Citations

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.

Abstract Aims Lipoprotein(a) (Lp(a)) levels are known to be mainly genetically determined. However, only scarce data are available on the intra-individual variability of Lp(a) levels across time. Methods and results We included adult patients (≥18 years old) who had baseline and follow-up Lp(a) measurements (between 1997 and 2024) with a minimum of 1 year apart. Patients were categorized into three groups as follows: normal (&lt;30 mg/dL), borderline (30 to 50 mg/dL), and high Lp(a) (≥50 mg/dL). Multivariable logistic regression was conducted to assess the predictors of the intra-individual changes in Lp(a) ≥ 10 mg/dL. A total of 11 669 individuals (median age: 54 years, 60% males) were included in our analysis, with median time between measurements of 4.5 years [interquartile range (IQR): 2.2, 10.6]. The median Lp(a) was 16 mg/dL (IQR: 7, 52) at baseline, compared with 15 mg/dL (IQR: 7, 52) at follow-up. At follow-up, 96.4% of individuals with normal Lp(a) and 89.9% with high Lp(a) remained in their categories, while 51.2% with borderline Lp(a) changed their category. Of the included population, 24.9% had an intra-individual Lp(a) change ≥ 10 mg/dL. Female sex (P &lt; 0.001), history of ASCVD (P = 0.003), statin therapy (P = 0.003), and elevated LDL cholesterol (LDL-C) levels ≥ 100 mg/dL (P &lt; 0.001) were significantly associated with higher odds of intra-individual Lp(a) changes ≥ 10 mg/dL. Conclusion Lipoprotein(a) levels were generally stable over time; however, patients with borderline levels may require more than one Lp(a) measurement, especially if they are females, have a history of ASCVD, have elevated LDL-C levels, or are on statin therapy.

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.

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.

Abstract Background Bicuspid aortic valve (BAv) is associated with increased oxidative stress and inflammation, resulting in valve fibrosis, calcification, and ultimately early degenerative valve disease, often necessitating premature aortic valve intervention. In recent years, growing evidence has been published supporting the role of lipoprotein(a) [Lp(a)], an important carrier of oxidized phospholipids, in the development of aortic valve disease in the general population. However, the specific influence of Lp(a) levels in patients with BAv remains to be firmly established. Purpose To assess the role of Lp(a) levels in the development of aortic valve disease and the necessity for aortic valve interventions among individuals with BAv. Methods This retrospective multicenter study encompassed consecutive patients diagnosed with BAv from January 1997 to December 2022, all of whom had undergone serum Lp(a) measurement. This study evaluated the association between Lp(a) concentrations and the occurrence of aortic valve interventions. A cutoff point of ≥30 mg/dl for high Lp(a) levels was established. Binary logistic regression was utilized to calculate the odds ratio (OR) for an aortic intervention according to high versus low Lp(a) levels. Additionally, Kaplan Meier curves were employed to estimate the cumulative requirement for an aortic valve replacement based on Lp(a) concentrations. Results A total of 452 patients with BAv and a Lp(a) measurement were included in the study, with a mean age of 37.2 ±10.5 years at the time of BAv diagnosis, with 71.2% being male. Among these, 101 (22.3%) patients underwent an aortic valve replacement. In 72 cases (71.3%) aortic stenosis was the primary indication for intervention, while aortic regurgitation accounted for 29 cases (28.7%). The presence of elevated Lp(a) levels (≥30 mg/dl) demonstrated a significant association with the requirement for an aortic valve intervention (OR 2.2, 95%CI 1.4-3.6, p&lt;0.001) in both the regression analysis and using the Kaplan-Meier estimator (Figure). High Lp(a) concentrations posed a risk factor for aortic valve replacements regardless of whether the primary indication for intervention was significant stenosis (OR 1.8, 95%CI 1.1-3.1, p=0.028) or regurgitation (OR 2.5, 95%CI 1.2-5.4, p=0.018). Conclusion Increased concentrations of Lp(a) may influence the clinical trajectory of patients with a BAv and may be a significant risk factor for aortic valve replacement, irrespective of the primary indication for intervention. Further investigations will be critical in unveiling the precise pathological mechanisms of Lp(a) in BAv. Confirming whether reducing Lp(a) levels could slow the progression of aortic disease in this demographic requires further exploration. Kaplan-Meier estimator.

Prostate cancer lung metastasis represents a clinical conundrum due to its implications for advanced disease progression and the complexities it introduces in treatment planning. As the disease progresses to distant sites such as the lung, the clinical management becomes increasingly intricate, requiring tailored therapeutic strategies to address the unique characteristics of metastatic lesions. This review seeks to synthesize the current state of knowledge surrounding prostate cancer metastasis to the lung, shedding light on the diverse array of clinical presentations encountered, ranging from subtle radiological findings to overt symptomatic manifestations. By examining the diagnostic modalities utilized in identifying this metastasis, including advanced imaging techniques and histopathological analyses, this review aims to provide insights into the diagnostic landscape and the challenges associated with accurately characterizing lung metastatic lesions in prostate cancer patients. Moreover, this review delves into the nuances of therapeutic interventions employed in managing prostate cancer lung metastasis, encompassing systemic treatments such as hormonal therapies and chemotherapy, as well as metastasis-directed therapies including surgery and radiotherapy.

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.