Scalia, Isabel G.

Introduction: Mitral valve transcatheter edge-to-edge repair (M-TEER) has emerged as a minimally invasive option for high-risk surgical candidates with severe and symptomatic mitral regurgitation (MR), but post-procedure residual mitral valve (MV) dysfunction remains a significant concern. This study evaluates the clinical utility of combining artificial intelligence applied to electrocardiograms (ECG-AI) for diastolic dysfunction (DD) grading and the echocardiography-derived velocity time integral of the MV and left ventricular outflow tract ratio (VTIMV/LVOT) in predicting prognosis in patients post-M-TEER. Methods: A retrospective analysis of patients who underwent M-TEER between 2014 and 2021 was conducted. Patients were categorized based on VTIMV/LVOT and ECG-AI scores into three groups: both normal parameters, either abnormal parameter, or both abnormal parameters to compare outcomes (mortality, major adverse cardiovascular events [MACE], and the need for subsequent MV reintervention) using Kaplan–Meier analysis, multivariable Cox regression models, and net reclassification improvement. Results: Overall, 250 patients were included; the median age was 79.5 (IQR: 73.1, 84.6) and 66.4% were male. The combined abnormal VTIMV/LVOT (≥2.5) and ECG-AI score for DD (>1) was associated with higher risk of one-year mortality (adjusted HR: 4.56 [1.04–19.89], p = 0.044) and MACE (adjusted HR: 3.72 [1.09–12.72], p = 0.037) compared to patients with both normal parameters. Conclusions: This study highlights the potential additive value of integrating VTIMV/LVOT and ECG-AI scores as a prognostic tool for a personalized approach to the post-operative evaluation and risk stratification in M-TEER patients.

Abstract Introduction Cancer therapy-related cardiac dysfunction (CTRCD) after anthracycline-based therapy is a dreaded complication due to its significant morbidity and mortality. Sodium-glucose cotransporters-2 inhibitors (SGLT2i) have been shown to improve cardiovascular outcomes in multiple scenarios. However, its potential benefits in patients who develop CTRCD due to anthracycline-based chemotherapy are not well established. Purpose To investigate the benefits of SGLT2i in cancer patients who develop CTRCD secondary to anthracycline-based chemotherapy. Methods All patients who underwent anthracycline therapy between 2002 and 2022 across three tertiary centers and had a diagnosis of moderate or severe CTRCD according to 2022 European Society of Cardiology (ESC) guidelines were evaluated. Baseline characteristics, echocardiograms pre and post chemotherapy, and mortality were reviewed. Kaplan Meier analysis was conducted to compare all-cause and cardiovascular mortality between patients treated with SGLT2i (both patients on chronic SGLT2i who continued their therapy following CTRCD and those who commenced the treatment after CTRCD diagnosis) and those not receiving this therapy. Results In total, 398 patients diagnosed with moderate or severe CTRCD were included; median age was 66.82 (58.07, 74.46) years and 59.29% were males. Among them, 39 (9.80%) received SGLT2i. Mortality rates at 1- and 5-years were significantly lower among patients who were on SGLT2i treatment compared to patients who were not (8.40% vs 46.30%, p= 0.0001 and 17.30% vs 65%, p= 0.0001, respectively) (Figure1). Furthermore, cardiovascular mortality rate at 5 years was significantly lower in patients receiving SGLT2i compared to patients not receiving this therapy (0% vs 11%, p= 0.046). Conclusions SGLT2i may have survival benefit in cancer patients who develop CTRCD secondary to anthracycline-based chemotherapy and might be considered as an adjunctive treatment to improve survival outcomes in this population.Figure 1.Kaplan-Meier Curves

Aortic stenosis (AS), the most common valvular heart disease, is traditionally graded based on several echocardiographic quantitative parameters, such as aortic valve area (AVA), mean pressure gradient (MPG), and peak jet velocity (Vmax). This systematic review evaluates the clinical significance and prognostic implications of discordant high-gradient AS (DHG-AS), a distinct hemodynamic phenotype characterized by elevated MPG despite a preserved AVA (>1.0 cm2). Although often overlooked, DHG-AS presents unique diagnostic and therapeutic challenges, as high gradients remain a strong predictor of adverse outcomes despite moderately reduced AVA. Sixty-three studies were included following rigorous selection and quality assessment of the key studies. Prognostic outcomes across five key studies were discrepant: some showed better survival in DHG-AS compared to concordant high-gradient AS (CHG-AS), while others reported similar or worse outcomes. For instance, a retrospective observational study including 3209 patients with AS found higher mortality in CHG-AS (unadjusted HR: 1.4; 95% CI: 1.1 to 1.7), whereas another retrospective multicenter study including 2724 patients with AS observed worse outcomes in DHG-AS (adjusted HR: 1.59; 95% CI: 1.04 to 2.56). These discrepancies may stem from delays in intervention or heterogeneity in study populations. Despite the diagnostic ambiguity, the presence of high gradients warrants careful evaluation, aggressive risk stratification, and timely management. Current guidelines recommend a multimodal approach combining echocardiography, computed tomography (CT) calcium scoring, transesophageal echocardiography (TEE) planimetry, and, when needed, catheterization. Anatomic AVA assessment by TEE, CT, and cardiac magnetic resonance imaging (CMR) can improve diagnostic accuracy by directly visualizing valve morphology and planimetry-based AVA, helping to clarify the true severity in discordant cases. However, these modalities are limited by factors such as image quality (especially with TEE), radiation exposure and contrast use (in CT), and availability or contraindications (in CMR). Management remains largely based on CHG-AS protocols, with intervention primarily guided by transvalvular gradient and symptom burden. The variability among the different guidelines in defining severity and therapeutic thresholds highlights the need for tailored approaches in DHG-AS. DHG-AS is clinically relevant and associated with substantial prognostic uncertainty. Timely recognition and individualized treatment could improve outcomes in this complex subgroup.

Abstract Aims Significant advancements have been made in the management of obstructive hypertrophic cardiomyopathy (oHCM), yet the extent of left ventricular outflow tract (LVOT) gradient reduction achieved with commonly used pharmacological therapies [beta-blockers (BBs), calcium channel blockers (CCBs), disopyramide, and cardiac myosin inhibitors (CMIs)] relative to each other is still unclear. Methods and results PubMed and Scopus were searched up to September 2024. Clinical trials or observational studies that assessed the changes associated with BBs, CCBs, disopyramide, or CMIs in LVOT gradient at rest or with provocation in patients with oHCM were included. Mean changes in LVOT gradients were pooled as mean differences (MD) with 95% confidence intervals (CIs) in a random-effects model. Thirty-seven studies, with 44 arms and 1898 patients, were included in the analysis. At the therapeutic class level, pooled analysis showed that disopyramide was associated with the highest reduction in LVOT gradient at rest [MD: −43.5 (95% CI, −51.6 to −35.3)], followed by CMIs [MD: −34.8 (95% CI, −40.6 to −29.0)], BBs [MD: −20.7 (95% CI, −29.4 to −12.0)], and then CCBs [MD: −14.7 (95% CI, −23.3 to −6.1)], inter-action P < 0.01. Within CMIs, mavacamten had a higher effect than aficamten on gradient reduction; among the included BBs, metoprolol showed the highest gradient reduction, while among CCBs, verapamil was the most effective (inter-action P < 0.01). Similar results were observed for provocable LVOT gradients. Conclusion Pharmacological therapies effectively reduced LVOT gradients in oHCM patients to varying degrees, with disopyramide and CMIs showing the highest effect, followed by BBs and CCBs.

Cardiovascular diseases and cancer are the leading causes of morbidity and mortality in modern society. Expanding cancer therapies that have improved prognosis may also be associated with cardiotoxicity, and extended life span after survivorship is associated with the increasing prevalence of cardiovascular disease. As such, the field of cardio-oncology has been rapidly expanding, with an aim to identify cardiotoxicity and cardiac disease early in a patient who is receiving treatment for cancer or is in survivorship. Artificial intelligence is revolutionizing modern medicine with its ability to identify cardiac disease early. This article comprehensively reviews applications of artificial intelligence specifically applied to electrocardiograms, echocardiography, cardiac magnetic resonance imaging, and nuclear imaging to predict cardiac toxicity in the setting of cancer therapies, with a view to reduce early complications and cardiac side effects from cancer therapies such as chemotherapy, radiation therapy, or immunotherapy.

Abstract Aims Atrial fibrillation (AF) is the most common cardiac arrhythmia. Although lipoprotein(a) [Lp(a)] is known to be a well-established risk factor for atherosclerotic cardiovascular disease, its role in the development of AF, independent of this association, remains unclear. Methods and results Adult patients from the three Mayo Clinic sites with a baseline Lp(a) and without AF history were included. Patients were categorized into two groups based on their Lp(a) levels: high Lp(a) (≥50 mg/dL) and low Lp(a) (<50 mg/dL). Survival probabilities free from incident AF were compared between Lp(a) groups, during a follow-up period up to 15 years, using the Kaplan–Meier curve and the log-rank test. Multivariable Cox regression analysis was also conducted. A total of 75 376 patients were included (median age: 55 years, 59% males), with a median follow-up duration of 8.8 (inter-quartile range: 3.4, 14.8) years. Incident AF was detected in 5738 (7.6%) patients. Survival probability free from incident AF was significantly lower in patients with elevated Lp(a) (86%) compared with those with low Lp(a) (88%, log-rank P < 0.001). Multivariable analysis adjusted for potential risk factors of AF showed a statistically significant association of elevated Lp(a) with an 11% increase in AF risk (adjusted hazard ratio: 1.11, 95% confidence interval: 1.05–1.18). Conclusion Our study suggests that elevated Lp(a) (≥50 mg/dL) is an independent risk factor for incident AF. Future prospective studies are warranted to validate our results and to test if reducing Lp(a) could mitigate the burden of AF.

Lipoprotein(a) [Lp(a)] is a well-established causal risk factor for cardiovascular diseases (CVDs), as reported by multiple Mendelian randomization studies and large epidemiological studies. When elevated Lp(a) is combined with other risk factors, most notably elevated low-density lipoprotein cholesterol (LDL-C), a synergistic atherogenic effect has been reported. However, the current literature is conflicting regarding how Lp(a) interacts in the context of controlled LDL-C levels (e.g., <70 mg/dL) and whether reducing LDL-C can modify the atherogenic effect of Lp(a). In some studies, elevated Lp(a) was still significantly associated with a higher risk of cardiovascular events, despite controlled levels of LDL-C. In contrast, multiple studies have reported attenuation of the cardiovascular risk mediated by elevated Lp(a) with lower LDL-C levels. Moreover, the relationship between Lp(a) and triglycerides, high-density lipoprotein, and very low-density lipoprotein remains unclear. In this literature review, we summarize and discuss the current evidence regarding the interactions between Lp(a) and other lipid molecules, how they contribute to the pathogenesis of CVD, and future perspectives, particularly in the current era where promising targeted Lp(a)-lowering therapies are under development.

Background: Pulmonary hypertension (PH) is a complex condition associated with significant morbidity and mortality. Traditional diagnostic and management approaches for PH often face limitations, leading to delays in diagnosis and potentially suboptimal treatment outcomes. Artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL) offers a transformative approach to PH care. Materials and Methods: We systematically searched PubMed, Scopus, and Web of Science for original studies on AI applications in PH, using predefined keywords. Out of more than 500 initial articles, 45 relevant studies were selected. Risk of bias was evaluated using PROBAST (Prediction model Risk of Bias Assessment Tool). Results: This review examines the potential applications of AI in PH, focusing on its role in enhancing diagnosis, disease classification, and prognostication. We discuss how AI-powered analysis of medical data can improve the accuracy and efficiency of detecting PH. Furthermore, we explore the potential of AI in risk stratification, leading to treatment optimization for PH. Conclusions: While acknowledging the existing challenges and limitations and the need for continued exploration and refinement of AI-driven tools, this review highlights the significant promise of AI in revolutionizing PH management to improve patient outcomes.

Bioprosthetic aortic valve degeneration (BAVD) is a significant clinical concern following both transcatheter aortic valve replacement (TAVR) and surgical aortic valve replacement (SAVR). The increasing use of bioprosthetic valves in aortic valve replacement in younger patients and the subsequent rise in cases of BAVD are acknowledged in this review which aims to provide a comprehensive overview of the incidence, diagnosis, predictors, and management of BAVD. Based on a thorough review of the existing literature, this article provides an updated overview of the biological mechanisms underlying valve degeneration, including calcification, structural deterioration, and inflammatory processes and addresses the various risk factors contributing to BAVD, such as patient demographics, comorbidities, and procedural variables. The difficulties in early detection and accurate diagnosis of BAVD are discussed with an emphasis on the need for improved imaging techniques. The incidence and progression of BAVD in patients undergoing TAVR versus SAVR are compared, providing insights into the differences and similarities between the two procedures and procedural impacts on valve longevity. The current strategies for managing BAVD, including re-intervention options of redo surgery and valve-in-valve TAVR, along with emerging treatments are discussed. The controversies in the existing literature are highlighted to offer directions for future investigations to enhance the understanding and management of BAVD.

Background Lipoprotein(a) [Lp(a)] is an independent, causal risk factor for cardiovascular disease. However, it is still unclear whether controlling low-density lipoprotein cholesterol (LDL-C) to optimal levels can attenuate cardiovascular risk mediated by elevated Lp(a), especially in the setting of secondary prevention. Methods Adult patients with a baseline Lp(a) measurement who underwent percutaneous coronary intervention (PCI) and reached their LDL-C target levels (<70 mg/dl) at Mayo Clinic sites between 2006 and 2017 were included. Primary outcomes included major adverse cardiovascular events (MACE) and all-cause mortality. Kaplan–Meier curves were created to compare the survival probabilities among patients with Lp(a) ≥ 50 mg/dl compared with Lp(a) < 50 mg/dl. Multivariable Cox regression analyses were performed to quantify the association of elevated Lp(a) with our relevant outcomes and to control for possible confounders. Results In total, 878 patients (median age: 68 years, and 74% males) who underwent PCI were included for analysis. Of them, 29.7% had elevated Lp(a) ≥ 50 mg/dl. Kaplan–Meier curves did not reveal any significant difference in survival probabilities for elevated Lp(a) for any outcome including MACE (P = 0.91), all-cause mortality (P = 0.26), or the separate MACE components. Similarly, the multivariable analysis showed no significant association for MACE (hazard ratio: 1.07, 95% confidence interval: 0.84–1.37) or all-cause mortality (hazard ratio: 0.98, 95% confidence interval: 0.74–1.30). Conclusion In patients who underwent PCI and have their LDL-C controlled below 70 mg/dl, no significant association was found between elevated Lp(a) ≥ 50 mg/dl and risk for MACE or all-cause mortality.