Scott, Christopher G.

Introduction: While left ventricular assist devise (LVAD) support improves the prognosis of end-stage heart failure (HF) patients, the long-term outcomes remains suboptimal. Improved outcomes may occur with organ protection including reverse myocardial remodeling. Cenderitide (CDNP) is a Mayo engineered designer natriuretic peptide (NP) that co-activates particulate guanylyl cyclase A and B receptors and functions via the second messenger cGMP. We reported a NP deficient state in the heart with LVAD support which lays the rationale for NP replacement therapy with Cenderitide which has cardiorenal protective actions in experimental HF. We sought to determine if Cenderitide co-therapy would be safe and activate cGMP in patients with LVAD support. Hypothesis: Acute single dose of subcutaneous (SQ) Cenderitide will be safe and activate cGMP in patients with LVAD support. Methods: Stable HF patients with LVAD support (Heartmate II, all males) were enrolled in a cross-over design comparing SQ placebo and low (Low-C, 5 ug/kg, n=8) or high dose (High-C, 10 ug/kg, n=8) Cenderitide (Capricor Therapeutics) administration. Vital signs, plasma C(D)NP, cGMP, Aldosterone (Aldo), and NT-proBNP levels were measured before or after drug administration over 24 hours. All parameters in Cenderitide group were adjusted by those in placebo. Results: Both Low-C and High-C group demonstrated significantly increased plasma C(D)NP and cGMP levels for 2 hours after drug injection and those in High-C group showed more prolonged and higher increases than Low-C group. Mean arterial pressure (MAP) in Low-C did not show any changes but in High-C group tended to be lower for 18 hours but this was not significant. Plasma Aldo and NT-proBNP levels in Low-C group did not show any change but those in High-C group tended to be lower after drug injection s similar to the change in MAP. No adverse events were observed in the study. Conclusions: SQ Cenderitide was successfully absorbed, activated cGMP and well tolerated in patients with LVAD support. High dose Cenderitide may have cardiac unloading effects suggested by decreases in NT-proBNP. Further clinical trial for efficacy is warranted to clarify cardiorenal protective effects of Cenderitide in the LVAD population to improve outcomes.

Background Patients with peripheral artery disease are at increased risk for major adverse cardiac events, major adverse limb events, and all‐cause death. Developing tools capable of identifying those patients with peripheral artery disease at greatest risk for major adverse events is the first step for outcome prevention. This study aimed to determine whether computer‐assisted analysis of a resting Doppler waveform using deep neural networks can accurately identify patients with peripheral artery disease at greatest risk for adverse outcome events. Methods and Results Consecutive patients (April 1, 2015, to December 31, 2020) undergoing ankle–brachial index testing were included. Patients were randomly allocated to training, validation, and testing subsets (60%/20%/20%). Deep neural networks were trained on resting posterior tibial arterial Doppler waveforms to predict major adverse cardiac events, major adverse limb events, and all‐cause death at 5 years. Patients were then analyzed in groups based on the quartiles of each prediction score in the training set. Among 11 384 total patients, 10 437 patients met study inclusion criteria (mean age, 65.8±14.8 years; 40.6% women). The test subset included 2084 patients. During 5 years of follow‐up, there were 447 deaths, 585 major adverse cardiac events, and 161 MALE events. After adjusting for age, sex, and Charlson comorbidity index, deep neural network analysis of the posterior tibial artery waveform provided independent prediction of death (hazard ratio [HR], 2.44 [95% CI, 1.78–3.34]), major adverse cardiac events (HR, 1.97 [95% CI, 1.49–2.61]), and major adverse limb events (HR, 11.03 [95% CI, 5.43–22.39]) at 5 years. Conclusions An artificial intelligence–enabled analysis of Doppler arterial waveforms enables identification of major adverse outcomes among patients with peripheral artery disease, which may promote early adoption and adherence of risk factor modification.

Background: Diagnosis of heart failure with preserved ejection fraction (HFpEF) is challenging due to non-diagnostic imaging outputs and discordant clinical features. Using only a single videoclip from a standard transthoracic echocardiogram (TTE), we developed an artificial intelligence (AI) model to differentiate patients with HFpEF from those without HFpEF. In a separate test population, we assessed the model’s ability to predict cardiac mortality. Methods: A 3-dimensional convolutional neural network was developed and trained on apical 4-chamber videoclips to classify patients with HFpEF (cases) versus without HFpEF (controls). Overall and cardiac mortality were obtained from the National Death Index. Results: The model was independently tested in 646 cases and 638 controls from 8 centers in 4 states. Sensitivity (87.8%; 84.5-90.9%) and specificity (81.9%; 78.2-85.6%) were high and sustained in various subgroups, including increased left atrial volume index, average E/e’ ≥15, and pulmonary artery systolic pressure >35 mm Hg. During follow-up (median [IQR] 3.4 [1.7-6.5] years), 540 patients died. There were 135 cardiac deaths attributable to heart failure (47%), coronary artery disease (41%), valve disease (4%), arrhythmia (4%), and others (5%). Compared to a negative output, all-cause mortality was higher in patients with a positive (HR 2.9 [2.4-3.5]) or uncertain output (HR 1.8 [1.2-2.5]), and cardiac mortality (Figure) was also higher in patients with a positive (HR 7.7 [4.5-13.3]) or uncertain output (HR 3.4 [1.4-8.1]). Cardiac mortality differences according to AI model prediction remained after age adjustment (positive: HR 5.9 [3.3-10.4], p<0.001; uncertain: HR 2.8 [1.2-6.8], p=0.02). Conclusion: A novel AI model to detect HFpEF based on a single routinely acquired TTE videoclip also identifies those at increased risk of cardiac mortality.

Introduction: Common genetic variation has been linked to an increased risk of developing dilated cardiomyopathy (DCM). However, the phenotypic profile, outcomes, and biological mechanisms by which such genetic background may predispose individuals to DCM are still unknown. Hypothesis: The primary objectives of this study were to develop a DCM polygenic risk score (PRS) based on prior case control-DCM GWAS and to apply this PRS to a well clinical characterized general population. Methods: The DCM-PRS was derived from 13 DCM risk alleles that were assayed in an unselected cohort (n=1897) of unrelated Olmsted County residents age >45 years who did not have a history of heart failure (HF) or CM and underwent physical examination, echocardiography, and blood analyses. Results: The entire population was equally divided into quartiles based on the DCM-PRS. No significant differences were present in terms of age (median 62 years) and sex (48% male). However, a significant correlation was detected between the DCM-PRS and left ventricle ejection fraction (LVEF) (Beta: -2.68, p<0.001), LV end-systolic diameter (Beta: 0.22, p<0.001), and LV end-diastolic diameter (Beta: 0.14, p=0.01). During a follow-up of 16 years (IQR: 15-17), 47 subjects developed DCM. Using a 3:1 non-DCM vs DCM matched cohort, a logistic regression analysis, found a significant correlation between median DCM-PRS and DCM development [OR=2.27 (1.06, 4.85), p=0.03]. However, there was no association between the DCM-PRS and HF biomarkers (aldosterone, natriuretic peptides, ST2, Galectin-3). Conclusions: DCM-PRS correlates with decreased LVEF, increased LV dimensions, and DCM development in a general population without significant differences in baseline clinical features. The absence of correlation between the DCM-PRS and available HF biomarkers suggests that this genetic background affects LV traits and DCM development independent of these biological mechanisms.

Introduction: Isolated functional tricuspid regurgitation (FTR) in the absence of structural heart disease may develop secondary to elevation in left heart pressures caused by left ventricular diastolic dysfunction (DD), as in heart failure with preserved ejection fraction (HFpEF). FTR may also herald the presence of occult DD or indicate greater risk for new-onset DD. However, prevalence and incidence of diastolic dysfunction (DD) in isolated FTR have not been studied. Aims: Investigate the prevalence and incidence of DD across the different severities of FTR of unclear cause. Methods: Adults with normal EF and without structural heart disease undergoing echocardiography at a tertiary medical center with a repeat study ≥6 months from baseline were identified. Severe DD was defined by ≥3/4 abnormal DD parameters (medial e’, medial E/e’, tricuspid regurgitation velocity, left atrial volume index) and moderate DD by ≥2. Results: Among 30,428 patients (median age 60; 50% women), FTR was absent in 73%, mild in 22%, moderate in 4%, and severe in 0.4%. Severe DD was present in 2%, 5%, 11%, and 13% patients, respectively, (p<.001) and moderate DD in 9%, 19%, 31%, and 48%, respectively (p<.001). The association of DD with increasing FTR was independent of all clinical characteristics. Over median 3.0 (IQR 1.5-5.4) years, incident severe and moderate DD developed more frequently with increasing FTR severity ( Figure) . Findings were confirmed in a propensity-matched subset where patients were matched for age, sex, BMI, atrial fibrillation, and comorbidities and in patients without lung disease or ≥moderate right ventricular enlargement. Conclusions: Patients with FTR of undefined etiology commonly have DD suggesting the presence of underlying left heart disease. Patients without apparent DD or HF at baseline who have FTR remain at significantly increased risk of developing DD over follow-up and may be a target population for therapies to prevent progression to clinical HFpEF.

Introduction: Tricuspid regurgitation is a common echocardiographic finding leading to excess morbidity and mortality in adult population. Hypothesis: Racial and ethnic disparities have been observed in various cardiovascular disorders’ prevalence and natural course, including valvular lesions. However, little is known about the epidemiology and clinical correlations of TR among non-Hispanic Black adults. Methods: To examine risk factors and clinical outcomes in non-Hispanic Black adults with moderate or more severe TR, 685 patients (7%) self-identified as non-Hispanic Black and 9127 (93%) self-identified as non-Hispanic White with a first echocardiographic report of moderate or more severe TR between 2005-2016 were studied. Results: Non-Hispanic Black patients had more severe TR when compared to white patients (25% vs. 20%, p<0.001). After adjusting for age and sex, non-Hispanic Black patients had significantly higher 10-year all-cause mortality (HR=1.34 (1.18, 1.52), p<0.001). Black race remained a risk factor for all-cause mortality even after adjustment for comorbidities like CHF, COPD, DM, CKD, hypertension, and ischemic heart disease (HR=1.23 (1.08, 1.40), p=0.002). Conclusions: Significant racial disparities exist in demographic, clinical and echocardiographic characteristics between non-Hispanic Black and White patients with moderate or more severe TR. Black race is a potential disease modifier leading to excess mortality.

Introduction: Biomarkers can facilitate the prediction of events in primary prevention. Few studies have been conducted in the community setting with analyses that incorporate many biomarkers. Hypothesis: We tested whether a multi biomarker model would outperform clinical factors and individual biomarkers for predicting MACE and Stroke/MI in subjects without known CAD. Methods: A retrospective cohort study assessed composite outcomes MACE (MI, CABG, PCI, stroke, and death) and Stroke/MI. Cox proportional hazard models were fit for individual biomarkers, adjusted for age, gender, BMI, hypertension, CAD, and GFR. Multi biomarker models were developed based on AIC values from the single-biomarker models. Bootstrap tests compared survival C-statistics and relative Integrated Discrimination Index (IDI). Results: 1131 patients in Olmsted County, MN were studied. Median age was 63.1 years, 97.5% were Caucasian, and 52.2% were female. Median BMI was 27.8. Kaplan Meier rates of MACE and Stroke/MI were 29.2% (CI = 26.5-31.8%) and 12.3% (CI = 10.3% - 14.3%), at 10 years. Adjusted NT proBNP models showed a 31% increased risk of MACE/death (HR = 1.31; CI = 1.17-1.46) and a 31% increased risk for stroke/MI (HR = 1.31; CI = 1.08-1.58). Adjusted Ceramide score models showed a 13% increased risk of MACE/death (HR = 1.13; CI = 1.04-1.24) and a 29% increased risk for stroke/MI (HR = 1.29; CI = 1.11-1.51). NT proBNP and the Ceramide score with clinical factors was better than clinical factors alone for MACE/Death (Relative IDI = 29.7%; p = 0.003) and Stroke/MI (Relative IDI = 36.1%; p = 0.034). This combined model did not outperform the strongest single biomarker model for Stroke/MI or MACE/Death. Other biomarkers were not significant when added to the combined model. Discussion: Ceramide score and NT proBNP alone and together improve the prediction of MACE and Stroke/MI in a community primary prevention cohort.

Objective Tricuspid regurgitation (TR) is a prevalent valve disease associated with significant morbidity and mortality. We aimed to apply machine learning (ML) to assess risk stratification in patients with ≥moderate TR. Methods Patients with ≥moderate TR on echocardiogram between January 2005 and December 2016 were retrospectively included. We used 70% of data to train ML-based survival models including 27 clinical and echocardiographic features to predict mortality over a 3-year period on an independent test set (30%). To account for differences in baseline comorbidities, prediction was performed in groups stratified by increasing Charlson Comorbidity Index (CCI). Permutation feature importance was calculated using the best-performing model separately in these groups. Results Of 13 312 patients, mean age 72 ± 13 years and 7406 (55%) women, 7409 (56%) had moderate, 2646 (20%) had moderate–severe and 3257 (24%) had severe TR. The overall performance for 1-year mortality by 3 ML models was good, c-statistic 0.74–0.75. Interestingly, performance varied between CCI groups, (c-statistic = 0.774 in lowest CCI group and 0.661 in highest CCI group). The performance decreased over 3-year follow-up (average c-index 0.78). Furthermore, the top 10 features contributing to these predictions varied slightly with the CCI group, the top features included heart rate, right ventricular systolic pressure, blood pressure, diuretic use and age. Conclusions Machine learning of common clinical and echocardiographic features can evaluate mortality risk in patients with TR. Further refinement of models and validation in prospective studies are needed before incorporation into the clinical practice.

Abstract Background/Introduction Hypertension (HTN) and metabolic syndrome (MetS) are both leading risk factors for major cardiovascular diseases, which frequently coexist as a complicated cardiometabolic disorder. The cardiac hormone atrial natriuretic peptide (ANP) plays a key role in both blood pressure and metabolic regulation through activation of the guanylyl cyclase-A receptor (GC-A) and the second messenger 3’,5’ cyclic guanosine monophosphate (cGMP). Indeed, ANP decreases blood pressure, induces lipolysis by increasing plasma levels of non-esterified fatty acids (NEFA) and improves insulin-sensitivity. MANP is a new Mayo Clinic designed natriuretic peptide consisting of the native ANP with a 12-amino-acid C-terminus extension and its biological actions are mediated by the GC-A/cGMP pathway. MANP is less susceptible to neprilysin degradation and exert more sustained cGMP dependent biological actions than ANP. Purpose In a proof-of-principle human study, for the first time we aimed to determine the cardiovascular and metabolic properties of MANP, a novel ANP analog, in the clinical setting of HTN with MetS. Methods We conducted a double-blind, placebo-controlled trial in 22 patients (17 receiving MANP) with HTN and MetS involving single subcutaneous injection of MANP (2.5 µg/kg) or placebo (NCT03781739). Blood pressure (BP) and circulating cGMP were monitored for 24 hours post treatment. Circulating metabolic parameters including insulin, glucose, non-esterified fatty acids (NEFA) and insulin resistance (HOMA-IR) and insulin sensitivity (HOMA-IS) indexes were assessed for the first 4 hours post treatment. Results Compared to baseline, MANP increased plasma cGMP at 30 minutes (delta: 4.8 ± 2.0 pmol/mL, P = 0.02) and 1 hour (delta: 2.9 ± 1.3 pmol/mL, P = 0.03) post injection. At 6 hours, systolic BP decreased by 5.7 ± 2.9 mmHg (P = 0.06) in the MANP group, whereas no reduction in BP was observed in placebo group. Among the 17 subjects receiving MANP, lower baseline cGMP levels were associated with greater mean reductions in systolic BP (ρ = 0.66, P = 0.005). After MANP injection, glucose levels decreased at 2 (delta: -4.7 ± 2.1 mg/mL, P = 0.04) and 4 hours (delta: -13.1 ± 3.9 mg/mL, P = 0.003) compared to baseline while insulin levels remained stable. During the first 4 hours post injection, we also observed a trend of increase in insulin sensitivity index (HOMA2-IS) and decrease in insulin resistance index (HOMA2-IR) with MANP, both were opposite to the trends in placebo. At 1 hour post MANP administration, NEFA increased by 108.2 ± 37.4 µM compared to baseline (P = 0.01). Conclusion(s) Our findings support the favorable cardiovascular and metabolic actions of MANP as a potential therapeutic strategy for HTN with MetS.