Ayoub, Chadi

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.

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.

Abstract Aims The increasing need for diagnostic echocardiography tests presents challenges in preserving the quality and promptness of reports. While Large Language Models (LLMs) have proven effective in summarizing clinical texts, their application in echo remains underexplored. Methods and results Adult echocardiography studies, conducted at the Mayo Clinic from 1 January 2017 to 31 December 2017, were categorized into two groups: development (all Mayo locations except Arizona) and Arizona validation sets. We adapted open-source LLMs (Llama-2, MedAlpaca, Zephyr, and Flan-T5) using In-Context Learning and Quantized Low-Rank Adaptation fine-tuning (FT) for echo report summarization from ‘Findings’ to ‘Impressions.’ Against cardiologist-generated Impressions, the models’ performance was assessed both quantitatively with automatic metrics and qualitatively by cardiologists. The development dataset included 97 506 reports from 71 717 unique patients, predominantly male (55.4%), with an average age of 64.3 ± 15.8 years. EchoGPT, a fine-tuned Llama-2 model, outperformed other models with win rates ranging from 87% to 99% in various automatic metrics, and produced reports comparable to cardiologists in qualitative review (significantly preferred in conciseness (P < 0.001), with no significant preference in completeness, correctness, and clinical utility). Correlations between automatic and human metrics were fair to modest, with the best being RadGraph F1 scores vs. clinical utility (r = 0.42) and automatic metrics showed insensitivity (0–5% drop) to changes in measurement numbers. Conclusion EchoGPT can generate draft reports for human review and approval, helping to streamline the workflow. However, scalable evaluation approaches dedicated to echo reports remains necessary.

Introduction/Background: Loeys-Dietz syndrome (LDS) is a rare autosomal dominant aortic aneurysm syndrome characterized by arterial tortuosity resulting in arterial aneurysms and dissections, with unique craniofacial and skeletal features including bifid uvula, cleft palate and hypertelorism. While the presence of atrial fibrillation (Afib) and arrhythmias have been reported in LDS patients, limited investigation has been completed regarding the associated risk and severity of vascular complications in relationship to these arrhythmias1,2. Research Questions/Hypothesis: Are there any differences in vascular outcomes in patients with LDS when experiencing various forms of tachyarrhythmia? Goals/Aims: To evaluate the relationship between various types of arrhythmias and vascular outcomes in patients with LDS, including arterial dissection, stroke, revascularization, and death. Methods/Approach: A large sample of LDS patients (n=436) from a single tertiary referral center was assessed for ICD-10 diagnoses of arrhythmia and outcomes of interest. Arrhythmias assessed included Afib, atrial flutter (AFL), premature ventricular contractions (PVCs), and supraventricular tachycardia (SVT). Outcomes were arterial dissection, hemorrhagic and ischemic stroke, revascularization, and all-cause mortality. Results/Data: Our cohort (n=436) had an average age of 47 and was 57.8% female. A total of 26 patients had a documented history of tachyarrhythmia: 16 (3.4%) Afib, 2 (0.5%) AFL, 6 (1.4%) SVT, and 2 (0.5%) PVC. LDS patients with Afib were at significantly higher risk of arterial dissection (25% vs 6.0%, OR: 5.3, p<0.01), revascularization (18.8% vs 3.3%, OR: 8.1, p<0.01), stroke (25% vs 3.6%, OR: 9.0, p<0.001), and death (25% vs 4.3%, OR: 7.4, p<0.01) compared to those without a documented history of arrhythmia. Other arrhythmia types evaluated were not significant. Predictors of any arrhythmia type included hypertension (78% vs 31%, OR: 1.5, p<0.001) and heart failure (39% vs 5.0%, OR: 2.3, p<0.001). Conclusion: Although rare, Afib in LDS patients is associated with adverse vascular outcomes and mortality compared to those without a history of arrhythmia. Furthermore, the magnitude of increased risk is striking. Early identification and management of Afib in LDS patients may be critical in mitigating the risk of potential vascular complications.

Background: Atrial fibrillation (AF), the most common clinically managed cardiac arrhythmia, is known to increase the risk of heart failure, stroke, and mortality. Lipoprotein(a) [Lp(a)], a well-established risk factor for atherosclerotic cardiovascular disease (ASCVD), also plays a role in cardiovascular health. However, the influence of Lp(a) on the development of AF, independent of its association with ASCVD, remains unclear. Hypothesis: Elevated Lp(a) may be associated with increased risk of new-onset AF. Methods: A retrospective study was conducted on patients from the three Mayo Clinic sites who had their Lp(a) levels measured and had no prior history of AF. Patients were categorized into two groups based on their serum Lp(a) concentrations: high Lp(a) (≥50 mg/dL) and low Lp(a) (<50 mg/dL). New AF diagnoses were identified during the follow-up period. Survival probabilities between the two Lp(a) groups were compared using the Kaplan–Meier curve and the Log-Rank test. Cox regression analyses, both univariable and multivariable, were performed to evaluate established risk factors and compare the risk of new-onset AF between the high and low Lp(a) groups. Results: A total of 108,930 patients were included (median age: 55 years, 58% males), with a follow-up duration for up to 10 years. Incident AF was detected in 8432 (7.7%) patients. Median serum levels of Lp(a) were significantly higher in patients with AF versus non-AF patients: 15 (IQR 43) vs. 12 (IQR 34) mg/dL, p<0.001. The percentage of patients having elevated Lp(a) was significantly higher in the AF group versus non-AF group: 2119 (25%) vs 21151 (21%), p<0.001. Survival probability for new-onset AF was significantly lower in patients with elevated Lp(a) compared with those with low Lp(a) (log rank p<0.001, Figure 1). In the univariate analysis, high Lp(a) levels were associated with a 17% increase in the risk of AF (HR = 1.17, 95% CIs: 1.12 to 1.23). The multivariate analysis adjusted for well-established risk factors for AF showed a less strong but still significant association, with a 10% increase in AF risk (HR = 1.10, 95% CI: 1.05 to 1.15). Conclusion: Our study suggests that elevated Lp(a) (≥50 mg/dL) seems to be an independent risk factor for new-onset AF. Future prospective studies are still warranted to validate our results.

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.

Coronary CT angiography (CCTA) is now endorsed by all major cardiology guidelines for the investigation of chest pain and assessment for coronary artery disease (CAD) in appropriately selected patients. CAD is a leading cause of morbidity and mortality. There is extensive literature to support CCTA diagnostic and prognostic value both for stable and acute symptoms. It enables rapid and cost-effective rule-out of CAD, and permits quantification and characterization of coronary plaque and associated significance. In this comprehensive review, we detail the road traveled as CCTA evolved to include quantitative assessment of plaque stenosis and extent, characterization of plaque characteristics including high-risk features, functional assessment including fractional flow reserve-CT (FFR-CT), and CT perfusion techniques. The state of current guideline recommendations and clinical applications are reviewed, as well as future directions in the rapidly advancing field of CT technology, including photon counting and applications of artificial intelligence (AI).

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.

AbstractBackgroundDespite optimal medical therapy and cardiac resynchronization therapy (CRT), significant functional mitral regurgitation (MR) persisted in 30% of the patients and labeled as CRT nonresponders.AimsWe sought to study the impact of transcatheter edge‐to‐edge repair (TEER) in patients with symptomatic grade III and IV functional MR despite CRT.MethodsA 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.ResultsA 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.ConclusionPatients 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.