The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk ...factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).
The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.
Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.
The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk ...factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).
The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.
Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.
The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
Although obesity and cardiometabolic traits commonly overlap, underlying pathways remain incompletely defined. The association of metabolite profiles across multiple cardiometabolic traits may lend ...insights into the interaction of obesity and metabolic health. We sought to investigate metabolic signatures of obesity and related cardiometabolic traits in the community using broad-based metabolomic profiling.
We evaluated the association of 217 assayed metabolites and cross-sectional as well as longitudinal changes in cardiometabolic traits among 2,383 Framingham Offspring cohort participants. Body mass index (BMI) was associated with 69 of 217 metabolites (P<0.00023 for all), including aromatic (tyrosine, phenylalanine) and branched chain amino acids (valine, isoleucine, leucine). Additional metabolic pathways associated with BMI included the citric acid cycle (isocitrate, alpha-ketoglutarate, aconitate), the tryptophan pathway (kynurenine, kynurenic acid), and the urea cycle. There was considerable overlap in metabolite profiles between BMI, abdominal adiposity, insulin resistance IR and dyslipidemia, modest overlap of metabolite profiles between BMI and hyperglycemia, and little overlap with fasting glucose or elevated blood pressure. Metabolite profiles were associated with longitudinal changes in fasting glucose, but the involved metabolites (ornithine, 5-HIAA, aminoadipic acid, isoleucine, cotinine) were distinct from those associated with baseline glucose or other traits. Obesity status appeared to "modify" the association of 9 metabolites with IR. For example, bile acid metabolites were strongly associated with IR among obese but not lean individuals, whereas isoleucine had a stronger association with IR in lean individuals.
In this large-scale metabolite profiling study, body mass index was associated with a broad range of metabolic alterations. Metabolite profiling highlighted considerable overlap with abdominal adiposity, insulin resistance, and dyslipidemia, but not with fasting glucose or blood pressure traits.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Objectives The aim of this study was to examine the relation of galectin-3 (Gal-3), a marker of cardiac fibrosis, with incident heart failure (HF) in the community. Background Gal-3 is an emerging ...prognostic biomarker in HF, and experimental studies suggest that Gal-3 is an important mediator of cardiac fibrosis. Whether elevated Gal-3 concentrations precede the development of HF is unknown. Methods Gal-3 concentrations were measured in 3,353 participants in the Framingham Offspring Cohort (mean age 59 years; 53% women). The relation of Gal-3 to incident HF was assessed using proportional hazards regression. Results Gal-3 was associated with increased left ventricular mass in age-adjusted and sex-adjusted analyses (p = 0.001); this association was attenuated in multivariate analyses (p = 0.06). A total of 166 participants developed incident HF and 468 died during a mean follow-up period of 11.2 years. Gal-3 was associated with risk for incident HF (hazard ratio HR: 1.28 per 1 SD increase in log Gal-3; 95% confidence interval CI: 1.14 to 1.43; p < 0.0001) and remained significant after adjustment for clinical variables and B-type natriuretic peptide (HR: 1.23; 95% CI: 1.04 to 1.47; p = 0.02). Gal-3 was also associated with risk for all-cause mortality (multivariable-adjusted HR: 1.15; 95% CI: 1.04 to 1.28; p = 0.01). The addition of Gal-3 to clinical factors resulted in negligible changes to the C-statistic and minor improvements in net reclassification improvement. Conclusions Higher concentration of Gal-3, a marker of cardiac fibrosis, is associated with increased risk for incident HF and mortality. Future studies evaluating the role of Gal-3 in cardiac remodeling may provide further insights into the role of Gal-3 in the pathophysiology of HF.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The incidence and prevalence of heart failure with preserved ejection fraction (HFpEF) continue to rise in tandem with the increasing age and burdens of obesity, sedentariness, and cardiometabolic ...disorders. Despite recent advances in the understanding of its pathophysiological effects on the heart, lungs, and extracardiac tissues, and introduction of new, easily implemented approaches to diagnosis, HFpEF remains under-recognized in everyday practice. This under-recognition presents an even greater concern given the recent identification of highly effective pharmacologic-based and lifestyle-based treatments that can improve clinical status and reduce morbidity and mortality. HFpEF is a heterogenous syndrome and recent studies have suggested an important role for careful, pathophysiological-based phenotyping to improve patient characterization and to better individualize treatment. In this JACC Scientific Statement, we provide an in-depth and updated examination of the epidemiology, pathophysiology, diagnosis, and treatment of HFpEF.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Purpose Current staging systems for oral cavity cancers incorporate lymph node (LN) size and laterality, but place less weight on the total number of positive metastatic nodes. We investigated the ...independent impact of numerical metastatic LN burden on survival. Methods Adult patients with oral cavity squamous cell carcinoma undergoing upfront surgical resection for curative intent were identified in the National Cancer Data Base between 2004 and 2013. A neck dissection of a minimum of 10 LNs was required. Multivariable models were constructed to assess the association between the number of metastatic LNs and survival, adjusting for factors such as nodal size, laterality, extranodal extension, margin status, and adjuvant treatment. Results Overall, 14,554 patients met inclusion criteria (7,906 N0 patients; 6,648 node-positive patients). Mortality risk escalated continuously with increasing number of metastatic nodes without plateau, with the effect most pronounced with up to four LNs (HR, 1.34; 95% CI, 1.29 to 1.39; P < .001). Extranodal extension (HR, 1.41; 95% CI, 1.20 to 1.65; P < .001) and lower neck involvement (HR, 1.16; 95% CI, 1.06 to 1.27; P < .001) also predicted increased mortality. Increasing number of nodes examined was associated with improved survival, plateauing at 35 LNs (HR, 0.98; 95% CI, 0.98 to 0.99; P < .001). In multivariable models accounting for the number of metastatic nodes, contralateral LN involvement (N2c status) and LN size were not associated with mortality. A novel nodal staging system derived by recursive partitioning analysis exhibited greater concordance than the American Joint Committee on Cancer (8th edition) system. Conclusion The number of metastatic nodes is a critical predictor of oral cavity cancer mortality, eclipsing other features such as LN size and contralaterality in prognostic value. More robust incorporation of numerical metastatic LN burden may augment staging and better inform adjuvant treatment decisions.
Artificial intelligence (AI)-enabled analysis of 12-lead ECGs may facilitate efficient estimation of incident atrial fibrillation (AF) risk. However, it remains unclear whether AI provides meaningful ...and generalizable improvement in predictive accuracy beyond clinical risk factors for AF.
We trained a convolutional neural network (ECG-AI) to infer 5-year incident AF risk using 12-lead ECGs in patients receiving longitudinal primary care at Massachusetts General Hospital (MGH). We then fit 3 Cox proportional hazards models, composed of ECG-AI 5-year AF probability, CHARGE-AF clinical risk score (Cohorts for Heart and Aging in Genomic Epidemiology-Atrial Fibrillation), and terms for both ECG-AI and CHARGE-AF (CH-AI), respectively. We assessed model performance by calculating discrimination (area under the receiver operating characteristic curve) and calibration in an internal test set and 2 external test sets (Brigham and Women's Hospital BWH and UK Biobank). Models were recalibrated to estimate 2-year AF risk in the UK Biobank given limited available follow-up. We used saliency mapping to identify ECG features most influential on ECG-AI risk predictions and assessed correlation between ECG-AI and CHARGE-AF linear predictors.
The training set comprised 45 770 individuals (age 55±17 years, 53% women, 2171 AF events) and the test sets comprised 83 162 individuals (age 59±13 years, 56% women, 2424 AF events). Area under the receiver operating characteristic curve was comparable using CHARGE-AF (MGH, 0.802 95% CI, 0.767-0.836; BWH, 0.752 95% CI, 0.741-0.763; UK Biobank, 0.732 95% CI, 0.704-0.759) and ECG-AI (MGH, 0.823 95% CI, 0.790-0.856; BWH, 0.747 95% CI, 0.736-0.759; UK Biobank, 0.705 95% CI, 0.673-0.737). Area under the receiver operating characteristic curve was highest using CH-AI (MGH, 0.838 95% CI, 0.807 to 0.869; BWH, 0.777 95% CI, 0.766 to 0.788; UK Biobank, 0.746 95% CI, 0.716 to 0.776). Calibration error was low using ECG-AI (MGH, 0.0212; BWH, 0.0129; UK Biobank, 0.0035) and CH-AI (MGH, 0.012; BWH, 0.0108; UK Biobank, 0.0001). In saliency analyses, the ECG P-wave had the greatest influence on AI model predictions. ECG-AI and CHARGE-AF linear predictors were correlated (Pearson
: MGH, 0.61; BWH, 0.66; UK Biobank, 0.41).
AI-based analysis of 12-lead ECGs has similar predictive usefulness to a clinical risk factor model for incident AF and the approaches are complementary. ECG-AI may enable efficient quantification of future AF risk.
Galectin-3 is a versatile protein orchestrating several physiological and pathophysiological processes in the human body. In the last decade, considerable interest in galectin-3 has emerged because ...of its potential role as a biotarget. Galectin-3 is differentially expressed depending on the tissue type, however its expression can be induced under conditions of tissue injury or stress. Galectin-3 overexpression and secretion is associated with several diseases and is extensively studied in the context of fibrosis, heart failure, atherosclerosis and diabetes mellitus. Monomeric (extracellular) galectin-3 usually undergoes further "activation" which significantly broadens the spectrum of biological activity mainly by modifying its carbohydrate-binding properties. Self-interactions of this protein appear to play a crucial role in regulating the extracellular activities of this protein, however there is limited and controversial data on the mechanisms involved. We therefore summarize (recent) literature in this area and describe galectin-3 from a binding perspective providing novel insights into mechanisms by which galectin-3 is known to be "activated" and how such activation may be regulated in pathophysiological scenarios.
The discovery of novel and highly predictive biomarkers of cardiovascular disease (CVD) has the potential to improve risk-stratification methods and may be informative regarding biological pathways ...contributing to disease.
We used a discovery proteomic platform that targeted high-value proteins for CVD to ascertain 85 circulating protein biomarkers in 3523 Framingham Heart Study participants (mean age, 62 years; 53% women). Using multivariable-adjusted Cox models to account for clinical variables, we found 8 biomarkers associated with incident atherosclerotic CVD, 18 with incident heart failure, 38 with all-cause mortality, and 35 with CVD death (false discovery rate, q<0.05 for all;
-value ranges, 9.8×10
to 3.6×10
). Notably, a number of regulators of metabolic and adipocyte homeostasis were associated with cardiovascular events, including insulin-like growth factor 1 (IGF1), insulin-like growth factor binding protein 1 (IGFBP1), insulin-like growth factor binding protein 2 (IGFBP2), leptin, and adipsin. In a multimarker approach that accounted for clinical factors, growth differentiation factor 15 (GDF15) was associated with all outcomes. In addition, N-terminal pro-b-type natriuretic peptide, C-reactive protein, and leptin were associated with incident heart failure, and C-type lectin domain family 3 member B (CLEC3B; tetranectin), N-terminal pro-b-type natriuretic peptide, arabinogalactan protein 1 (AGP1), soluble receptor for advanced glycation end products (sRAGE), peripheral myelin protein 2 (PMP2), uncarboxylated matrix Gla protein (UCMGP), kallikrein B1 (KLKB1), IGFBP2, IGF1, leptin receptor, and cystatin-C were associated with all-cause mortality in a multimarker model.
We identified numerous protein biomarkers that predicted cardiovascular outcomes and all-cause mortality, including biomarkers representing regulators of metabolic homeostasis and inflammatory pathways. Further studies are needed to validate our findings and define clinical utility, with the ultimate goal of improving strategies for CVD prevention.
Identifying genetic variants associated with circulating protein concentrations (protein quantitative trait loci; pQTLs) and integrating them with variants from genome-wide association studies (GWAS) ...may illuminate the proteome's causal role in disease and bridge a knowledge gap regarding SNP-disease associations. We provide the results of GWAS of 71 high-value cardiovascular disease proteins in 6861 Framingham Heart Study participants and independent external replication. We report the mapping of over 16,000 pQTL variants and their functional relevance. We provide an integrated plasma protein-QTL database. Thirteen proteins harbor pQTL variants that match coronary disease-risk variants from GWAS or test causal for coronary disease by Mendelian randomization. Eight of these proteins predict new-onset cardiovascular disease events in Framingham participants. We demonstrate that identifying pQTLs, integrating them with GWAS results, employing Mendelian randomization, and prospectively testing protein-trait associations holds potential for elucidating causal genes, proteins, and pathways for cardiovascular disease and may identify targets for its prevention and treatment.
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