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Background-Women receive less evidence-based medical care than men and have higher rates of death after acute myocardial infarction (AMI). It is unclear whether efforts undertaken to improve AMI care have mitigated these sex disparities in the current era.

The management of low-risk patients presenting to emergency departments is a common and challenging clinical problem entailing 8 million emergency department visits annually. Although a majority of these patients do not have a life-threatening condition, the clinician must distinguish between those who require urgent treatment of a serious problem and those with more benign entities who do not require admission. Inadvertent discharge of patients with acute coronary syndrome from the emergency department is associated with increased mortality and liability, whereas inappropriate admission of patients without serious disease is neither indicated nor cost-effective. Clinical judgment and basic clinical tools (history, physical examination, and electrocardiogram) remain primary in meeting this challenge and affording early identification of low-risk patients with chest pain. Additionally, established and newer diagnostic methods have extended clinicians' diagnostic capacity in this setting. Low-risk patients presenting with chest pain are increasingly managed in chest pain units in which accelerated diagnostic protocols are performed, comprising serial electrocardiograms and cardiac injury markers to exclude acute coronary syndrome. Patients with negative findings usually complete the accelerated diagnostic protocol with a confirmatory test to exclude ischemia. This is typically an exercise treadmill test or a cardiac imaging study if the exercise treadmill test is not applicable. Rest myocardial perfusion imaging has assumed an important role in this setting. Computed tomography coronary angiography has also shown promise in this setting. A negative accelerated diagnostic protocol evaluation allows discharge, whereas patients with positive findings are admitted. This approach has been found to be safe, accurate, and cost-effective in low-risk patients presenting with chest pain.

W orldwide, cardiovascular disease (CVD) is the largest single cause of death among women, accounting for one third of all deaths (1). In many countries, including the United States, more women than men die every year of CVD, a fact largely unknown by physicians (2,3). The public health impact of CVD in women is not related solely to the mortality rate, given that advances in science and medicine allow many women to survive heart disease. For example, in the United States, 38.2 million women (34%) are living with CVD, and the population at risk is even larger (2). In China, a country with a population of approximately 1.3 billion, the agestandardized prevalence rates of dyslipidemia and hypertension in women 35 to 74 years of age are 53% and 25%, respectively, which underscores the enormity of CVD as a †Representation does not imply endorsement by the American College of Physicians. Please see the online version of this document for data supplements. The American Heart Association makes every effort to avoid any actual or potential conflicts of interest that may arise as a result of an outside relationship or a personal, professional, or business interest of a member of the writing panel. Specifically, all members of the writing group are required to complete and submit a Disclosure Questionnaire showing all such relationships that might be perceived as real or potential conflicts of interest.

Objective To identify novel biomarkers through metabolomic profiles that distinguish metabolically well (MW) from metabolically unwell (MUW) individuals, independent of body mass index (BMI). Materials/Methods This study was conducted as part of the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) project. Individuals from 3 cohorts were classified as lean (BMI<25 kg/m2), overweight (BMI≥25 kg/m2, BMI<30 kg/m2) or obese (BMI≥30 kg/m2). Cardiometabolic abnormalities were defined as: (1) impaired fasting glucose (≥100mg/dL and ≤126mg/dL); (2) hypertension; (3) triglycerides ≥150 mg/dL; (4) HDL-C <40 mg/dL in men, <50 mg/dL in women); and (5) insulin resistance (calculated Homeostatic Model Assessment (HOMA-IR) index of >5.13). MW individuals were defined as having <2 cardiometabolic abnormalities and MUW individuals had ≥two cardiometabolic abnormalities. Targeted profiling of 55 metabolites used mass-spectroscopy-based methods. Principal components analysis (PCA) was used to reduce the large number of correlated metabolites into clusters of fewer uncorrelated factors. Results Of 1,872 individuals, 410 were lean, 610 were overweight, and 852 were obese. Of lean individuals, 67% were categorized as MUW, whereas 80% of overweight and 87% of obese individuals were MUW. PCA-derived factors with levels that differed the most between MW and MUW groups were factors 4 (branched chain amino acids [BCAA]) [p<.0001], 8 (various metabolites) [p<.0001], and 9 (C4/Ci4, C3, C5 acylcarnitines) [p<.0001] and 10 (amino acids) [p<.0002]. Further, Factor 4, distinguishes MW from MUW individuals independent of BMI. Conclusion BCAA and related metabolites are promising biomarkers that may aid in understanding cardiometabolic health independent of BMI category.

Background-Prior studies have demonstrated an inconsistent association between patients' arrival time for acute myocardial infarction (AMI) and their subsequent medical care and outcomes. Methods and Results-Using a contemporary national clinical registry, we examined differences in medical care and in-hospital mortality among AMI patients admitted during regular hours (weekdays 7 AM to 7 PM) versus off-hours (weekends, holidays, and 7 PM to 7 AM weeknights).

Background-The molecular pathophysiology of coronary artery disease (CAD) includes cytokine release and a localized inflammatory response within the vessel wall. The extent to which CAD and its severity is reflected by gene expression in circulating cells is unknown. Key Words: gene expression Ⅲ coronary disease Ⅲ blood, peripheral Ⅲ atherosclerosis Ⅲ leukocytes Ⅲ polymerase chain reaction Ⅲ stenosis C oronary artery disease (CAD) and sequelae of atherosclerotic disease such as stroke and myocardial infarction are the largest source of morbidity and mortality in the developed world. The risk of developing CAD events over time can be estimated with clinical factors and family history, as in the Framingham Risk Score. 1 For patients with suspicious clinical histories, extant coronary disease may be diagnosed by indirect methods, including nuclear perfusion imaging and computed tomography angiography, but coronary angiography remains the "gold standard." These tests have drawbacks, including radiation exposure, contrast agent allergy, nephrotoxicity, and, in the case of coronary angiography, invasiveness of the procedure. Therefore, the development of a blood test that reliably identified patients with CAD would have diagnostic utility. Methods and Results-From Editorial see p 7 Clinical Perspective see p 38The cellular and molecular basis of atherosclerotic plaque development has a systemic inflammatory component involving primarily monocytes/macrophages and CD4 ϩ T cells. 2,3 Oxidized lipids initiate the process with subsequent responses by endothelial, vascular smooth muscle cells, and circulating cells. Peripheral-blood studies have identified gene expression signatures that are correlated with the presence of systemic inflammatory and immune-mediated disorders, as well as cardiovascular diseases, 4 suggesting that such an approach might be useful for CAD. However, although investigators have identified profiles for atherosclerosis directly from arterial wall samples in murine models and human atheroma samples, 5-9 it is unclear whether such localized processes are detectable or their severity reflected in the peripheral circulation. As a first step, we sought to identify genes for which expression levels distinguished patients with and without significant coronary artery stenosis. We approached this problem by microarray analysis on an angiographically defined patient cohort to identify a set of discriminatory genes. We then replicated these results using real-time polymerase chain reaction (RT-PCR) on 2 addi-