Exercise-Induced Reduction in Left Ventricular Ejection Fraction in the Absence of Coronary Artery Disease: Clinical Characteristics and Outcomes

BACKGROUND

During exercise stress echocardiography (ESE), there are patients with normal left ventricular ejection fraction (LVEF) who paradoxically develop reduced LVEF during exercise despite absence of coronary artery disease (CAD) and a significant hypertensive response. This study sought to describe the clinical features and outcomes of this population.

METHODS

Among ESEs performed between 2003 and 2022, patients without CAD by angiogram within 90 days of ESE and resting LVEF ≥50% with a ≥5% LVEF decrease during ESE were included. Outcomes assessed were all-cause mortality, heart failure (HF) hospitalization, and atrial fibrillation (AF). Kaplan-Meier and Cox regression methods were used to analyze time-to-event outcomes.

RESULTS

Among 213,643 ESE, 134 patients met the eligibility criteria. The mean age of the population was 66 ± 10 years, 76% were women, and 16% had AF at baseline. Mean LVEF was 58% ± 4% at rest and 43% ± 4% at peak stress. Stress ECG met the criteria for ischemia in 14% of these patients. The 10-year estimated incidence of HF hospitalization was 17.6% (95% CI, 9.0%-26.2%). Among the subgroup without AF at baseline, the 10-year estimated incidence of developing AF was 23.4% (95% CI, 13.4%-33.4%). The 10-year estimated incidence of all-cause mortality was 12.9% (95% CI, 5.5%-20.3%), with 89% of deaths occurring due to noncardiovascular causes.

CONCLUSION

Patients with exercise-induced reduction in LVEF in the absence of obstructive CAD have a high incidence of HF hospitalizations and AF. The underlying pathophysiology of this disease process needs to be further investigated.

Genetic Biomarkers in Heart Failure: From Gene Panels to Polygenic Risk Scores

PURPOSE OF REVIEW

This review aims to provide a comprehensive overview of the current understanding of genetic markers associated with heart failure (HF) and its underlying causative diseases, such as cardiomyopathies. It highlights the relevance of genetic biomarkers in diagnosing HF, predicting prognosis, potentially identifying its preclinical stages and identifying targets to enable the implementation of individualized medicine approaches.

RECENT FINDINGS

The prevalence of HF is increasing due to an aging population but with greater access to disease-modifying therapies. Advanced diagnostic tools such as cardiac magnetic resonance, nuclear imaging, and AI-enabled diagnostic testing are now being utilized to further characterize HF patients. Additionally, the importance of genetic testing in HF diagnosis and management is increasingly being recognized. Genetic biomarkers, including single nucleotide polymorphisms (SNPs) and rare genetic variants, are emerging as crucial tools for diagnosing HF substrates, determining prognosis and increasingly directing therapy. These genetic insights are key to optimizing HF management and delivering personalized treatment tailored to individual patients. HF is a complex syndrome affecting millions globally, characterized by high mortality and significant economic burden. Understanding the underlying etiologies of HF is essential for improving management and clinical outcomes. Recent advances highlight the use of multimodal assessments, including AI-enabled diagnostics and genetic testing, to better characterize and manage HF. Genetic biomarkers are particularly promising in identifying preclinical HF stages and providing personalized treatment options. The genetic contribution to HF is heterogeneous, with both monogenic and polygenic bases playing a role. These developments underscore the shift towards personalized medicine in HF management.

Conduction Disorders And Their Clinical Impact After Sutureless/Rapid Deployment Aortic Bioprosthesis

INTRODUCTION

Aortic stenosis remains the number one heart valve pathology. The drive to improve the surgical outcomes brought to focus rapid deployment valves (RDV), which reduce aortic cross-clamping and cardio-pulmonary bypass (CPB) times. However, some centers have reported a higher rate of conduction abnormalities and permanent pacemaker (PPM) implantation. The aim of this study was to investigate the incidence of conduction abnormalities after aortic valve replacement with RDV, as well as its impact on immediate postoperative outcomes.

METHODS

Retrospective analysis of associated conductions disorders and PPM implantation rates, as well as post-operative outcomes of all patients undergoing isolated aortic valve replacement between April 2014 and December 2019 with an RDV. Comparative analysis between the group with PPM implantation and the one with no PPM implantation. Patients with previous PPM implantation, reoperations and patients with missing pre or postoperative ECG data were excluded.

RESULTS

We studied 201 patients. The majority of conduction abnormalities were left bundle branch block (54,0%). Twenty-six PPM were implanted (12,6%). Pre-operative characteristic between the groups were similar and little differences were found in regard to most complications. However, the PPM group showed significantly higher rates of stroke (7.7% vs 0.0%, p=0.016) and hemodynamic support for longer than 24 hours (60.0% vs 36.1%, p=0.028). From the multivariable analysis, preoperative right bundle branch block was the only independent risk factor associated with PPM.

CONCLUSIONS

PPM implantation rates with RDV are relatively high and are associated with prolonged hospital and ICU stays, postoperative stroke rates and requirement of aminergic support. Their use should be made on a case-by-case basis taking into consideration the existence of preoperative conduction disorders, especially right bundle branch block.

The Detection Rate of Late Gadolinium Enhancement in Takotsubo Syndrome: A Systematic Review and Meta-Analysis

The absence of late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) is commonly used to distinguish takotsubo syndrome (TTS) from other myocardial diseases. However, case series have reported the presence of LGE in TTS. This study aimed to summarize the evidence on the frequency of LGE in TTS and identify potential variables that may influence the detection of LGE. Electronic databases were systematically searched for studies reporting LGE frequency in patients with TTS. The overall frequency was estimated using the inverse variance method and a random-effects model for a single proportion. Factors influencing LGE detection were analyzed. Of 490 studies screened, 21 were included (703 patients, 90% women). The estimated overall frequency of LGE was 22.4% (95% confidence interval [CI] 8.7% to 39.6%). In patients with TTS who underwent CMR within 3 days of symptom occurrence, the frequency of LGE was 40.7% (95% CI 18.8% to 64.5%), which was significantly higher than in those who performed CMR after 3 days (3.9%, p <0.010). The sensitivity threshold used in the imaging protocols had a statistically significant impact on the frequency of LGE detection (p = 0.030). A total of 10 studies performed a follow-up CMR after at least 3 months, reporting a frequency of LGE of 1.7% (95% CI 0.0% to 8.9%). In conclusion, published studies report the presence of LGE in TTS at presentation in a significant proportion of patients. However, its detection is strongly influenced by the duration between symptom onset and CMR acquisition and by the sensitivity threshold used for the imaging protocol. LGE is rarely present at follow-up.

Prevalence, Penetrance, and Phenotypic Manifestation of Cardiomyopathy-Associated Genetic Variants in the General Population: Insights from a Mayo Clinic Biobank Study

OBJECTIVE

To determine the prevalence, penetrance, and disease expression of cardiomyopathy-related genetic variants in an unselected, richly phenotyped Mayo Clinic population in the setting of preemptive sequencing, with return of incidental findings following the American College of Medical Genetics and Genomics recommendations.

PATIENTS AND METHODS

We analyzed a quaternary medical center-based biobank cohort (n=983) for reportable variants in 15 cardiomyopathy genes. Prioritization of genetic variants was performed using an internally developed pipeline to identify potentially reportable variants. Prioritized variants were then manually curated. The correlation of likely pathogenic/pathogenic (LP/P) variants with clinical phenotypes and outcomes was established. Artificial intelligence-enabled electrocardiographic predictions of reduced left ventricular ejection fraction and hypertrophic cardiomyopathy were applied to genotype-positive (G+) participants.

RESULTS

Of the 983 patients, 11 (1%) were G+, with 11 LP/P variants found in the MYBPC3, DSG2, MYH7, DSP, and PKP2 genes. All G+ participants underwent electrocardiography, and 10 (90%) underwent echocardiography. Most patients (10 [90%]) did not have a prior diagnosis of cardiomyopathy. Definitive disease penetrance (heart failure or cardiomyopathy) was present in 4 (36%), while 3 (27%) had possible penetrance (structural heart disease identified by echocardiography). Arrhythmias and/or cardiac conduction disease was present in 4 of 11 G+ individuals (36%). Artificial intelligence-electrocardiography was positive for hypertrophic cardiomyopathy or reduced left ventricular ejection fraction in 5 of the G+ participants (45%), of whom 4 (80%) had definitive or possible disease penetrance.

CONCLUSION

Cardiomyopathy-associated LP/P variants are present in a small subset of a quaternary medical center population, and disease penetrance in G+ individuals is high in the form of cardiac structural abnormalities and heart failure.