Physical Activity, Cardiovascular Status, Mortality, and Prediabetes in Hispanic and Non-Hispanic Adults.

Importance: Data are limited on the association of physical activity (PA) with incident cardiovascular disease (CVD) and mortality in prediabetes, especially in racial and ethnic minority groups, including Hispanic and Latino populations. Objective: To determine the association of PA with incident CVD and mortality by prediabetes status among Hispanic or Latino and non-Hispanic adults. Design, Setting, and Participants: This cohort study included data from 2 cohorts of adults with prediabetes or normoglycemia who were free of CVD at baseline visit: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) from baseline examination through 2017, with median (IQR) follow-up of 7.8 (7.2-8.5) years, and the Framingham Heart Study (FHS) with non-Hispanic participants from index examination through 2019, with median (IQR) follow-up of 9.6 (8.1-10.7) years. Analyses were conducted between September 1, 2022, and January 10, 2024. Exposure: The primary exposure was baseline accelerometry-measured moderate to vigorous PA, insufficient vs sufficient to meet 2018 Physical Activity Guidelines for Americans (PAG) in both cohorts; additional accelerometer-measured exposures in HCHS/SOL were steps per day, sedentary behavior, and counts per min. Main Outcomes and Measures: The outcome was a composite of incident CVD or all-cause mortality, whichever came first. Results: This cohort study included 13 223 participants: from HCHS/SOL, there were 9456 adults (all self-identified Hispanic or Latino ethnicity; survey-adjusted mean [SD] age, 38.3 [13.9] years, unweighted counts 5673 (60.0%) female; 4882 [51.6%] with normoglycemia; 4574 [48.4%] with prediabetes), and from FHS there were 3767 adults (3623 [96.2%] non-Hispanic and 140 [3.7%] Hispanic or Latino ethnicity, with 4 [0.1%] participants missing ethnicity; mean [SD] age, 54.2 [13.6] years; 2128 (56.5%) female; 2739 [72.7%] with normoglycemia; 1028 [27.3%] with prediabetes). Not meeting PAG was associated with higher risk of the composite outcome among participants with normoglycemia (vs PAG met; hazard ratio [HR], 1.85 [95% CI, 1.12-3.06]), but not among participants with prediabetes (HR, 1.07 [95% CI, 0.72-1.58]). For HCHS/SOL, no statistically significant association was found between the composite outcome and other PA metrics, although estimated HRs tended to be higher for lower activity in the normoglycemia group but not for the prediabetes group (eg, for steps less than vs at least 7000 per day, the HR was 1.58 [95% CI, 0.85-2.93] for normoglycemia vs 1.08 [95% CI 0.67-1.74] for prediabetes). While there was also no association in HCHS/SOL between the composite outcome and sedentary behavior, results were similar in the prediabetes group (HR per 30 minutes per day of sedentary behavior, 1.05 [95% CI 0.99-1.12]) and in the normoglycemia group (HR, 1.07 [95% CI 0.98-1.16]). Conclusions and Relevance: In this cohort study of US Hispanic or Latino and non-Hispanic adults, lower moderate to vigorous PA levels were associated with CVD or mortality among participants with normoglycemia but not participants with prediabetes. Adults with prediabetes may benefit from reducing sedentary behavior and improving multiple lifestyle factors beyond improving moderate to vigorous PA alone.

A general framework for developing computable clinical phenotype algorithms.

OBJECTIVE: Present a general framework providing high-level guidance to developers of computable algorithms for identifying patients with specific clinical conditions (phenotypes) through a variety of approaches, including but not limited to machine learning and natural language processing methods to incorporate rich electronic health record data. MATERIALS/METHODS: Drawing on extensive prior phenotyping experiences and insights derived from three algorithm development projects conducted specifically for this purpose, our team with expertise in clinical medicine, statistics, informatics, pharmacoepidemiology, and healthcare data science methods conceptualized stages of development and corresponding sets of principles, strategies, and practical guidelines for improving the algorithm development process. RESULTS: We propose five stages of algorithm development and corresponding principles, strategies, and guidelines: 1) assessing fitness-for-purpose, 2) creating gold standard data, 3) feature engineering, 4) model development, and 5) model evaluation. DISCUSSION/CONCLUSION: This framework is intended to provide practical guidance and serve as a basis for future elaboration and extension.

High Throughput Plasma Proteomics and Risk of Heart Failure and Frailty in Late Life.

Importance: Heart failure (HF) and frailty frequently coexist and may share a common pathobiology, although the underlying mechanisms remain unclear. Understanding these mechanisms may provide guidance for preventing and treating both conditions. Objective: To identify shared pathways between incident HF and frailty in late life using large-scale proteomics. Design, Setting, and Participants: In this cohort study, 4877 aptamers (Somascan v4) were measured among participants in the community-based longitudinal Atherosclerosis Risk In Communities (ARIC) cohort study at visit 3 (V3; 1993-1995; n = 10 638) and at visit 5 (V5; 2011-2013; n = 3908). Analyses were externally replicated among 3189 participants in the Cardiovascular Health Study (CHS). Data analysis was conducted from February 2022 to June 2023. Exposures: Protein aptamers, measured at study V3 and V5. Main Outcomes and Measures: Outcomes assessed included incident HF hospitalization after V3 and after V5, prevalent frailty at V5, and incident frailty between V5 and visit 6 (V6; 2016-2017; n = 4131). Frailty was assessed using the Fried criteria. Analyses were adjusted for age, gender, race, field center, hypertension, diabetes, smoking status, body mass index, estimated glomerular filtration rate, prevalent coronary heart disease, prevalent atrial fibrillation, and history of myocardial infarction. Mendelian randomization (MR) analysis was performed to assess potential causal effects of candidate proteins on HF and frailty. Results: A total of 4877 protein aptamers were measured among 10 638 participants at V3 (mean [SD] age, 60 [6] years; 4886 [46%] men). Overall, 286 proteins were associated with incident HF after V3 (822 events; P < 1.0 × 10-5), 83 of which were also associated with incident after V5 (336 events; P < 1.7 × 10-4). Among HF-free participants at V5 (n = 3908; mean [SD] age, 75 [5] years; 1861 [42%] men), 48 of 83 HF-associated proteins were associated with prevalent frailty (223 cases; P < 6.0 × 10-4), 18 of which were also associated with incident frailty at V6 (152 cases; P < 1.0 × 10-3). These proteins enriched fibrosis and inflammation pathways and demonstrated stronger associations with incident HF with preserved ejection fraction (HFpEF) than HF with reduced ejection fraction. All 18 proteins were associated with both prevalent frailty and incident HF in CHS. MR identified potential causal effects of several proteins on frailty and HF. Conclusions and Relevance: In this study, the proteins associated with risk of HF and frailty enrich for pathways related to inflammation and fibrosis as well as risk of HFpEF. Several of these proteins could potentially contribute to the shared pathophysiology of frailty and HF.

Current use of estrogen-containing oral contraceptives or hormone therapy and risk of COVID-19 infection and hospitalization: a population-based cohort study.

This population-based cohort study evaluated the association between current use of oral contraceptives (OC) among women under 50 years (n=306,541), and hormone therapy (HT) among women aged 50 or older (n=323,203), and COVID-19 infection and hospitalization. Current OC/HT use was recorded monthly using prescription dispensing data. COVID-19 infections were identified March 2020-February 2021. COVID-19 infection and hospitalization were identified through diagnosis codes and laboratory tests. Weighted generalized estimating equations models estimated multivariable-adjusted odds ratios (aORs) for COVID-19 infection associated with time-varying OC/HT use. Among women with COVID-19, logistic regression models evaluated OC/HT use and COVID-19 hospitalization. Over 12 months, 11,727 (3.8%) women <50 years and 8,661 (2.7%) women ≥50 years experienced COVID-19 infections. There was no evidence of an association between OC use and infection (aOR=1.05; 95%CI: 0.97, 1.12). There was a modest association between HT use and infection (aOR=1.19; 95%CI: 1.03, 1.38). Women using OC had a 39% lower risk of hospitalization (aOR=0.61; 95%CI: 0.38, 1.00), but there was no association of HT use with hospitalization (aOR=0.89; 95%CI: 0.51, 1.53). These findings do not suggest a meaningfully greater risk of COVID-19 infection associated with OC or HT use. OC use may be associated with lower COVID-19 hospitalization risk.

Racism-related stress and mental health among black women living in Los Angeles County, California: A comparison of postpartum mood and anxiety disorder screening scales.

PURPOSE: To assess Black women's exposure to and appraisal of racism-related stress during the postpartum period and to distinguish its impact on three indicators of postpartum mood and anxiety disorders (PMADs) symptoms. METHODS: Data from the Black Mothers' Mental Wellness Study (N = 231) and linear regression models estimated the associations between racism-related stress and the PMAD indicators: 3-item Edinburgh Postnatal Depression Scale (EPDS-3), 8-item Patient Health Questionnaire (PHQ-8), and PHQ-15. RESULTS: The majority of participants (80.5%, N = 186) experienced racism a few times a year or more, of which 37.1% (N = 69) were bothered somewhat and 19.3% (N = 36) a lot. Racism-related stress, income, level of education, and history of mental health diagnosis explained greater variance in PMAD symptoms as measured by the PHQ-8 score (R2 = 0.58, p = < 0.001) compared to the EPDS-3 (R2 = 0.46, p = < 0.001) or the PHQ-15 (R2 = 0.14, p = 0.035). CONCLUSIONS: Racism is a stressor for Black women living in Los Angeles County, California. Racism-related stress and emotional expression of PMAD symptoms were salient to the postpartum mental health of the Black women in this study. Findings from this study suggest that the PHQ-8 should be used to assess how racism impacts Black women's postpartum mental health.

Large-Scale Proteomics Identifies Novel Biomarkers and Circulating Risk Factors for Aortic Stenosis.

BACKGROUND: Limited data exist regarding risk factors for aortic stenosis (AS). The plasma proteome is a promising phenotype for discovery of novel biomarkers and potentially causative mechanisms. OBJECTIVES: The aim of this study was to discover novel biomarkers with potentially causal associations with AS. METHODS: We measured 4,877 plasma proteins (SomaScan aptamer-affinity assay) among ARIC (Atherosclerosis Risk In Communities) study participants in mid-life (visit 3 [V3]; n = 11,430; age 60 ± 6 years) and in late-life (V5; n = 4,899; age 76 ± 5 years). We identified proteins cross-sectionally associated with aortic valve (AV) peak velocity (AVmax) and dimensionless index by echocardiography at V5 and with incident AV-related hospitalization after V3 with the use of multivariable linear and Cox proportional hazard regression. We assessed associations of candidate proteins with changes in AVmax over 6 years and with AV calcification with the use of cardiac computed tomography, replicated analysis in an independent sample, performed Mendelian randomization, and evaluated gene expression in explanted human AV tissue. RESULTS: Fifty-two proteins cross-sectionally were associated with AVmax and dimensionless index at V5 and with risk of incident AV-related hospitalization after V3. Among 3,413 participants in the Cardiovascular Health Study, 6 of those proteins were significantly associated with adjudicated moderate or severe AS, including matrix metalloproteinase 12 (MMP12), complement C1q tumor necrosis factor-related protein 1 (C1QTNF1), and growth differentiation factor-15. MMP12 was also associated with greater increase in AVmax over 6 years, greater degree of AV calcification, and greater expression in calcific compared with normal or fibrotic AV tissue. C1QTNF1 had consistent potential causal effects on both AS and AVmax according to Mendelian randomization analysis. CONCLUSIONS: These findings identify MMP12 as a potential novel circulating biomarker of AS risk and C1QTNF1 as a new putative target to prevent AS progression.

Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol.

Importance: Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified. Objective: To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (≥190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults. Design, Setting, and Participants: A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023. Exposures: LDL-C, cumulative past LDL-C, FH variant status. Main Outcomes and Measures: Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults. Results: Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3%) and in 33 individuals with severely elevated LDL-C (2.5%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95% CI, 1.4-6.0) and 2.6 (95% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant. Conclusions and Relevance: In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

Heart rate fragmentation and brain MRI markers of small vessel disease in MESA.

INTRODUCTION: Heart rate (HR) fragmentation indices quantify breakdown of HR regulation and are associated with atrial fibrillation and cognitive impairment. Their association with brain magnetic resonance imaging (MRI) markers of small vessel disease is unexplored. METHODS: In 606 stroke-free participants of the Multi-Ethnic Study of Atherosclerosis (mean age 67), HR fragmentation indices including percentage of inflection points (PIP) were derived from sleep study recordings. We examined PIP in relation to white matter hyperintensity (WMH) volume, total white matter fractional anisotropy (FA), and microbleeds from 3-Tesla brain MRI completed 7 years later. RESULTS: In adjusted analyses, higher PIP was associated with greater WMH volume (14% per standard deviation [SD], 95% confidence interval [CI]: 2, 27%, P = 0.02) and lower WM FA (-0.09 SD per SD, 95% CI: -0.16, -0.01, P = 0.03). DISCUSSION: HR fragmentation was associated with small vessel disease. HR fragmentation can be measured automatically from ambulatory electrocardiogram devices and may be useful as a biomarker of vascular brain injury.

A proteomic analysis of atrial fibrillation in a prospective longitudinal cohort (AGES-Reykjavik study).

AIMS: Atrial fibrillation (AF) is associated with high risk of comorbidities and mortality. Our aim was to examine causal and predictive relationships between 4137 serum proteins and incident AF in the prospective population-based Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) study. METHODS AND RESULTS: The study included 4765 participants, of whom 1172 developed AF. Cox proportional hazards regression models were fitted for 4137 baseline protein measurements adjusting for known risk factors. Protein associations were tested for replication in the Cardiovascular Health Study (CHS). Causal relationships were examined in a bidirectional, two-sample Mendelian randomization analysis. The time-dependent area under the receiver operating characteristic curve (AUC)-statistic was examined as protein levels and an AF-polygenic risk score (PRS) were added to clinical risk models. The proteomic signature of incident AF consisted of 76 proteins, of which 63 (83%) were novel and 29 (38%) were replicated in CHS. The signature included both N-terminal prohormone of brain natriuretic peptide (NT-proBNP)-dependent (e.g. CHST15, ATP1B1, and SVEP1) and independent components (e.g. ASPN, AKR1B, and LAMA1/LAMB1/LAMC1). Nine causal candidates were identified (TAGLN, WARS, CHST15, CHMP3, COL15A1, DUSP13, MANBA, QSOX2, and SRL). The reverse causal analysis suggested that most AF-associated proteins were affected by the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide improved the prediction of incident AF events close to baseline with further improvements gained by the AF-PRS at all time points. CONCLUSION: The AF proteomic signature includes biologically relevant proteins, some of which may be causal. It mainly reflects an NT-proBNP-dependent consequence of the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide is a promising marker for incident AF in the short term, but risk assessment incorporating a PRS may improve long-term risk assessment.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

A Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies.

Context: Both type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight. Objective: We examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Methods: We constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D. Results: The T1D PS was not associated with T2D both in CHARGE (P = .15) and in the MGB Biobank (P = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, P = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, P = .03) in CHARGE T2D cases but not with other outcomes. Conclusion: In large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study.

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.

Electrocardiographic markers of atrial cardiomyopathy and risk of heart failure in the multi-ethnic study of atherosclerosis (MESA) cohort.

Background: The association of electrocardiographic (ECG) markers of atrial cardiomyopathy with heart failure (HF) and its subtypes is unclear. Methods: This analysis included 6,754 participants free of clinical cardiovascular disease (CVD), including atrial fibrillation (AF), from the Multi-Ethnic Study of Atherosclerosis. Five ECG markers of atrial cardiomyopathy (P-wave terminal force in V1 [PTFV1], deep-terminal negativity in V1 [DTNV1], P-wave duration [PWD], P-wave axis [PWA], advanced intra-atrial block [aIAB]) were derived from digitally recorded electrocardiograms. Incident HF events through 2018 were centrally adjudicated. An ejection fraction (EF) of 50% at the time of HF was used to classify HF as HF with reduced EF (HFrEF), HF with preserved EF (HFpEF), or unclassified HF. Cox proportional hazard models were used to examine the associations of markers of atrial cardiomyopathy with HF. The Lunn-McNeil method was used to compare the associations in HFrEF vs. HFpEF. Results: 413 HF events occurred over a median follow-up of 16 years. In adjusted models, abnormal PTFV1 (HR (95%CI): 1.56(1.15-2.13), abnormal PWA (HR (95%CI):1.60(1.16-2.22), aIAB (HR (95%CI):2.62(1.47-4.69), DTNPV1 (HR (95%CI): 2.99(1.63-7.33), and abnormal PWD (HR (95%CI): 1.33(1.02-1.73), were associated with increased HF risk. These associations persisted after further adjustments for intercurrent AF events. No significant differences in the strength of association of each ECG predictor with HFrEF and HFpEF were noted. Conclusions: Atrial cardiomyopathy defined by ECG markers is associated with HF, with no differences in the strength of association between HFrEF and HFpEF. Markers of atrial Cardiomyopathy may help identify individuals at risk of developing HF.

Plasma Proteomic Associations With Incident Ischemic Stroke in Older Adults: The Cardiovascular Health Study.

BACKGROUND AND OBJECTIVES: Plasma proteomics may elucidate novel insights into the pathophysiology of ischemic stroke (IS), identify biomarkers of IS risk, and guide development of nascent prevention strategies. We evaluated the relationship between the plasma proteome and IS risk in the population-based Cardiovascular Health Study (CHS). METHODS: Eligible CHS participants were free of prevalent stroke and underwent quantification of 1,298 plasma proteins using the aptamer-based SOMAScan assay platform from the 1992-1993 study visit. Multivariable Cox proportional hazards regression was used to evaluate associations between a 1-SD increase in the log2-transformed estimated plasma protein concentrations and incident IS, adjusting for demographics, IS risk factors, and estimated glomerular filtration rate. For proteins independently associated with incident IS, a secondary stratified analysis evaluated associations in subgroups defined by sex and race. Exploratory analyses evaluated plasma proteomic associations with cardioembolic and noncardioembolic IS and proteins associated with IS risk in participants with left atrial dysfunction but without atrial fibrillation. RESULTS: Of 2,983 eligible participants, the mean age was 74.3 (±4.8) years, 61.2% were women, and 15.4% were Black. Over a median follow-up of 12.6 years, 450 participants experienced an incident IS. N-terminal probrain natriuretic peptide (NTproBNP, adjusted HR 1.37, 95% CI 1.23-1.53, p = 2.08 × 10-08) and macrophage metalloelastase (MMP12, adjusted HR 1.30, 95% CI 1.16-1.45, p = 4.55 × 10-06) were independently associated with IS risk. These 2 associations were similar in men and women and in Black and non-Black participants. In exploratory analyses, NTproBNP was independently associated with incident cardioembolic IS, E-selectin with incident noncardioembolic IS, and secreted frizzled-related protein 1 with IS risk in participants with left atrial dysfunction. DISCUSSION: In a cohort of older adults, NTproBNP and MMP12 were independently associated with IS risk. We identified plasma proteomic determinants of incident cardioembolic and noncardioembolic IS and found a novel protein associated with IS risk in those with left atrial dysfunction.

Association Between Diabetes Severity and Risks of COVID-19 Infection and Outcomes.

BACKGROUND: Little is known about whether diabetes increases the risk of COVID-19 infection and whether measures of diabetes severity are related to COVID-19 outcomes. OBJECTIVE: Investigate diabetes severity measures as potential risk factors for COVID-19 infection and COVID-19 outcomes. DESIGN, PARTICIPANTS, MEASURES: In integrated healthcare systems in Colorado, Oregon, and Washington, we identified a cohort of adults on February 29, 2020 (n = 1,086,918) and conducted follow-up through February 28, 2021. Electronic health data and death certificates were used to identify markers of diabetes severity, covariates, and outcomes. Outcomes were COVID-19 infection (positive nucleic acid antigen test, COVID-19 hospitalization, or COVID-19 death) and severe COVID-19 (invasive mechanical ventilation or COVID-19 death). Individuals with diabetes (n = 142,340) and categories of diabetes severity measures were compared with a referent group with no diabetes (n = 944,578), adjusting for demographic variables, neighborhood deprivation index, body mass index, and comorbidities. RESULTS: Of 30,935 patients with COVID-19 infection, 996 met the criteria for severe COVID-19. Type 1 (odds ratio [OR] 1.41, 95% CI 1.27-1.57) and type 2 diabetes (OR 1.27, 95% CI 1.23-1.31) were associated with increased risk of COVID-19 infection. Insulin treatment was associated with greater COVID-19 infection risk (OR 1.43, 95% CI 1.34-1.52) than treatment with non-insulin drugs (OR 1.26, 95% 1.20-1.33) or no treatment (OR 1.24; 1.18-1.29). The relationship between glycemic control and COVID-19 infection risk was dose-dependent: from an OR of 1.21 (95% CI 1.15-1.26) for hemoglobin A1c (HbA1c) < 7% to an OR of 1.62 (95% CI 1.51-1.75) for HbA1c ≥ 9%. Risk factors for severe COVID-19 were type 1 diabetes (OR 2.87; 95% CI 1.99-4.15), type 2 diabetes (OR 1.80; 95% CI 1.55-2.09), insulin treatment (OR 2.65; 95% CI 2.13-3.28), and HbA1c ≥ 9% (OR 2.61; 95% CI 1.94-3.52). CONCLUSIONS: Diabetes and greater diabetes severity were associated with increased risks of COVID-19 infection and worse COVID-19 outcomes.

Factors Associated with Postpartum Maternal Functioning in Black Women: A Secondary Analysis.

In the United States, 29−44% of Black women experience postpartum depressive symptoms (PDS), yet few are properly identified and/or connected to mental care services. The purpose of this secondary analysis was to examine the relationship between maternal functioning and clinical variables (PDS, maternal−infant attachment), racial variable (Black racial identity types­low race salience, assimilated and miseducated, self-hating, anti-White, multiculturalist, and conflicted), and sociodemographic characteristics (relationship status, education, insurance, childbirth type). A total of 116 women living in the southern United States were included in the analysis. Multivariate analyses revealed that Black racial identity (p = 0.02), PDS (p < 0.0001), maternal−infant attachment (p < 0.0001), and educational level (p = 0.03) were independently associated with maternal functioning. This work provides new evidence regarding the role of various clinical and racial factors on Black postpartum women's adjustment to motherhood. This analysis also adds to the growing body of evidence of reliability for the BIMF in Black postpartum women.

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning.

We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance of automated health-care claims-based algorithms to identify anaphylaxis events using data on 516 patients with outpatient, emergency department, or inpatient anaphylaxis diagnosis codes during 2015-2019 in 2 integrated health-care institutions in the Northwest United States. We used one site's manually reviewed gold-standard outcomes data for model development and the other's for external validation based on cross-validated area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and sensitivity. In the development site 154 (64%) of 239 potential events met adjudication criteria for anaphylaxis compared with 180 (65%) of 277 in the validation site. Logistic regression models using only structured claims data achieved a cross-validated AUC of 0.58 (95% CI: 0.54, 0.63). Machine learning improved cross-validated AUC to 0.62 (0.58, 0.66); incorporating NLP-derived covariates further increased cross-validated AUCs to 0.70 (0.66, 0.75) in development and 0.67 (0.63, 0.71) in external validation data. A classification threshold with cross-validated PPV of 79% and cross-validated sensitivity of 66% in development data had cross-validated PPV of 78% and cross-validated sensitivity of 56% in external data. Machine learning and NLP-derived data improved identification of validated anaphylaxis events.