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Background: Secondary prevention after percutaneous coronary interventions (PCIs) is still challenging and lipoprotein(a) [Lp(a)] is believed to be a residual risk factor in this setting. However, the effect of Lp(a) in case of well-controlled low-density lipoprotein cholesterol (LDL-C) is still unclear. The interaction between Lp(a) and LDL-C has been studied in primary prevention but still needs to be investigated in secondary prevention. Hypothesis: Achieving adequate LDL-C control after PCI may reduce the cardiovascular (CV) risk associated with Lp(a). Methods: A retrospective study of consecutive patients who underwent PCI and reached their LDL-C target levels (<70mg/dL) at three academic centers sites between 2006 and 2017. All included patients must have an Lp(a) measurement before the PCI intervention. Clinical outcomes on 10-year follow-up were collected by reviewing the electronic patients' records. The primary outcomes included all-cause mortality (ACM) and major adverse CV events (MACE) including non-fatal MI, ischemic stroke, coronary revascularization, and CV death. Kaplan-Meier curves were created to compare the survival probabilities among patients with high Lp(a) (≥50mg/dL) versus those with low Lp(a) (<50mg/dL). Univariate and multivariate Cox regression analyses were performed to quantify the association of elevated Lp(a) with outcomes and control for potential confounders. Results: In total, 878 patients (median age = 68 years, 74% males) were included in the analysis. Of them, 242 (27.6%) had high Lp(a) ≥50mg/dL. Kaplan Meier analyses did not reveal any significant difference in survival probabilities across the Lp(a) groups for any of the outcomes (Figure 1). The results were consistent in univariate (MACE, HR: 1.08 [95%CIs 0.85-1.35]; ACM, HR: 0.97 [95% CI 0.76-1.23]) and multivariate analyses (MACE, HR: 1.14, [95% CIs 0.90-1.45]; ACM, HR: 1.08 [95% CI 0.84-1.39]). Conclusion: These findings suggest that, in patients who underwent PCI and achieved an LDL-C target of <70 mg/dL, elevated Lp(a) levels were not associated with and increased risk of MACE or mortality. Controlling the LDL-C should still be the cornerstone in secondary prevention after PCI, however, larger prospective studies are still warranted to validate our results.

Background: Myocarditis is a dreaded complication of immune-checkpoint inhibitor (ICI) therapy but challenging to diagnose. There are no published data comparing the two leading diagnostic criteria for ICI myocarditis and their association with cardiovascular events. Methods: Patients treated with ICI and cardiac Troponin (cTnT) measurements thereafter at a tertiary institution from 2011 to 2022 were identified. Charts were reviewed for ICI-related myocarditis according to the Bonaca et. al criteria and the ESC-ICOS guideline criteria. A propensity matched control group was identified of patients treated with ICI but without developing myocarditis. Medical records were reviewed for baseline characteristics and long-term outcomes, including cardiac death, MACE (myocardial infarction, TIA/stroke, new heart failure diagnosis), and arrhythmias (V-tach, A-fib, complete heart block). Results: A total of 59 patients were identified as having a diagnosis of ICI-related myocarditis per Bonaca criteria (16 having definite, 13 probable and 30 possible myocarditis), and 47 met the ESC-ICOS guideline criteria. Mean age was 73.1±10.2 years, 60.1% were male, median follow-up was 2.5 years. ICI-related myocarditis as diagnosed by both diagnostic criteria had prognostic value for cardiac death (HR 13.94, 95%CI 1.84-105.64, p=0.011 per Bonaca, HR 6.22, 95%CI 1.77-21.88, p=0.004 per ESC-ICOS), MACE, (HR 3.17, 95%CI 1.34-7.47, p=0.008 per Bonaca, HR 2.97, 95%CI 1.37-6.45, p=0.006 per ESC-ICOS), and arrhythmias (HR 1.93, 95%CI 1.10-3.38, p=0.022 per Bonaca, HR 2.09, 95%CI 1.21-3.60, p<0.001 per ESC-ICOS), (Figures 1 and 2). There was no significant difference for cardiac death (AUC 0.75 for Bonaca, AUC 0.74 for ESC, p=0.765) or MACE (AUC 0.66 for Bonaca, AUC 0.66 for ESC, p=0.916) when both criteria were compared with each other. Conclusion: The ESC-ICOS criteria were more restrictive than the Bonaca criteria for the diagnosis of ICI-related myocarditis but similar in terms of prognostic value.

Background: New-onset atrial fibrillation (AF) is common among kidney transplant (KTx) recipients and is associated with reduced patient survival. Predictors of AF after KTx are not well understood, although AF can be associated with traditional and non-traditional risk factors. While artificial intelligence-enabled electrocardiography (AI-ECG) has shown promise in predicting incident AF, its predictive and prognostic implications in the KTx population have not yet been evaluated. Hypothesis: AI-ECG can predict new-onset AF and carries prognostic implications in patients undergoing KTx. Aims: To evaluate the clinical implications of applying AI-ECG to the preoperative ECGs of recipients of a KTx. Methods: Patients without a history of AF who underwent KTx at three referral centers between 2011 and 2021, with at least one preoperative ECG, were included in this retrospective study. Preoperative ECGs were analyzed using a previously developed AI-ECG algorithm to estimate the probabilities of new-onset AF. Based on these probabilities, patients were categorized into two groups: high and low probability of incident AF. The optimal cut-off value for the AI-ECG tool was determined using ROC analysis. The incidence of new-onset AF and mortality at 5 years post KTx were compared between these two groups using univariate and multivariate Cox regression analyses. Results: In total, 6246 patients were included (mean age 52.9 ±14.3 years, 58.7% males). A pre-transplant AI-ECG probability of AF >10% was identified as the most accurate cutoff point to distinguish between patients at low risk and high risk of incident AF (ROC = 0.72). The study found that a preoperative AI-ECG high risk of AF demonstrated not only a strong association with new-onset AF (HR 2.54, 95%CI 2.02-3.19, p<0.001 on multivariable analysis, Figure 1A ) but was also associated with an increased risk of mortality both on univariate (HR 2.73, 95%CI 2.34-3.18, p<0.001) and multivariate (HR 1.57, 95%CI 1.29-1.91, p<0.001 ) analysis at 5-year follow-up ( Figure 1B ). Conclusion: The application of AI-ECG to a single widely available test may help assess the risk of new-onset AF and mortality in patients undergoing KTx. Accurate risk stratification may identify a high-risk subgroup of transplant recipients who can benefit from closer AF monitoring, risk factor modification, and early management.

The assessment of left atrial strain (LAS) has emerged as an essential component in the evaluation of cardiac function, especially in pathologies such as heart failure and atrial fibrillation. This narrative review aims to outline the available methods for assessing LAS with a major emphasis on speckle-tracking echocardiography techniques. Other imaging modalities, including cardiac magnetic resonance and cardiac computed tomography, also provide important information on LA dynamics but have disadvantages with respect to cost and availability. The current narrative review underlines basic concepts such as the accurate assessment of LAS and discusses the clinical relevance of LAS by pointing out its significant diagnostic and prognostic role in several cardiovascular conditions. The aim of this article is to discuss the current integration of LAS into clinical practice with a view to further improving patient management and treatment strategies.

Lipoprotein (a) is a complex lipid molecule that has sparked immense interest in recent years, after studies demonstrated its significant association with several cardiovascular conditions. Lp(a) promotes cardiovascular disease through its combined proatherogenic, pro-inflammatory, and prothrombotic effects. While the measurement of Lp(a) has become widely available, effective methods to reduce its concentration are currently limited. However, emerging data from ongoing clinical trials involving antisense oligonucleotides have indicated promising outcomes in effectively reducing Lp(a) concentrations. This may serve as a potential therapeutic target in the management and prevention of myocardial infarction, calcific aortic stenosis, and cerebrovascular accidents. In contrast, the role of Lp(a) in atrial fibrillation, in-stent restenosis, cardiac allograft vasculopathy, and bioprosthetic aortic valve degeneration remains unclear. This review article aims to thoroughly review the existing literature and provide an updated overview of the evidence surrounding the association of Lp(a) and these cardiovascular diseases. We seek to highlight controversies in the existing literature and offer directions for future investigations to better understand Lp(a)’s precise role in these conditions, while providing a summary of its unique molecular characteristics.

Athlete’s heart (AH) represents the heart’s remarkable ability to adapt structurally and functionally to prolonged and intensive athletic training. Characterized by increased left ventricular (LV) wall thickness, enlarged cardiac chambers, and augmented cardiac mass, AH typically maintains or enhances systolic and diastolic functions. Despite the positive health implications, these adaptations can obscure the difference between benign physiological changes and early manifestations of cardiac pathologies such as dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), and arrhythmogenic cardiomyopathy (ACM). This article reviews the imaging characteristics of AH across various modalities, emphasizing echocardiography, cardiac magnetic resonance (CMR), and cardiac computed tomography as primary tools for evaluating cardiac function and distinguishing physiological adaptations from pathological conditions. The findings highlight the need for precise diagnostic criteria and advanced imaging techniques to ensure accurate differentiation, preventing misdiagnosis and its associated risks, such as sudden cardiac death (SCD). Understanding these adaptations and employing the appropriate imaging methods are crucial for athletes’ effective management and health optimization.

Abstract Aims Lipoprotein(a) [Lp(a)] has demonstrated its association with atherosclerosis and myocardial infarction. However, its role in the development of in-stent restenosis (ISR) after percutaneous coronary intervention (PCI) is not clearly established. The aim of this study is to investigate the association between Lp(a) and ISR. Methods and results A retrospective study of adult patients who underwent successful PCI between January 2006 and December 2017 at the three Mayo Clinic sites and had a preprocedural Lp(a) measurement was conducted. Patients were divided into two groups according to the serum Lp(a) concentration [high Lp(a) ≥ 50 mg/dL and low Lp(a) &lt; 50 mg/dL]. Univariable and multivariable analyses were performed to compare risk of ISR between patients with high Lp(a) vs. those with low Lp(a). A total of 1209 patients were included, with mean age 65.9 ± 11.7 years and 71.8% were male. Median follow-up after baseline PCI was 8.8 [interquartile range (IQR) 7.4] years. Restenosis was observed in 162 (13.4%) patients. Median serum levels of Lp(a) were significantly higher in patients affected by ISR vs. non-affected cases: 27 (IQR 73.8) vs. 20 (IQR 57.5) mg/dL, P = 0.008. The rate of ISR was significantly higher among patients with high Lp(a) vs. patients with low Lp(a) values (17.0% vs. 11.6%, P = 0.010). High Lp(a) values were independently associated with ISR events (hazard ratio 1.67, 95% confidence interval 1.18–2.37, P = 0.004), and this association was more prominent after the first year following the PCI. Conclusion Lipoprotein(a) is an independent predictor for long-term ISR and should be considered in the evaluation of patients undergoing PCI.

Systemic vasculitides are a rare and complex group of diseases that can affect multiple organ systems. Clinically, presentation may be vague and non-specific and as such, diagnosis and subsequent management are challenging. These entities are typically classified by the size of vessel involved, including large-vessel vasculitis (giant cell arteritis, Takayasu’s arteritis, and clinically isolated aortitis), medium-vessel vasculitis (including polyarteritis nodosa and Kawasaki disease), and small-vessel vasculitis (granulomatosis with polyangiitis and eosinophilic granulomatosis with polyangiitis). There are also other systemic vasculitides that do not fit in to these categories, such as Behcet’s disease, Cogan syndrome, and IgG4-related disease. Advances in medical imaging modalities have revolutionized the approach to diagnosis of these diseases. Specifically, color Doppler ultrasound, computed tomography and angiography, magnetic resonance imaging, positron emission tomography, or invasive catheterization as indicated have become fundamental in the work up of any patient with suspected systemic or localized vasculitis. This review presents the key diagnostic imaging modalities and their clinical utility in the evaluation of systemic vasculitis.

Cardiac amyloidosis (CA) is an underdiagnosed form of infiltrative cardiomyopathy caused by abnormal amyloid fibrils deposited extracellularly in the myocardium and cardiac structures. There can be high variability in its clinical manifestations, and diagnosing CA requires expertise and often thorough evaluation; as such, the diagnosis of CA can be challenging and is often delayed. The application of artificial intelligence (AI) to different diagnostic modalities is rapidly expanding and transforming cardiovascular medicine. Advanced AI methods such as deep-learning convolutional neural networks (CNNs) may enhance the diagnostic process for CA by identifying patients at higher risk and potentially expediting the diagnosis of CA. In this review, we summarize the current state of AI applications to different diagnostic modalities used for the evaluation of CA, including their diagnostic and prognostic potential, and current challenges and limitations.

Cardiac allograft vasculopathy (CAV) is a distinct form of coronary artery disease that represents a major cause of death beyond the first year after heart transplantation. The pathophysiology of CAV is still not completely elucidated; it involves progressive circumferential wall thickening of both the epicardial and intramyocardial coronary arteries. Coronary angiography is still considered the gold-standard test for the diagnosis of CAV, and intravascular ultrasound (IVUS) can detect early intimal thickening with improved sensitivity. However, these tests are invasive and are unable to visualize and evaluate coronary microcirculation. Increasing evidence for non-invasive surveillance techniques assessing both epicardial and microvascular components of CAV may help improve early detection. These include computed tomography coronary angiography (CTCA), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and vasodilator stress myocardial contrast echocardiography perfusion imaging. This review summarizes the current state of diagnostic modalities and their utility and prognostic value for CAV and also evaluates emerging tools that may improve the early detection of this complex disease.