Background - Identification of systolic heart failure among patients presenting to the emergency department (ED) with acute dyspnea is challenging. The reasons for dyspnea are often multifactorial. A focused physical evaluation and diagnostic testing can lack sensitivity and specificity. The objective of this study was to assess the accuracy of an artificial intelligence-enabled electrocardiogram (AI-ECG) to identify patients presenting with dyspnea who have left ventricular systolic dysfunction (LVSD). Methods - We retrospectively applied a validated AI-ECG algorithm for the identification of LVSD (defined as left ventricular ejection fraction ≤ 35%) to a cohort of patients aged ≥ 18 years who were evaluated in the ED at a Mayo Clinic site with dyspnea. Patients were included if they had at least one standard 12-lead ECG acquired on the date of the ED visit and an echocardiogram performed within 30 days of presentation. Patients with prior LVSD were excluded. We assessed the model performance using area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Results - A total of 1,606 patients were included. Median time from ECG to echocardiogram was 1 day (Q1: 1, Q3: 2). The AI-ECG algorithm identified LVSD with an AUC of 0.89 (95% CI: 0.86 - 0.91) and accuracy of 85.9%. Sensitivity, specificity, negative predictive value, and positive predictive value were 74%, 87%, 97%, and 40%, respectively. To identify an ejection fraction < 50%, the AUC, accuracy, sensitivity, and specificity were 0.85 (95% CI: 0.83 - 0.88), 86%, 63%, and 91%, respectively. NT-Pro BNP alone at a cut-off of >800 identified LVSD with an AUC of 0.80 (95% CI: 0.76 - 0.84). Conclusions - The ECG is an inexpensive, ubiquitous, painless test which can be quickly obtained in the ED. It effectively identifies LVSD in selected patients presenting to the ED with dyspnea when analyzed with AI and outperforms NT-Pro BNP.

Background The United States implemented mandatory folic acid fortification of enriched cereal grains in 1998. Although several studies have documented the resulting decrease in anemia and folate deficiency, to our knowledge, no one has determined the prevalence of folate-deficiency anemia after fortification. Objective We determined the prevalence of folate deficiency and folate-deficiency anemia within a sample of the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. Design The REGARDS cohort is a prospective cohort of 30,239 black and white participants living in the contiguous United States. We measured serum folate concentrations in a random sample of 1546 REGARDS participants aged ≥50 y with baseline hemoglobin and red blood cell mean corpuscular volume measurements. Folate deficiency was defined as a serum folate concentration <6.6 nmol/L (<3.0 ng/mL), and anemia was defined as a hemoglobin concentration <13 g/dL in men and <12 g/dL in nonpregnant women (WHO criteria). Folate-deficiency anemia was defined as the presence of both folate deficiency and anemia. Results The mean hemoglobin concentration was 13.6 g/dL, and 15.9% of subjects had anemia. The median serum folate concentration was 34.2 nmol/L (15.1 ng/mL), and only 2 of 1546 participants 0.1%) were folate deficient. Both subjects were African American women with markedly elevated C-reactive protein concentrations, macrocytosis, and normal serum cobalamin concentrations; only one subject was anemic. Overall, the prevalence of folate-deficiency anemia was <0.1% (1 of 1546 subjects). Conclusion Our data suggest that, after mandatory folic acid fortification, the prevalence of folate-deficiency anemia is nearly nonexistent in a community-dwelling population in the United States.

Most women of reproductive age who receive a valproate prescription do not have epilepsy. Valproate prescriptions did not decline, despite increasing knowledge of its teratogenicity. Reducing valproate use among women of reproductive age, especially among those who use the drug for psychiatric indications, would prevent birth defects and cognitive deficits.

Background The 2013 American College of Cardiology/American Heart Association guidelines recommend statins for adults ≤75 years who have clinical atherosclerotic cardiovascular disease (ASCVD) (IA) and for adults aged 40 – 75 with diabetes and LDL-C 70-189 mg/dl (IA). Our aim was to estimate the prevalence and likelihood of statin use among selected statin benefit groups. Methods Using data from the National Health and Nutrition Examination Survey (NHANES) 2011 – 2012, we examined 5,319 adults ≥20 years. We estimated weighted frequencies and prevalence of statin use for adults with diabetes and dyslipidemia (or LDL ≥70 mg/dl), defined as statin benefit group 1 (SBG1); and for adults with ASCVD, defined as statin benefit group 2 (SBG2). We constructed a logistic regression model to estimate the odds of statin use in SBG1. Results Overall, an estimated 38.6 million Americans are on a statin. In adjusted models, uninsured and Hispanic adults were less likely to be on a statin compared to white adults. 59.5% (95% CI: 53.0 – 66.1) of all adults in SBG1, 58.8% (95% CI: 51.5 – 66.1) of adults aged 40 – 75 in SBG1 and 63.5% (95% CI: 55.6 – 71.4) of all adults in SBG2 were on a statin. Conclusion Although the prevalence of statin use has increased over time, Hispanic ethnicity and lack of insurance remain a barrier to statin use. Black-white racial disparities were not significant. Our study provides a baseline estimate of statin use in the non-institutionalized population just prior to the introduction of the new guidelines and provides a reference for evaluating the impact of the new guidelines on statin utilization.

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Our findings suggest a relationship between maternal anxiety and reduced exclusivity and continuation of breastfeeding. Maternal anxiety should be actively monitored and managed appropriately in the postpartum period to support optimal breastfeeding practices.

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular disease development and outcomes, the need for more effective approaches to screening for risk factors and phenotypes in women is ever urgent. Public health surveillance and health care delivery systems now continuously generate massive amounts of data that could be leveraged to enable both screening of cardiovascular risk and implementation of tailored preventive interventions across a woman’s life span. However, health care providers, clinical guidelines committees, and health policy experts are not yet sufficiently equipped to optimize the collection of data on women, use or interpret these data, or develop approaches to targeting interventions. Therefore, we provide a broad overview of the key opportunities for cardiovascular screening in women while highlighting the potential applications of artificial intelligence along with digital technologies and tools.

The BBT reduced 30-day, all-cause and heart failure-related readmission rate but not 1-year mortality in patients having HFrEF with concurrent cocaine use.