Scott, Christopher G.

Abstract Aims Right ventricular dysfunction (RVD) is an important determinant of functional status and survival in various diseases states. Data are sparse on the epidemiology and outcome of patients with severe RVD. This study examined the characteristics, aetiology, and survival of patients with severe RVD. Methods and results Retrospective study of consecutive patients with severe RVD diagnosed by transthoracic echocardiography (TTE) between 2011 and 2015 in a single tertiary referral institution. Patients with prior cardiac surgery, mechanical assist devices, and congenital heart disease were excluded. Primary endpoint was all-cause mortality. In 64 728 patients undergoing TTE, the prevalence of ≥mild RVD was 21%. This study focused on the cohort of 1299 (4%) patients with severe RVD; age 64 ± 16 years; 61% male. The most common causes of severe RVD were left-sided heart diseases (46%), pulmonary thromboembolic disease (18%), chronic lung disease/hypoxia (CLD; 17%), and pulmonary arterial hypertension (PAH; 11%). After 2 ± 2 years of follow-up, 701 deaths occurred, 66% within the first year of diagnosis. The overall probability of survival at 1- and 5 years for the entire cohort were 61% [95% confidence interval (CI) 58–64%] and 35% (95% CI 31–38%), respectively. In left-sided heart diseases, 1- and 5-year survival rates were 61% (95% CI 57–65%) and 33% (95% CI 28–37%), respectively; vs. 76% (95% CI 68–82%) and 50% (95% CI 40–59%) in PAH, vs. 71% (95% CI 64–76%) and 49% (95% CI 41–58%) in thromboembolic diseases, vs. 42% (95% CI 35–49%) and 8% (95% CI 4–15%) in CLD (log-rank P < 0.0001). Presence of ≥moderate tricuspid regurgitation portended worse survival in severe RVD. Conclusion One-year mortality of patients with severe RVD was high (∼40%) and dependent on the aetiology of RVD. Left-sided heart diseases is the most common cause of severe RVD but prognosis was worst in CLD.

Abstract Funding Acknowledgements Mayo Clinic Background Variability in Doppler signals is common in patients with atrial fibrillation (AF) and AF is common in low-gradient AS (LGAS). Presence of high single beat Doppler signals (peak velocity ≥4m/s or mean gradient ≥40mmHg) is not factored into decision-making in low-gradient aortic stenosis (LGAS). Objective Determine prevalence of at least one high Doppler signal in AF LGAS and its relationship to computed tomography aortic valve calcium score (AVCS) versus sinus rhythm (SR) high-gradient aortic stenosis (HGAS). Methods Consecutive patients with aortic valve area ≤1cm2 and left ventricular ejection fraction ≥50% during echo were identified (January 1, 2012-December 31, 2016). At least three consecutive Doppler signals were averaged in sinus rhythm (SR) and five in atrial fibrillation (AF). Results Of 1,854 patients, age 76± 11 years, male 52%, 301/1,854 (16%) were in AF and LGAS was present in 122/301 (41%). At least one high Doppler signal in AF LGAS was present in 43/122 (35%). AVCS within 1 year of echo was available for 36% of patient with SR HGAS and 34% of AS LGAS. Median AVCS was not different in SR HGAS 2424 (IQR 1623, 3445) vs AF LGAS with at least one high Doppler signal 2509 [IQR1547, 3119], p =0.10 AVCS threshold for severe AS (men >2000 women >1200) was met in 80% SR HGAS vs 86% AF LGAS with high signals. Conclusions High Doppler signals in AF LGAS are associated with high AVCS more frequently exceeding thresholds for severe AS. Single-beat high Doppler signals instead of the average correlate better with AVCS and classic HGAS.

Abstract Background In patients with hemodynamically-significant chronic aortic valve regurgitation (AR), the prognostic significance of routinely-measured diastolic blood pressure (DBP), resting heart rate (RHR) and physical examination signs of heart failure (HF), is unknown. Purpose To investigate the association of DBP, RHR and HF signs, with all-cause mortality. Methods This retrospective cohort study included all consecutive patients with moderately-severe or severe AR within a tertiary-referral center from 2006–2017. Patients with ≥moderate aortic stenosis and those with ≥moderate mitral stenosis/regurgitation were excluded. Results Of 820 patients (age 59±17 years; 82% men) with DBP 64±13mmHg and RHR 64±12bpm, followed for 5.5±3.5 years, 104 died under medical management and 400 underwent aortic valve surgery (AVS). In multivariable analysis, DBP (adjusted-hazard ratio [HR] 0.82 [0.68–0.98] p=0.031, per 10mmHg increase), RHR (adjusted HR 1.2 [1.01–1.41] p=0.034 per 10bpm increase), and any HF signs (adjusted HR 1.66 [1.04–2.61] p=0.032) were associated with all-cause death independently of demographics, comorbidities, and guideline-derived surgical triggers. Mortality increased in a J-curve fashion for DBP starting at 70 mmHg and peaking at 55 mmHg (Fig A,C), and in a linear fashion for RHR starting at 60bpm (Fig B, D). The association persisted after additional adjustment for medications, presence of hypertension and time-dependent AVS. A clinical score combining DBP, RHR and any HF signs increased the mortality risk-discrimination of demographics and comorbidities from 74% to 79% (p=0.01), and from 79% to 82% after addition of surgical triggers (p=0.04). Figure. Risk of death by DBP and RHR Conclusions In patients with AR, routinely-measured vital signs and physical examination are strongly associated with all-cause mortality; lower DBP, higher RHR and any HF signs are independent predictors of mortality, and provide incremental mortality risk-discriminating value to baseline demographics, comorbidities and guideline-derived surgical triggers. These findings represent a clinical paradigm shift and have guideline implications.

Abstract Background Anthracyclines are one of the most effective chemotherapeutic agents but can lead to a decline in cardiac function. Two-dimensional (2D) speckle tracking echocardiography derived strain can predict cancer therapeutics-related cardiac dysfunction (CTRCD). However, little is known about the role of three-dimensional (3D) strain imaging in this setting. Purpose To evaluate different methods of Left Ventricular Ejection Fraction (LVEF) and strain, and to identify the best strain parameter for the prediction of CTRCD in this group of patients during treatment with anthracycline based chemotherapy. Methods Patients with Hodgkin's or non-Hodgkin's lymphoma receiving anthracycline based chemotherapy were enrolled. 2D-and 3D echocardiography was performed at 3 time points: baseline, at the completion of chemotherapy and at 1 year. 2D- and 3D LVEF (2D Modified Quinones, M-mode, 2D Biplane, 3D Philips, 3D GE and 3D TomTec), peak systolic left and right ventricular longitudinal, radial and circumferential strain and strain rate were measured. CTRCD was defined as a decrease in LVEF >10% to an absolute value of <53%. Lin's Concordance Correlation Coefficient (CCC) was calculated to compare LVEF methods. ANOVA, uni and multivariate analysis was performed. Results A total of 130 patients (79 males, mean age 57±16 years) were enrolled; 104 non-Hodgkin.3D Philips and GE (CCC 0.88 [0.84, 0.92]), 3D Philips and biplane (CCC 0.84 [0.79, 0.89]), 3D Philips and Modified Quinones (CCC 0.86 [0.82, 091]) as well as 3D Philips and M-mode (CCC 0.77 [0.70, 0.85]) showed strong correlation for LVEF. 15 patients (12%) developed CTRCD. Mean cumulative anthracycline dose was 263±65 mg/m2. 2D and 3D global longitudinal and circumferential peak systolic strain, 2D global longitudinal systolic and early diastolic strain rate, 2D global early diastolic strain rate, 2D right ventricular longitudinal peak systolic strain and systolic strain rate, 2D global radial peak systolic strain and systolic strain rate measured at the completion of chemotherapy were independent predictors of the development of CTRCD at 1 year post-chemotherapy. The strongest predictors of CTRCD were 3D global longitudinal and circumferential strain either individually (area under the curve, 0.90 and 0.95 respectively) or combined (area under the curve, 0.95) at the completion of chemotherapy; a cutoff value of <-18% in 3D global longitudinal strain had a sensitivity of 82% and specificity of 99%, while for 3D global circumferential peak systolic strain of <-24% had a sensitivity of 82% and specificity of 95%. Conclusions To our knowledge this is the first prospective trial that shows that 3D EF correlates well with other EF methods and 3D strain predicts cardiac toxicity in this group of patients with a very good sensitivity and specificity. Acknowledgement/Funding Department of Cardiovascular Medicine-Mayo Clinic Rochester MN

Abstract Background Papillary fibroelastoma (PFE) is a rare benign cardiac tumor with embolic potential. It is most commonly found on cardiac valves but can also be present on non-valvular endocardial surfaces. We sought to better understand the average PFE growth and recurrence rates, and characteristics that might be associated with embolization. Purpose To examine growth and recurrence rates and factors associated with embolization in patients with pathology-proven PFE. Methods Pathology-proven PFEs from 279 patients were identified at a single center between January 1995 and December 2018,and those with at least two transesophageal echocardiograms (TEE) more than 30 days apart were analyzed (n=62). Medical records were retrospectively reviewed for clinical characteristics and outcomes. In addition, intra-operative TEEs were manually reviewed and compared to previous TEEs at our institution to estimate overall size, location, and average PFE growth rates. Results The TEEs from 62 patients with pathology-proven PFE (mean age 65±12 years, female 63%) were reviewed. PFE was discovered incidentally during cardiac surgery in 18% of patients. Most PFEs were located on the aortic valve (AV) (73%) followed by the mitral valve (MV) (16%). The majority of PFEs (71%) presented with a stalk versus a sessile configuration. Average maximal length for PFE (including stalk if present) on the AV was 8.5±3.3 mm, and on the MV 6.8±2.0 mm. The number of PFEs located in other locations was too small to be analyzed for growth. PFE growth varied depending on location and configuration. The PFE growth on the AV was an average increase of 0.47 mm/year, those on the MV was 0.115 mm/year. Valvular PFE was associated with significant functional valve abnormality in 15% of patients, and the abnormality was attributed to the PFE in 9% of patients. There were 25 patients (40%) who had a documented stroke/transient ischemic attack prior to PFE removal (46% located on AV, 44% on MV, 10% other locations). In addition, some patients had other documented embolic complications, such as myocardial infarction, amaurosis fugax, and peripheral embolization to the spleen and kidney. PFE size and location (up-/ downstream of the valve) were not predictive of cardiovascular thromboembolic events. At a median follow up of 2 years, PFEs recurred in the same location in 7.5% of the patients. Conclusion PFE is highly associated with thromboembolic events and seem to grow slowly, with an average growth rate of 0.47mm/year on AV and 0.115mm/year on MV. Growth rates for PFE have not been previously described. PFE can be safely excised with preservation of the native valve and recurs in 7.5% of patients, suggesting that close follow-up maybe warranted.

Background: Mitral stenosis frequently coexists in patients with severe aortic stenosis. Mitral stenosis severity evaluation is challenging in the setting of combined aortic stenosis and mitral stenosis because of hemodynamic interactions between the 2 valve lesions. The impact of aortic valve replacement (AVR) for severe aortic stenosis on mitral stenosis is unknown. This study aimed to assess the effect of AVR on mitral stenosis hemodynamics and the clinical outcomes of patients with severe aortic stenosis with and without mitral stenosis. Methods: We retrospectively investigated patients who underwent surgical AVR or transcatheter AVR for severe aortic stenosis from 2008 to 2015. Mean transmitral gradient by Doppler echocardiography ≥4 mm Hg was identified as mitral stenosis; patients were then stratified according to mitral valve area (MVA, by continuity equation) as >2.0 cm 2 or ≤2.0 cm 2 . MVA before and after AVR in patients with mitral stenosis were evaluated. Clinical outcomes of patients with and without mitral stenosis were compared using 1:2 matching for age, sex, left ventricular ejection fraction, method of AVR (surgical AVR versus transcatheter AVR) and year of AVR. Results: Of 190 patients with severe aortic stenosis and mitral stenosis (age 76±9 years, 42% men), 184 were matched with 362 with severe aortic stenosis without mitral stenosis. Among all mitral stenosis patients, the mean MVA increased after AVR by 0.26±0.59 cm 2 (from 2.00±0.50 to 2.26±0.62 cm 2 , P <0.01). MVA increased in 105 (55%) and remained unchanged in 34 (18%). Indexed stroke volume ≤45 mL/m 2 (odds ratio [OR] 2.40; 95% CI, 1.15–5.01; P =0.020) and transcatheter AVR (OR, 2.36; 95% CI, 1.17–4.77; P =0.017) were independently associated with increase in MVA. Of 107 with significant mitral stenosis (MVA ≤2.0 cm 2 ), MVA increased to >2.0 cm 2 after AVR in 52 (49%, pseudo mitral stenosis) and remained ≤2.0 cm 2 in 55 (51%, true mitral stenosis). During follow-up of median 2.9 (0.7–4.9) years, true mitral stenosis was an independent predictor of all-cause mortality (adjusted hazard ratio, 1.88; 95% CI, 1.20–2.94; P <0.01). Conclusions: MVA improved after AVR in nearly half of patients with severe aortic stenosis and mitral stenosis. MVA remained ≤2.0 cm 2 (true mitral stenosis) in nearly half of patients with severe aortic stenosis and significant mitral stenosis; this was associated with worse survival among patients undergoing AVR for severe aortic stenosis.

Background: Sex and age have long been known to affect the ECG. Several biologic variables and anatomic factors may contribute to sex and age-related differences on the ECG. We hypothesized that a convolutional neural network (CNN) could be trained through a process called deep learning to predict a person’s age and self-reported sex using only 12-lead ECG signals. We further hypothesized that discrepancies between CNN-predicted age and chronological age may serve as a physiological measure of health. Methods: We trained CNNs using 10-second samples of 12-lead ECG signals from 499 727 patients to predict sex and age. The networks were tested on a separate cohort of 275 056 patients. Subsequently, 100 randomly selected patients with multiple ECGs over the course of decades were identified to assess within-individual accuracy of CNN age estimation. Results: Of 275 056 patients tested, 52% were males and mean age was 58.6±16.2 years. For sex classification, the model obtained 90.4% classification accuracy with an area under the curve of 0.97 in the independent test data. Age was estimated as a continuous variable with an average error of 6.9±5.6 years (R-squared =0.7). Among 100 patients with multiple ECGs over the course of at least 2 decades of life, most patients (51%) had an average error between real age and CNN-predicted age of <7 years. Major factors seen among patients with a CNN-predicted age that exceeded chronologic age by >7 years included: low ejection fraction, hypertension, and coronary disease ( P <0.01). In the 27% of patients where correlation was >0.8 between CNN-predicted and chronologic age, no incident events occurred over follow-up (33±12 years). Conclusions: Applying artificial intelligence to the ECG allows prediction of patient sex and estimation of age. The ability of an artificial intelligence algorithm to determine physiological age, with further validation, may serve as a measure of overall health.

Abstract Background: Prospective validation of breast cancer risk models integrating classical risk factors and genetic variants is required for risk-stratified prevention and screening strategies. The objective of this study was to validate a breast cancer risk model integrating classical risk factors and a 313-variant polygenic risk score (PRS) in multiple prospective cohort studies, and to project five-year risk of breast cancer in six different countries. Methods: The study population included 7,529 cases and 230,103 controls from 14 prospective cohort studies in Australia, Germany, the Netherlands, Sweden, UK, and USA. We used the Individualized Coherent Absolute Risk Estimator (iCARE) tool for risk model building, validation, and risk projection. Expected five-year risk of invasive or in situ breast cancer was compared to observed risk, overall and within deciles of expected risk using goodness of fit statistics. We evaluated calibration of the relative risk through meta-analysis across cohorts, and of the absolute risk within each cohort. Model discrimination was evaluated using the area under the curve (AUC), and percentages of women crossing risk thresholds. Projections of five-year risk distributions were estimated for women of European ancestry aged 50-70 years in the general populations of these six countries. Results: Analysis showed overall good calibration of the integrated iCARE-based model relative risk for both women younger than 50 years (χ2=14.9, P=0.09) and aged 50 years or older (χ2=14.6, P=0.10), with a small overestimation of risk for women in the highest decile of expected risk (RR = 3.5 expected vs 2.3 (95% CI 1.6 to 3.2) observed for women &lt;50 years; and 2.8 expected vs 2.3 (95% CI 2.0 to 2.7) observed for women 50+ years). The age-adjusted AUCs for the integrated model were 63.1 (95% CI 60.9 to 65.3) and 62.9 (95% CI 61.8 to 64.0), for the two age groups respectively. The calibration of absolute risk showed substantial variation across cohorts, particularly for the older group, but had no systematic bias. Model based projections in the general populations showed that compared to the population average, women in the 1st and 99th percentiles of the integrated risk score had relative risks 0.19 and 3.56 respectively. The proportion of women of European ancestry aged 50-70 years with a five-year risk greater than 3% (threshold for consideration of risk-lowering drugs by U.S. Preventive Services Task Force) ranged from 7.1% in Germany to 18.2% in the US, which corresponds to ~5.5 million women in the US. Conclusions: Five-year risk predictions from a model with classical risk factors and PRS are well calibrated and provide substantial risk stratification across multiple cohorts in six different countries. Further studies are needed to evaluate the clinical utility of the validated model for risk stratified screening and prevention of breast cancer. Citation Format: Parichoy Pal Choudhury, Amber Wilcox, Chi Gao, Brian Carter, Anika Husing, Mark Brook, Mikael Eriksson, Kara Martin, Chris Scott, Min Shi, Thomas Ahearn, Michael Jones, Nick Orr, Minouk Schoemaker, Kamila Czene, Jenny Chang-Claude, Jacques Simard, Doug Easton, Marjanka K. Schmidt, Dale Sandler, Clarice R. Weinberg, Celine Vachon, Roger Milne, Per Hall, Anthony Swerdlow, Rudolph Kaaks, Myrto Barrdahl, Mia Gaudet, Antonis Antoniou, Peter Kraft, Montserrat Garcia-Closas, Nilanjan Chatterjee. Validation of breast cancer risk model incorporating classical risk factors and polygenic risk scores in 14 prospective cohort studies in 6 countries [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 962.

Abstract Background: High mammographic breast density is a strong, well-established breast cancer risk factor. A recent study found increased expression of stem cell markers in the areas of high breast density, but, whether stem cells may explain high breast cancer risk due to high breast density is unknown. We investigated the association between breast density and the risk of breast cancer by the status of stem cell markers CD44, CD24, and ALDH1A1 in the tumor. Methods: We included 223 postmenopausal women with primary invasive or in-situ breast cancer and 399 age-matched controls from Mayo Clinic Mammography Study. Percent breast density, absolute dense area and non-dense area were assessed using computer-assisted thresholding technique. Immunohistochemical analysis of the markers was performed on tumor tissue microarrays according to a standard protocol with commercial antibodies. Cases with positive staining (≥1% positively stained cells) on one or more cores were considered marker-positive. We used polychotomous logistic regression to quantify the associations of breast density measures with breast cancer risk by the status of each of the markers. Heterogeneity tests were conducted to compare the differences in associations by marker-defined tumor subtypes. Results: Of the 223 cancers in the study, 182 (82%) were positive for CD44, 83 (37%) for CD24 and 52 (23%) for ALDH1A1. Associations of percent density were not significantly different across any of the marker-defined subtypes (density 51%+ vs. 11-25%: OR=2.83, 95% CI 1.49-5.37 for CD44+ vs. OR=1.87, 95% CI 0.47-7.51 for CD44-, p-heterogeneity=0.66; OR=2.80, 95% CI 1.27-6.18 for CD24+ vs. OR=2.44, 95% CI 1.14-5.22 for CD24-, p-heterogeneity=0.61; OR=3.04, 95% CI 1.14-8.10 for ALDH1A1+ vs. OR=2.57. 95% CI 1.30-5.08 for ALDH1A1-, p-heterogeneity=0.94). Positive associations of absolute dense area and inverse associations of non-dense area with breast cancer risk were similar across marker-defined subtypes. Similar associations of breast density measures with breast cancer were seen when cancer subtypes were defined using combined marker expression status (none, one positive marker, or two and more positive markers). Conclusions: We found no evidence of differential associations of breast density measures with breast cancer risk by the status of stem cell markers. However, our power was limited and further studies in larger study populations are warranted to confirm these associations in a larger sample. Citation Format: Lusine Yaghjyan, Ashwini Esnakula, Christopher Scott, Akemi Wijayabahu, Matthew Jensen, Celine Vachon. Associations of mammographic breast density with breast stem cell marker-defined breast cancer subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 592.