assessed perceived difficulty walking due to symptoms in the calves or buttocks on a Likert scale (range, 0-4). Symptom change was determined by comparing difficulty reported at 1-year follow-up to difficulty reported at baseline. RESULTS: At 1-year follow-up, 31.9% of participants with and 20.6% of participants without PAD reported walking difficulty that was improved (P < .01), whereas 41.2% vs 55%, respectively, reported walking difficulty that was unchanged (P < .01). Among all reporting no change in walking difficulty, participants with PAD declined in 6-minute walk, whereas participants without PAD improved (-10 vs +15 meters; mean difference, -25; 95% confidence interval, -38 to -13; P < .01). CONCLUSIONS: Most people with PAD reported improvement or no change in walking difficulty from calf or buttock symptoms at one-year follow-up. Among all participants who perceived stable walking ability, those with PAD had significant greater declines in objectively measured walking performance, compared with people without PAD.

Air quality and cancer risk in the All of Us Research Program.

INTRODUCTION: The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM2.5 exposure and cancer risks. MATERIALS AND METHODS: This work was performed on data from 409,876 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM2.5 exposure was retrieved from NASA's Earth Observing System Data and Information Center and assigned using participants' 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships. RESULTS: A total of 33,387 participants and 46,176 prevalent cancer cases were ascertained from participant EHR data, while 20,297 cases were ascertained from self-reported survey data from 18,133 participants; 9,502 cancer cases were captured in both the EHR and survey data. Average PM2.5 level from 2007 to 2016 was 8.90 µg/m3 (min 2.56, max 15.05). In analysis of cancer cases from EHR, an increased odds for breast cancer (OR 1.17, 95% CI 1.09-1.25), endometrial cancer (OR 1.33, 95% CI 1.09-1.62) and ovarian cancer (OR 1.20, 95% CI 1.01-1.42) in the 4th quartile of exposure compared to the 1st. In GAM, higher PM2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer. CONCLUSIONS: We found evidence of an association of PM2.5 with breast, ovarian, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM2.5 on risk of these cancers, warranting further investigation.

Robust and fast stochastic 4D flow vector-field signature technique for quantifying composite flow dynamics from 4D flow MRI: Application to left atrial flow in atrial fibrillation.

4D flow MRI is an emerging imaging modality that maps voxel-wise blood flow information as velocity vector fields that is acquired in 7-dimensional image volumes (3 spatial dimensions + 3 velocity directions + time). Blood flow in the cardiovascular system is often complex and composite involving multiple flow dynamics and patterns (e.g., vortex flow, jets, stagnating flow) that occur and interact simultaneously. The spectrum of such complex flow dynamics is embedded in the velocity vector field dynamics derived from 4D Flow MRI. However, current flow metrics cannot fully measure high-dimensional vector-field data and embedded complex composite flow data. Instead, these methods need to break down the vector-field data into secondary scalar fields of individual flow components using fluid dynamics operators. These methods are gradient-based and sensitive to data uncertainties, and only focus on individual flow components of the overall composite flow, therefore potentially underestimating the severity of overall flow changes associated with cardiovascular diseases. To address these limitations, in MICCAI 2021, we introduced a novel comprehensive stochastic 4D Flow vector-field signature technique that works directly on the entire spatiotemporal velocity vector field. This technique uses efficient stochastic gradient-free interrogation of multi-million flow vector-pairs per patient to derive the patient's unique flow profile of the complex composite flow alterations and in real-time processing. The signature technique's probabilistic gradient-free formulation should allow for highly robust quantification despite inherent errors in 4D flow MRI acquisitions. Here, we extend the application of the 4D flow vector-field signature technique to the left atrium to analyze complex composite flow changes in patients with atrial fibrillation. In 128 subjects, we performed extensive sensitivity testing and determined that the vector-field signature technique is highly robust to typical sources of data uncertainties in 4D flow MRI: degradation in spatiotemporal resolution, added Gaussian noise, and segmentation errors. We demonstrate the excellent generalizability of the stochastic convergence from the aorta to the left atrium and between different 4D Flow MRI acquisition protocols. We compare the robustness of our technique to existing advanced flow quantification metrics of kinetic energy, vorticity, and energy loss demonstrating a superior performance of up-to 14-fold. Our results show the potential diagnostic and clinical utility of our signature technique in identifying distinctly altered composite flow signatures in atrial fibrillation patients independent of existing flow metrics.

Body Mass Index, Adverse Pregnancy Outcomes, and Cardiovascular Disease Risk.

BACKGROUND: Obesity is a well-established risk factor for both adverse pregnancy outcomes (APOs) and cardiovascular disease (CVD). However, it is not known whether APOs are mediators or markers of the obesity-CVD relationship. This study examined the association between body mass index, APOs, and postpartum CVD risk factors. METHODS: The sample included adults from the nuMoM2b (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be) Heart Health Study who were enrolled in their first trimester (6 weeks-13 weeks 6 days gestation) from 8 United States sites. Participants had a follow-up visit at 3.7 years postpartum. APOs, which included hypertensive disorders of pregnancy, preterm birth, small-for-gestational-age birth, and gestational diabetes, were centrally adjudicated. Mediation analyses estimated the association between early pregnancy body mass index and postpartum CVD risk factors (hypertension, hyperlipidemia, and diabetes) and the proportion mediated by each APO adjusted for demographics and baseline health behaviors, psychosocial stressors, and CVD risk factor levels. RESULTS: Among 4216 participants enrolled, mean±SD maternal age was 27±6 years. Early pregnancy prevalence of overweight was 25%, and obesity was 22%. Hypertensive disorders of pregnancy occurred in 15%, preterm birth in 8%, small-for-gestational-age birth in 11%, and gestational diabetes in 4%. Early pregnancy obesity, compared with normal body mass index, was associated with significantly higher incidence of postpartum hypertension (adjusted odds ratio, 1.14 [95% CI, 1.10-1.18]), hyperlipidemia (1.11 [95% CI, 1.08-1.14]), and diabetes (1.03 [95% CI, 1.01-1.04]) even after adjustment for baseline CVD risk factor levels. APOs were associated with higher incidence of postpartum hypertension (1.97 [95% CI, 1.61-2.40]) and hyperlipidemia (1.31 [95% CI, 1.03-1.67]). Hypertensive disorders of pregnancy mediated a small proportion of the association between obesity and incident hypertension (13% [11%-15%]) and did not mediate associations with incident hyperlipidemia or diabetes. There was no significant mediation by preterm birth or small-for-gestational-age birth. CONCLUSIONS: There was heterogeneity across APO subtypes in their association with postpartum CVD risk factors and mediation of the association between early pregnancy obesity and postpartum CVD risk factors. However, only a small or nonsignificant proportion of the association between obesity and CVD risk factors was mediated by any of the APOs, suggesting APOs are a marker of prepregnancy CVD risk and not a predominant cause of postpartum CVD risk.

Identifying Patients With Peripheral Artery Disease Using the Electronic Health Record: A Pragmatic Approach.

BACKGROUND: Peripheral artery disease (PAD) is underdiagnosed due to poor patient and clinician awareness. Despite this, no widely accepted PAD screening is recommended. OBJECTIVES: The authors used machine learning to develop an automated risk stratification tool for identifying patients with a high likelihood of PAD. METHODS: Using data from the electronic health record (EHR), ankle-brachial indices (ABIs) were extracted for 3,298 patients. In addition to ABI, we extracted 60 other patient characteristics and used a random forest model to rank the features by association with ABI. The model identified several features independently correlated with PAD. We then built a logistic regression model to predict PAD status on a validation set of patients (n = 1,089), an external cohort of patients (n = 2,922), and a national database (n = 2,488). The model was compared to an age-based and random forest model. RESULTS: The model had an area under the curve (AUC) of 0.68 in the validation set. When evaluated on an external population using EHR data, it performed similarly with an AUC of 0.68. When evaluated on a national database, it had an AUC of 0.72. The model outperformed an age-based model (AUC: 0.62; P < 0.001). A random forest model with inclusion of all 60 features did not perform significantly better (AUC: 0.71; P = 0.31). CONCLUSIONS: Statistical techniques can be used to build models which identify individuals at high risk for PAD using information accessible from the EHR. Models such as this may allow large health care systems to efficiently identify patients that would benefit from aggressive preventive strategies or targeted-ABI screening.

Untargeted metabolomic analysis investigating links between unprocessed red meat intake and markers of inflammation.

BACKGROUND: Whether red meat consumption is associated with higher inflammation or confounded by increased adiposity remains unclear. Plasma metabolites capture the effects of diet after food is processed, digested, and absorbed, and correlate with markers of inflammation, so they can help clarify diet-health relationships. OBJECTIVE: To identify whether any metabolites associated with red meat intake are also associated with inflammation. METHODS: A cross-sectional analysis of observational data from older adults (52.84% women, mean age 63 ± 0.3 y) participating in the Multi-Ethnic Study of Atherosclerosis (MESA). Dietary intake was assessed by food-frequency questionnaire, alongside C-reactive protein (CRP), interleukin-2, interleukin-6, fibrinogen, homocysteine, and tumor necrosis factor alpha, and untargeted proton nuclear magnetic resonance (1H NMR) metabolomic features. Associations between these variables were examined using linear regression models, adjusted for demographic factors, lifestyle behaviors, and body mass index (BMI). RESULTS: In analyses that adjust for BMI, neither processed nor unprocessed forms of red meat were associated with any markers of inflammation (all P > 0.01). However, when adjusting for BMI, unprocessed red meat was inversely associated with spectral features representing the metabolite glutamine (sentinel hit: ß = -0.09 ± 0.02, P = 2.0 × 10-5), an amino acid which was also inversely associated with CRP level (ß = -0.11 ± 0.01, P = 3.3 × 10-10). CONCLUSIONS: Our analyses were unable to support a relationship between either processed or unprocessed red meat and inflammation, over and above any confounding by BMI. Glutamine, a plasma correlate of lower unprocessed red meat intake, was associated with lower CRP levels. The differences in diet-inflammation associations, compared with diet metabolite-inflammation associations, warrant further investigation to understand the extent that these arise from the following: 1) a reduction in measurement error with metabolite measures; 2) the extent that which factors other than unprocessed red meat intake contribute to glutamine levels; and 3) the ability of plasma metabolites to capture individual differences in how food intake is metabolized.

Metabolomic Profiling of Cholesterol Efflux Capacity in a Multiethnic Population: Insights From MESA.

BACKGROUND: Impaired cholesterol efflux capacity (CEC) is a novel lipid metabolism trait associated with atherosclerotic cardiovascular disease. Mechanisms underlying CEC variation are unknown. We evaluated associations of circulating metabolites with CEC to advance understanding of metabolic pathways involved in cholesterol efflux regulation. METHODS: Participants enrolled in the MESA (Multi-Ethnic Study of Atherosclerosis) who underwent nuclear magnetic resonance metabolome profiling and CEC measurement (N=3543) at baseline were included. Metabolite associations with CEC were evaluated using standard linear regression analyses. Repeated ElasticNet and multilayer perceptron regression were used to assess metabolite profile predictive performance for CEC. Features important for CEC prediction were identified using Shapley Additive Explanations values. RESULTS: Greater CEC was significantly associated with metabolite clusters composed of the largest-sized particle subclasses of VLDL (very-low-density lipoprotein) and HDL (high-density lipoprotein), as well as their constituent apo A1, apo A2, phospholipid, and cholesterol components (ß=0.072-0.081; P<0.001). Metabolite profiles had poor accuracy for predicting in vitro CEC in linear and nonlinear analyses (R2<0.02; Spearman ρ<0.18). The most important feature for CEC prediction was race, with Black participants having significantly lower CEC compared with other races. CONCLUSIONS: We identified independent associations among CEC, the largest-sized particle subclasses of VLDL and HDL, and their constituent apolipoproteins and lipids. A large proportion of variation in CEC remained unexplained by metabolites and traditional clinical risk factors, supporting further investigation into genomic, proteomic, and phospholipidomic determinants of CEC.