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Background: Despite optimal medical therapy and cardiac resynchronization therapy (CRT), significant functional mitral regurgitation (MR) persisted in 30% of the patients and labeled as CRT nonresponders., Aims: We sought to study the impact of transcatheter edge-to-edge repair (TEER) in patients with symptomatic grade III and IV functional MR despite CRT., Methods: A retrospective analysis was conducted of all patients who had prior CRT for at least 6 months and underwent TEER for significant residual functional MR (grade ≥3) and symptomatic heart failure (HF) at our institution. The primary outcomes were the change in New York Heart Association classification (NYHA), MR grade, echo parameters, and NT-ProBNP from baseline to 1-year post-procedure., Results: A total of 28 patients were identified, mean age of 73 ± 6.7 years and 89% males. Procedure success was achieved in all patients. At 1-year follow-up, patients had lower MR grade (median 2, IQR 1 [1,2] vs. 4, IQR 1 [3,4]; p < 0.001), NYHA class (median 2, IQR 1 [2,3] vs. 3, IQR 1 [3,4]; p < 0.001), and NT-ProBNP (7658 ± 11322 vs. 3760 ± 4431; p = 0.035) compared to before the TEER procedure. The left ventricular end-diastolic volume (255 ± 59 vs. 244 ± 66 mm; p = 0.016) and the right ventricular systolic pressure (52 ± 14 mmHg vs. 37 ± 13 mmHg, <0.001) decreased., Conclusion: Patients who remain symptomatic after CRT with severe functional MR had improved functional status and MR grade at 1-year following TEER. There was a signal toward reverse remodeling., (© 2024 Wiley Periodicals LLC.)

Objective: To investigate whether hypotensive patients diagnosed with heart failure and reduced ejection fraction (HFrEF) might benefit from angiotensin receptor-neprilysin inhibitors (ARNis) in real-world practice because patients with baseline systolic blood pressure (SBP) of less than 100 mm Hg have been excluded from landmark trials., Patients and Methods: In this multicenter study conducted between January 1, 2013, and December 31, 2021, a total of 7562 symptomatic patients with HFrEF were enrolled and grouped by SBP (hypotension was defined as an SBP of less than 100 mm Hg) and ARNi use as follows: group 1, hypotensive/non-ARNi users (n=484); group 2, hypotensive/ARNi users (n=308); group 3, nonhypotensive/non-ARNi users (n=4560); and group 4, nonhypotensive/ARNi users (n=2210). Inverse probability of treatment weighting was used to balance baseline characteristics for survival analysis., Results: Diverse baseline characteristics and lower rates of medication use were found among non-ARNi users compared with ARNi users. Hypotensive/ARNi users had lower ARNi initiation doses than nonhypotensive/ARNi users. We observed significantly lower mortality, composite heart failure hospitalization, and CV death for hypotensive/ARNi and the other 2 nonhypotensive groups (groups 3 and 4) during a median follow-up of 3.43 years (all P<.05), with a similar effect on reverse remodeling for the hypotensive/ARNi group compared with the hypotensive/non-ARNi group. The event-free survival benefits of ARNi vs renin-angiotensin system inhibitors were consistent with the lower boundary of SBP for clinical benefits found until 88 mm Hg (spline curves) after inverse probability of treatment weighting., Conclusion: Patients with HFrEF and hypotension may still benefit from ARNi treatment. Patients with hypotensive HFrEF should not be routinely excluded from ARNi use in a real-world setting., (Copyright © 2023 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background: Aortic stenosis (AS) is associated with myocardial ischemia through different mechanisms and may impair coronary arterial flow. However, data on the impact of moderate AS in patients with acute myocardial infarction (MI) is limited., Aims: This study aimed to investigate the impact of moderate AS in patients presenting with acute myocardial infarction (MI)., Methods: We conducted a retrospective analysis of all patients who presented with acute MI to all Mayo Clinic hospitals, using the Enterprise Mayo PCI Database from 2005 to 2016. Patients were stratified into two groups: moderate AS and mild/no AS. The primary outcome was all cause mortality., Results: The moderate AS group included 183 (13.3%) patients, and the mild/no AS group included 1190 (86.7%) patients. During hospitalization, there was no difference between both groups in mortality. Patients with moderate AS had higher in-hospital congestive heart failure (CHF) (8.2% vs. 4.4%, p = 0.025) compared with mild/no AS patients. At 1-year follow-up, patients with moderate AS had higher mortality (23.9% vs. 8.1%, p < 0.001) and higher CHF hospitalization (8.3% vs. 3.7%, p = 0.028). In multivariate analysis, moderate AS was associated with higher mortality at 1-year (odds ratio 2.4, 95% confidence interval [1.4-4.1], p = 0.002). In subgroup analyses, moderate AS increased all-cause mortality in STEMI and NSTEMI patients., Conclusion: The presence of moderate AS in acute MI patients was associated with worse clinical outcomes during hospitalization and at 1-year follow-up. These unfavorable outcomes highlight the need for a close follow-up of these patients and for timely therapeutic strategies to best manage these coexisting conditions., (© 2023 Wiley Periodicals LLC.)

Right ventricular (RV) pacing is the main treatment modality for patients with advanced atrioventricular (AV) block. Chronic RV pacing can cause cardiac systolic dysfunction and heart failure (HF). In this review, we discuss studies that have shown deleterious effects of chronic RV pacing on systolic cardiac function causing pacing-induced cardiomyopathy (PiCM), heart failure (HF), HF hospitalization, atrial fibrillation (AF) and cardiac mortality. RV apical pacing is the most widely used and studied. Adverse effects of RV pacing appear to be directly related to pacing burden and are worse in patients with pre-existing left ventricular (LV) dysfunction. Chronic RV pacing is also associated with heart failure with preserved ejection fraction (HFpEF). Mechanisms, risk factors, clinical and echocardiographic features, and strategies to minimize RV pacing-induced cardiac dysfunction are discussed in light of the latest data. Studies on biventricular (Bi-V) pacing upgrade in patients who develop RV PiCM, use of alternate RV pacing sites, de novo Bi-V pacing, and physiologic pacing using HIS bundle pacing (HBP) and left bundle area (LBBA) pacing in patients with an anticipated high RV pacing burden are discussed., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: To investigate the effectiveness and safety of angiotensin receptor-neprilysin inhibitors (ARNIs) in real-world patients with heart failure with reduced ejection fraction (HFrEF) and advanced chronic kidney disease (estimated glomerular filtration rate [eGFR] < 30 mL/min per 1.73 m 2 ), which have been excluded from the landmark trials., Patients and Methods: This study examined 3281 patients pooled from two multicenter HFrEF cohorts, and 661 patients with baseline eGFR less than 30 mL/min per 1.73 m 2 were further analyzed (the Taiwan Society of Cardiology - Heart Failure with reduced Ejection Fraction (TSOC-HFrEF) registry: May 1, 2013 to October 31, 2014, and the Treatment with Angiotensin Receptor neprilysin inhibitor fOr Taiwan Heart Failure patients (TAROT-HF) study: March 1, 2017, to December 31, 2018). Propensity score matching was performed to adjust for confounders. At 1-year follow-up, all-cause mortality, total heart failure hospitalizations, renal function, and left ventricular ejection fraction (LVEF) were used as the endpoints., Results: After propensity score matching, 510 patients (age, 69.8±13.9 years; male, 61.0%; mean LVEF, 29.8±7.3%; mean eGFR, 19.8±9.0 mL/min per 1.73 m 2 ) were included in the final analysis, including 278 patients receiving ARNI treatment (ARNI group) and 232 patients not on ARNI treatment (non-ARNI group). Baseline characteristics were comparable between the two groups. At 1 year, eGFR and LVEF measurements were significantly higher in the ARNI group than in the non-ARNI group (25.0±17.1 mL/min per 1.73 m 2 vs 21.4±17.5 mL/min per 1.73 m 2 ; P=.04; and 40.1±12.9% vs. 33.1±10.8%, P<.001, respectively). The ARNI group had significantly lower risks of 1-year all-cause mortality (19.4 vs 30.9 per 100-person year; P=.02), and total HF rehospitalizations (70.0 vs 110.4 per 100-person year; P=.01) than non-ARNI users., Conclusion: Our results show the effectiveness of ARNIs in HFrEF patients with advanced chronic kidney disease in a real-world setting., (Copyright © 2022 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Objective: Heart failure (HF) imposes a substantial burden and the prevalence of HF is high in patients with chronic kidney disease (CKD). HF results in multiple hospital admissions, but whether HF subtypes worsen long-term outcomes and renal function in patients with CKD remains inconclusive., Methods: The study comprised 10 904 patients with CKD aged ≥20 years who underwent echocardiography between 1 January 2011 and 31 December 2018. The patients were stratified into four groups: non-HF, HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and HF with preserved ejection fraction (HFpEF). The primary end points were all-cause mortality, major adverse cardiovascular events (MACEs) and adverse renal outcomes., Results: In inverse probability of treatment weighting-adjusted method, the risk of all-cause mortality and MACEs relative to the non-HF group was greatest in the HFrEF group (HR 3.18 (95% CI 2.57 to 3.93) and HR 3.83 (95% CI 3.20 to 4.59)), followed by the HFmrEF (HR 2.75 (95% CI 2.22 to 3.42) and HR 3.08 (95% CI 2.57 to 3.69)) and HFpEF (HR 1.85 (95% CI 1.59 to 2.15) and HR 2.43 (95% CI 2.16 to 2.73) groups. In addition, the HFrEF group had the greatest risks of end-stage renal disease (HR 2.58 (95% CI 1.94 to 3.44)) compared with other groups., Conclusions: HF is associated with subsequent worse clinical outcomes, which may be more pronounced in patients with HFrEF, followed by those with HFmrEF and those with HFpEF relative to non-HF group., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background. Clinical medicine relies heavily on the synthesis of information and data from multiple sources. However, often simple feature concatenation is used as a strategy for developing a multimodal machine learning model in the cardiovascular domain, and thus the models are often limited by pre-selected features and moderate accuracy. Method. We proposed a two-branched joint fusion model for fusing the 12-lead electrocardiogram (ECG) signal data with clinical variables from the electronic medical record (EMR) in an end-to-end deep learning architecture. The model follows the joint fusion scheme and learns complementary information from ECG and EMR. Retrospective data from the Mayo Clinic Health Systems across four sites for patients that underwent percutaneous coronary intervention (PCI) were obtained. Model performance was assessed by area under the receiver-operating characteristics (AUROC) and Delong's test. Results. The final cohort included 17,356 unique patients with a mean age of 67.2 ± 12.6 year (mean ± std) and 9,163 (52.7%) were male. The joint fusion model outperformed the ECG time-domain model with statistical margin. The model with clinical data obtained the highest AUROC for all-cause mortality (0.91 at 6 months) but the joint fusion model outperformed for cardiovascular outcomes - heart failure hospitalization and ischemic stroke with a significant margin (Delong's p < 0.05). Conclusion. To the best of our knowledge, this is the first study that developed a deep learning model with joint fusion architecture for the prediction of post-PCI prognosis and outperformed machine learning models developed using traditional single-source features (clinical variables or ECG features). Adding ECG data with clinical variables did not improve prediction of all-cause mortality as may be expected, but the improved performance of related cardiac outcomes shows that the fusion of ECG generates additional value., (© 2022 Institute of Physics and Engineering in Medicine.)

Background: The 2016 American Society of Echocardiography guidelines have been widely used to assess left ventricular diastolic function. However, limitations are present in the current classification system. The aim of this study was to develop a data-driven, unsupervised machine learning approach for diastolic function classification and risk stratification using the left ventricular diastolic function parameters recommended in the 2016 American Society of Echocardiography guidelines; the guideline grading was used as the reference standard., Methods: Baseline demographics, heart failure hospitalization, and all-cause mortality data were obtained for all adult patients who underwent transthoracic echocardiography at Mayo Clinic Rochester in 2015. Patients with prior mitral valve intervention, congenital heart disease, cardiac transplantation, or cardiac assist device implantation were excluded. Nine left ventricular diastolic function variables (mitral E- and A-wave peak velocities, E/A ratio, deceleration time, medial and lateral annular e' velocities and E/e' ratio, and tricuspid regurgitation peak velocity) were used for an unsupervised machine learning algorithm to identify different phenotype clusters. The cohort average of each variable was used for imputation. Patients were grouped according to the algorithm-determined clusters for Kaplan-Meier survival analysis., Results: Among 24,414 patients (mean age, 63.6 ± 16.2 years), all-cause mortality occurred in 4,612 patients (18.9%) during a median follow-up period of 3.1 years. The algorithm determined three clusters with echocardiographic measurement characteristics corresponding to normal diastolic function (n = 8,312), impaired relaxation (n = 11,779), and increased filling pressure (n = 4,323), with 3-year cumulative mortality of 11.8%, 19.9%, and 33.4%, respectively (P < .0001). All 10,694 patients (43.8%) classified as indeterminate were reclassified into the three clusters (n = 3,324, n = 5,353, and n = 2,017, respectively), with 3-year mortality of 16.6%, 22.9%, and 34.4%, respectively. The clusters also outperformed guideline-based grade for prognostication (C index = 0.607 vs 0.582, P = .013)., Conclusions: Unsupervised machine learning identified physiologically and prognostically distinct clusters on the basis of nine diastolic function Doppler variables. The clusters can be potentially applied in echocardiography laboratory practice and future clinical trials for simple, replicable diastolic function-related risk stratification., (Copyright © 2022 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.)