Douglass, Erika J.

Abstract Background Cardiovascular disease (CVD) has been identified as a major threat to maternal health in the US and UK with cardiomyopathy being one of the most common acquired CVD in the pregnant and postpartum period. Diagnosing cardiomyopathy in pregnancy is challenging due to an overlap of cardiovascular symptoms with normal pregnancy symptoms. Purpose The purpose of this study was to evaluate the effectiveness of an ECG based deep learning model in identifying cardiomyopathy among pregnant and postpartum women. Methods We utilized an ECG based deep learning model to detect cardiomyopathy in a cohort of pregnant or postpartum women seen at multiple hospital sites. Model performance was evaluated using area under the curve (AUC), accuracy, sensitivity, and specificity. We compared the diagnostic probabilities of the deep learning model with natriuretic peptides and a multivariable model consisting of demographic and clinical parameters. Results 1,807 women were included. 7%, 10% and 13% had LVEF ≤35%, <45% and <50% respectively. The ECG based deep learning model identified cardiomyopathy with an AUC of 0.92 for left ventricular ejection fraction (LVEF) ≤35%, 0.89 for LVEF <45% and 0.87 for LVEF <50%. For LVEF ≤35%, AUC was higher in Black (0.95) and Hispanic (0.98) women compared to white (0.91). Natriuretic peptides and the multivariable model had AUCs of 0.85 and 0.72 respectively. Conclusions A deep learning model effectively identifies cardiomyopathy in pregnant or postpartum women, outperforms natriuretic peptides and traditional clinical parameters with the potential to become a powerful initial screening tool for cardiomyopathy in the obstetric care setting. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): This study was made possible using resources supported by the Mayo Clinic Women's Health Research Center and the Mayo Clinic Building Interdisciplinary Research Careers in Women's Health (BIRCWH) Program funded by the National Institutes of Health (NIH), grant number K12 HD065987. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Abstract Aims Cardiovascular disease is a major threat to maternal health, with cardiomyopathy being among the most common acquired cardiovascular diseases during pregnancy and the postpartum period. The aim of our study was to evaluate the effectiveness of an electrocardiogram (ECG)-based deep learning model in identifying cardiomyopathy during pregnancy and the postpartum period. Methods and results We used an ECG-based deep learning model to detect cardiomyopathy in a cohort of women who were pregnant or in the postpartum period seen at Mayo Clinic. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. We compared the diagnostic probabilities of the deep learning model with natriuretic peptides and a multivariable model consisting of demographic and clinical parameters. The study cohort included 1807 women; 7%, 10%, and 13% had left ventricular ejection fraction (LVEF) of 35% or less, <45%, and <50%, respectively. The ECG-based deep learning model identified cardiomyopathy with AUCs of 0.92 (LVEF ≤ 35%), 0.89 (LVEF < 45%), and 0.87 (LVEF < 50%). For LVEF of 35% or less, AUC was higher in Black (0.95) and Hispanic (0.98) women compared to White (0.91). Natriuretic peptides and the multivariable model had AUCs of 0.85 to 0.86 and 0.72, respectively. Conclusions An ECG-based deep learning model effectively identifies cardiomyopathy during pregnancy and the postpartum period and outperforms natriuretic peptides and traditional clinical parameters with the potential to become a powerful initial screening tool for cardiomyopathy in the obstetric care setting.

e13002 Background: Despite improvement in survival in breast cancer patients from advanced therapies, rates of chemotherapy-induced cardiotoxicity manifesting as a decline in left ventricular ejection fraction (LVEF) have offset some of these benefits in patients receiving anthracycline-based chemotherapy followed by trastuzumab. Results suggesting clinical biomarkers predict cardiotoxicity are inconsistent. Recently, expression of angiotensin II type 1 receptor (ATR1) and endothelin 1 (ET1) has shown to play a role in breast tumor growth. We sought to evaluate whether the presence of ATR1 and ET1 in breast cancer tissue using immunohistochemistry (IHC) and qRT-PCR can predict chemotherapy-induced cardiotoxicity. Methods: We hypothesized that elevated expression of ATR1 and ET1 in tumor tissue is associated with chemotherapy-induced cardiotoxicity (LVEF < 50%) compared to tissue from controls. Preliminarily, 34 paraffin-embedded breast tissue specimens from women with breast cancer treated with anthracycline-based chemotherapy and trastuzumab were retrieved for analysis. IHC and qRT-PCR for expression of ATR1 and ET1 was performed on all specimens. Results: We found that ET1 expression was significantly increased in patients with an LVEF < 50%. In addition, we noted the lower the LVEF, the higher the ET1 expression (p = 0.03). We also found patients with a change in LVEF of greater than 10% had more ET1 expression compared to those without a change in LVEF (p = 0.05). We did not find a significant relationship between ATR1 and LVEF. Conclusions: Increased ET1 expression in breast tumor tissue may predict cardiotoxicity. Our findings may aid in future research using novel biomarkers to predict breast cancer patients at risk for developing chemotherapy-induced cardiotoxicity. In addition, targeted therapies to these biomarkers may potentially help prevent the development of cardiotoxicity.

BACKGROUNDAndrogenic alopecia (AGA) is a common hair loss disorder. Studies have demonstrated successful treatment with platelet-rich plasma (PRP) in men, but studies in women are few.OBJECTIVETo evaluate PRP in the treatment of AGA in women, compared with topical minoxidil.MATERIALS AND METHODSTwenty women with AGA received topical minoxidil for 12 weeks and injectable PRP for 12 weeks in a randomized crossover design with an 8-week washout between treatments. Standardized TrichoScan analysis and quality-of-life questionnaires were assessed at baseline and 12-week follow-up for each treatment.RESULTSAfter PRP, significant increases from baseline to Week 12 in TrichoScan analysis hair count (p= .002) and vellus hair density (p= .009) occurred. However, minoxidil resulted in significant increases in hair count (p< .001), vellus hair density (p= .03), terminal hair density (p= .004), and cumulative thickness (p= .004). Several quality of life responses improved from baseline to Week 12 after PRP treatment, whereas no improvements were noted after minoxidil.CONCLUSIONPlatelet-rich plasma is an effective treatment for hair regrowth in female AGA, although not as effective as minoxidil. However, the improved quality of life responses after PRP, but not minoxidil, suggest a potential overall greater degree of satisfaction with PRP.LEVELS OF EVIDENCEI.CLINICAL TRIAL REGISTRATIONNCT03488108.

An estimated 1 billion people worldwide have deficient or insufficient levels of vitamin D (VitD). Considerable evidence indicates that VitD deficiency is associated with an increased risk of autoimmune and cardiovascular disease (CVD), yet it remains unclear whether low VitD is simply a biomarker or has a true pathologic role. In this study we examined how sex differences in VitD influences various CVDs. We found that patients with CVD had significantly lower VitD than healthy controls (no ICD9/10 codes). In myocarditis patients low VitD correlated to poor ejection fraction (EF) in women with myocarditis (p=0.02), but high VitD correlated with low EF in men (p=0.04). In VDR knockout mice we found that VDR decreased myocarditis in females (p=2E-8) but increased inflammation in males (p=0.03) with an increase in total immune cells (p=0.02), CD3, CD4 and CD8 T cells (p=0.04), and the inflammasome in females. VDR altered Treg (p=0.04), mast cells (p=0.04) and cytokine profiles in males. Additionally, sera VitD levels were significantly higher in WT male mice with myocarditis compared to females. Our findings in VDR mice indicate that VitD/VDR reduces myocarditis in females, but increases disease in males. These data suggest that VitD sufficiency may increase inflammation in men, while VitD deficiency may make disease worse in women. These findings suggest that Vitamin D may have a role in the pathogenesis of inflammatory and cardiovascular disease.

Background Myocarditis is an important cause of acute and chronic heart failure. Men with myocarditis have worse recovery and an increased need for transplantation compared with women, but the reason for the sex difference remains unclear. Elevated sera soluble (s) ST 2 predicts mortality from acute and chronic heart failure, but has not been studied in myocarditis patients. Methods and Results Adults with a diagnosis of clinically suspected myocarditis (n=303, 78% male) were identified according to the 2013 European Society of Cardiology position statement. Sera sST 2 levels were examined by ELISA in humans and mice and correlated with heart function according to sex and age. Sera sST 2 levels were higher in healthy men ( P =8×10 −6 ) and men with myocarditis ( P =0.004) compared with women. sST 2 levels were elevated in patients with myocarditis and New York Heart Association class III ‐ IV heart failure ( P =0.002), predominantly in men ( P =0.0003). Sera sST 2 levels were associated with New York Heart Association class in men with myocarditis who were ≤50 years old ( r =0.231, P =0.0006), but not in women ( r =0.172, P =0.57). Sera sST 2 levels were also significantly higher in male mice with myocarditis ( P =0.005) where levels were associated with cardiac inflammation. Gonadectomy with hormone replacement showed that testosterone ( P <0.001), but not estradiol ( P =0.32), increased sera sST 2 levels in male mice with myocarditis. Conclusions We show in a well‐characterized subset of heart failure patients with clinically suspected and biopsy‐confirmed myocarditis that elevated sera sST 2 is associated with an increased risk of heart failure based on New York Heart Association class in men ≤50 years old.