Disproportionately High Aortic Valve Calcium Scores in Atrial Fibrillation: Implications for Transcatheter Aortic Valve Replacement.

AIMS: Doppler mean gradient (MG) can underestimate aortic stenosis (AS) severity in patients with atrial fibrillation (AF) compared to patients in sinus rhythm (SR), potentially delaying intervention in AF. This study compared outcomes in patients with AF and SR following transcatheter aortic valve replacement (TAVR) and investigated delay in TAVR based on computed tomography aortic valve calcium score (AVCS). METHODS AND RESULTS: Patients who underwent TAVR from 2013 to 2017 for native valve severe AS were identified from an institutional database. Baseline characteristics and overall survival were compared between those in SR and AF. There were 820 patients (mean age 81 years; 41.6% female) included. AF was present in 356 patients. Patients in AF were older (82.2 vs. 80.5, p = 0.003), had lower MG compared to SR patients (42.0 vs. 44.9, p = 0.002) with similar indexed aortic valve area (0.4 vs. 0.4, p = 0.17). Median AVCS was higher in AF (males: AF 2850.0 vs. SR 2561.0, p = 0.044; females: AF 1942.0 vs. SR 1610.5, p = 0.025). Projected AVCS assuming same age of diagnosis was similar between AF and SR. Median survival post-TAVR was worse in AF compared to SR (3.2 vs 5.4 years, log rank p < 0.001). AF, lower MG, higher RVSP, dialysis, diabetes, and significant TR were associated with higher mortality (p < 0.05 for all). CONCLUSION: Older age and higher AVCS in patients with AF compared to SR suggests that AS was both underestimated and more advanced at TAVR referral.

Role of Genetics in Diagnosis and Management of Hypertrophic Cardiomyopathy: A Glimpse into the Future.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiomyopathy. It follows an autosomal dominant inheritance pattern in most cases, with incomplete penetrance and heterogeneity. It is familial in 60% of cases and most of these are caused by pathogenic variants in the core sarcomeric genes (MYH7, MYBPC3, TNNT2, TNNI3, MYL2, MYL3, TPM1, ACTC1). Genetic testing using targeted disease-specific panels that utilize next-generation sequencing (NGS) and include sarcomeric genes with the strongest evidence of association and syndrome-associated genes is highly recommended for every HCM patient to confirm the diagnosis, identify the molecular etiology, and guide screening and management. The yield of genetic testing for a disease-causing variant is 30% in sporadic cases and up to 60% in familial cases and in younger patients with typical asymmetrical septal hypertrophy. Genetic testing remains challenging in the interpretation of results and classification of variants. Therefore, in 2015 the American College of Medical Genetics and Genomics (ACMG) established guidelines to classify and interpret the variants with an emphasis on the necessity of periodic reassessment of variant classification as genetic knowledge rapidly expands. The current guidelines recommend focused cascade genetic testing regardless of age in phenotype-negative first-degree relatives if a variant with decisive evidence of pathogenicity has been identified in the proband. Genetic test results in family members guide longitudinal clinical surveillance. At present, there is emerging evidence for genetic test application in risk stratification and management but its implementation into clinical practice needs further study. Promising fields such as gene therapy and implementation of artificial intelligence in the diagnosis of HCM are emerging and paving the way for more effective screening and management, but many challenges and obstacles need to be overcome before establishing the practical implications of these new methods.

Identifying the Causes of Unexplained Dyspnea at High Altitude Using Normobaric Hypoxia with Echocardiography.

Exposure to high altitude results in hypobaric hypoxia, leading to physiological changes in the cardiovascular system that may result in limiting symptoms, including dyspnea, fatigue, and exercise intolerance. However, it is still unclear why some patients are more susceptible to high-altitude symptoms than others. Hypoxic simulation testing (HST) simulates changes in physiology that occur at a specific altitude by asking the patients to breathe a mixture of gases with decreased oxygen content. This study aimed to determine whether the use of transthoracic echocardiography (TTE) during HST can detect the rise in right-sided pressures and the impact of hypoxia on right ventricle (RV) hemodynamics and right to left shunts, thus revealing the underlying causes of high-altitude signs and symptoms. A retrospective study was performed including consecutive patients with unexplained dyspnea at high altitude. HSTs were performed by administrating reduced FiO2 to simulate altitude levels specific to patients' history. Echocardiography images were obtained at baseline and during hypoxia. The study included 27 patients, with a mean age of 65 years, 14 patients (51.9%) were female. RV systolic pressure increased at peak hypoxia, while RV systolic function declined as shown by a significant decrease in the tricuspid annular plane systolic excursion (TAPSE), the maximum velocity achieved by the lateral tricuspid annulus during systole (S' wave), and the RV free wall longitudinal strain. Additionally, right-to-left shunt was present in 19 (70.4%) patients as identified by bubble contrast injections. Among these, the severity of the shunt increased at peak hypoxia in eight cases (42.1%), and the shunt was only evident during hypoxia in seven patients (36.8%). In conclusion, the use of TTE during HST provides valuable information by revealing the presence of symptomatic, sustained shunts and confirming the decline in RV hemodynamics, thus potentially explaining dyspnea at high altitude. Further studies are needed to establish the optimal clinical role of this physiologic method.

Role of lipoprotein(a) concentrations in bioprosthetic aortic valve degeneration.

OBJECTIVES: Lipoprotein(a) (Lp(a)) is associated with an increased incidence of native aortic stenosis, which shares similar pathological mechanisms with bioprosthetic aortic valve (bAV) degeneration. However, evidence regarding the role of Lp(a) concentrations in bAV degeneration is lacking. This study aims to evaluate the association between Lp(a) concentrations and bAV degeneration. METHODS: In this retrospective multicentre study, patients who underwent a bAV replacement between 1 January 2010 and 31 December 2020 and had a Lp(a) measurement were included. Echocardiography follow-up was performed to determine the presence of bioprosthetic valve degeneration, which was defined as an increase >10 mm Hg in mean gradient from baseline with concomitant decrease in effective orifice area and Doppler Velocity Index, or new moderate/severe prosthetic regurgitation. Levels of Lp(a) were compared between patients with and without degeneration and Cox regression analysis was performed to investigate the association between Lp(a) levels and bioprosthetic valve degeneration. RESULTS: In total, 210 cases were included (mean age 74.1±9.4 years, 72.4% males). Median time between baseline and follow-up echocardiography was 4.4 (IQR 3.7) years. Bioprostheses degeneration was observed in 33 (15.7%) patients at follow-up. Median serum levels of Lp(a) were significantly higher in patients affected by degeneration versus non-affected cases: 50.0 (IQR 72.0) vs 15.6 (IQR 48.6) mg/dL, p=0.002. In the regression analysis, high Lp(a) levels (≥30 mg/dL) were associated with degeneration both in a univariable analysis (HR 3.6, 95% CI 1.7 to 7.6, p=0.001) and multivariable analysis adjusted by other risk factors for bioprostheses degeneration (HR 4.4, 95% CI 1.9 to 10.4, p=0.001). CONCLUSIONS: High serum Lp(a) is associated with bAV degeneration. Prospective studies are needed to confirm these findings and to investigate whether lowering Lp(a) levels could slow bioprostheses degradation.

Case series: cardiac sarcoma.

Background: Cardiac masses encompass a wide differential including primary and secondary malignancies and can present with a variety of symptoms, many of which are non-specific. Early identification and classification are important, particularly for cardiac malignancies such as sarcomas as these are aggressive tumours with exceptionally poor prognoses when metastases are present at diagnosis. Case summary: We report two cases of patients who presented with dyspnoea and were diagnosed with cardiac sarcomas; the former a primary sarcoma (undifferentiated pleomorphic subtype) and the latter a secondary sarcoma (round cell myxoid liposarcoma) that serve as comparisons for presentation and management of different types of this disease. Computed Tomography (CT) and echocardiography imaging findings are demonstrated showing the typical location and morphology of each subtype. Discussion: Cardiac sarcomas are the most common primary cardiac malignancy, of which undifferentiated pleomorphic sarcoma is a common subtype. Undifferentiated pleomorphic sarcomas are aggressive, have a tendency to arise in the left atrium, and can appear similar to benign cardiac masses. Round cell myxoid liposarcomas by contrast are rare causes of secondary cardiac malignancies, metastasizing to the heart from soft tissues. Both diagnoses carry poor prognoses and although rare, are important to recognize as timely intervention with surgery, radiotherapy, and consideration of chemotherapy is key to maximizing survival.

Using Augmented Mean Arterial Pressure to Identify High Mortality Risk Patients With Moderate Aortic Stenosis.

OBJECTIVE: To study the usefulness of a novel echocardiographic marker, augmented mean arterial pressure (AugMAP = [(mean aortic valve gradient + systolic blood pressure) + (2 × diastolic blood pressure)] / 3), in identifying high-risk patients with moderate aortic stenosis (AS). PATIENTS AND METHODS: Adults with moderate AS (aortic valve area, 1.0-1.5 cm2) at Mayo Clinic sites from January 1, 2010, through December 31, 2020, were identified. Baseline demographic, echocardiographic, and all-cause mortality data were retrieved. Patients were grouped into higher and lower AugMAP groups using a cutoff value of 80 mm Hg for analysis. Kaplan-Meier and Cox regression models were used to assess the performance of AugMAP. RESULTS: A total of 4563 patients with moderate AS were included (mean ± SD age, 73.7±12.5 years; 60.5% men). Median follow-up was 2.5 years; 36.0% of patients died. The mean ± SD left ventricular ejection fraction (LVEF) was 60.1%±11.4%, and the mean ± SD AugMAP was 99.1±13.1 mm Hg. Patients in the lower AugMAP group, with either preserved or reduced LVEF, had significantly worse survival performance (all P<.001). Multivariate Cox regression showed that AugMAP (hazard ratio, 0.962; 95% CI, 0.942 to 0.981 per 5-mm Hg increase; P<.001) and AugMAP less than 80 mm Hg (hazard ratio, 1.477; 95% CI, 1.241 to 1.756; P<.001) were independently associated with all-cause mortality. CONCLUSION: AugMAP is a simple and effective echocardiographic marker to identify high-risk patients with moderate AS independent of LVEF. It can potentially be used in the candidate selection process if moderate AS becomes indicated for aortic valve intervention in the future.

An Evidence-Based Approach to Anticoagulation Therapy Comparing Direct Oral Anticoagulants and Vitamin K Antagonists in Patients With Atrial Fibrillation and Bioprosthetic Valves: A Systematic Review, Meta-Analysis, and Network Meta-Analysis.

Direct oral anticoagulants (DOACs) are a newer class of anticoagulants that inhibit factor Xa or factor IIa and include drugs such as rivaroxaban, apixaban, edoxaban, betrixaban, and dabigatran. Although vitamin K antagonists (VKAs) have been traditionally used to prevent thromboembolic events, DOACs have gained popularity because of their faster onset and offset of action and reduced need for monitoring. This study aimed to provide more data for anticoagulants in patients with atrial fibrillation with bioprosthetic heart valves by incorporating all available trials to date. A search was performed across 5 electronic databases to identify relevant studies. We analyzed the data using a pooled risk ratio for categorical outcomes and used the I2 test to determine heterogeneity. The quality of randomized controlled trials was assessed using the Cochrane risk of bias assessment tool, and the National Institutes of Health tool was used for observational studies. Our study included a frequentist network meta-analysis (MA) of the aggregate data to obtain the network estimates for the outcomes of interest. We retrieved 28 studies with a total of 74,660 patients with bioprosthetic heart valves. Our MA significantly showed that DOACs decrease the risk of all-cause bleeding (risk ratio [RR] 0.80, 95% confidence interval [CI] 0.75 to 0.85, p >0.00001), stroke and systemic embolization (RR 0.89, 95% CI 0.80 to 0.99, p = 0.03), and intracranial bleeding outcomes (RR 0.62, 95% CI 0.45 to 0.86, p = 0.004) compared with VKA. In contrast, there was no significant difference between the compared groups in major bleeding (RR = 0.92, 95% CI 0.84 to 1.02, p = 0.10) and all-cause mortality outcomes (RR = 0.96, 95% CI 0.85 to 1.07, p = 0.43), respectively. In addition, the network MA results did not favor any of the studied interventions over each other (p <0.05) regarding all-cause bleeding, mortality, stroke and systemic embolization, and major bleeding outcomes. In conclusion, our study found that DOACs are more effective in reducing the risk of bleeding, stroke, systemic embolism, and intracranial bleeding than VKAs. However, no significant difference was observed in the incidence of gastrointestinal bleeding, major bleeding, thromboembolic events, and all-cause mortality. In addition, our network MA did not identify any specific DOAC treatment as more favorable than others.

Using Artificial Intelligence in Predicting Ischemic Stroke Events After Percutaneous Coronary Intervention.

BACKGROUND: Ischemic stroke (IS) is an uncommon but severe complication in patients undergoing percutaneous coronary intervention (PCI). Despite significant morbidity and economic cost associated with post PCI IS, a validated risk prediction model is not currently available. AIMS: We aim to develop a machine learning model that predicts IS after PCI. METHODS: We analyzed data from Mayo Clinic CathPCI registry from 2003 to 2018. Baseline clinical and demographic data, electrocardiography (ECG), intra/post-procedural data, and echocardiographic variables were abstracted. A random forest (RF) machine learning model and a logistic regression (LR) model were developed. The receiver operator characteristic (ROC) analysis was used to assess model performance in predicting IS at 6-month, 1-, 2-, and 5-years post-PCI. RESULTS: A total of 17,356 patients were included in the final analysis. The mean age of this cohort was 66.9 ± 12.5 years, and 70.7% were male. Post-PCI IS was noted in 109 patients (.6%) at 6 months, 132 patients (.8%) at 1 year, 175 patients (1%) at 2 years, and 264 patients (1.5%) at 5 years. The area under the curve of the RF model was superior to the LR model in predicting ischemic stroke at 6 months, 1-, 2-, and 5-years. Periprocedural stroke was the strongest predictor of IS post discharge. CONCLUSIONS: The RF model accurately predicts short- and long-term risk of IS and outperforms logistic regression analysis in patients undergoing PCI. Patients with periprocedural stroke may benefit from aggressive management to reduce the future risk of IS.

The impact of moderate aortic stenosis in acute myocardial infarction: A multicenter retrospective study.

BACKGROUND: Aortic stenosis (AS) is associated with myocardial ischemia through different mechanisms and may impair coronary arterial flow. However, data on the impact of moderate AS in patients with acute myocardial infarction (MI) is limited. AIMS: This study aimed to investigate the impact of moderate AS in patients presenting with acute myocardial infarction (MI). METHODS: We conducted a retrospective analysis of all patients who presented with acute MI to all Mayo Clinic hospitals, using the Enterprise Mayo PCI Database from 2005 to 2016. Patients were stratified into two groups: moderate AS and mild/no AS. The primary outcome was all cause mortality. RESULTS: The moderate AS group included 183 (13.3%) patients, and the mild/no AS group included 1190 (86.7%) patients. During hospitalization, there was no difference between both groups in mortality. Patients with moderate AS had higher in-hospital congestive heart failure (CHF) (8.2% vs. 4.4%, p = 0.025) compared with mild/no AS patients. At 1-year follow-up, patients with moderate AS had higher mortality (23.9% vs. 8.1%, p < 0.001) and higher CHF hospitalization (8.3% vs. 3.7%, p = 0.028). In multivariate analysis, moderate AS was associated with higher mortality at 1-year (odds ratio 2.4, 95% confidence interval [1.4-4.1], p = 0.002). In subgroup analyses, moderate AS increased all-cause mortality in STEMI and NSTEMI patients. CONCLUSION: The presence of moderate AS in acute MI patients was associated with worse clinical outcomes during hospitalization and at 1-year follow-up. These unfavorable outcomes highlight the need for a close follow-up of these patients and for timely therapeutic strategies to best manage these coexisting conditions.

Developing an Echocardiography-Based, Automatic Deep Learning Framework for the Differentiation of Increased Left Ventricular Wall Thickness Etiologies.

AIMS: Increased left ventricular (LV) wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness. METHODS AND RESULTS: Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 and 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4-chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: HCM: 0.93, CA: 0.90, and HTN/other: 0.92). CONCLUSION: The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.

High Prevalence of Severe Aortic Stenosis in Low-Flow State Associated With Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) is a low-flow state and may underestimate aortic stenosis (AS) severity. Single-high Doppler signals (HS) consistent with severe AS (peak velocity ≥4 m/s or mean gradient ≥40 mm Hg) are averaged down in current practice. The objective for the study was to determine the significance of HS in AF low-gradient AS (LGAS). METHODS: One thousand five hundred forty-one patients with aortic valve area ≤1 cm2 and left ventricular ejection fraction ≥50% were identified and classified as high-gradient AS (HGAS) (≥40 mm Hg) and LGAS (<40 mm Hg), and AF versus sinus rhythm (SR). Available computed tomography aortic valve calcium scores (AVCS) were retrieved from the medical record. Outcomes were assessed. RESULTS: Mean age was 76±11 years, female 47%. Mean gradient was 51±12 in SR-HGAS, 48±10 in AF-HGAS, 31±5 in SR-LGAS, and 29±7 mm Hg in AF-LGAS, all P≤0.001 versus SR-HGAS; HS were present in 33% of AF-LGAS. AVCS were available in 34%. Compared with SR-HGAS (2409 arbitrary units; interquartile range, 1581-3462) AVCS were higher in AF-HGAS (2991 arbitrary units; IQR1978-4229, P=0.001), not different in AF-LGAS (2399 arbitrary units; IQR1817-2810, P=0.47), and lower in SR-LGAS (1593 arbitrary units; IQR945-1832, P<0.001); AVCS in AF-LGAS were higher when HS were present (P=0.048). Compared with SR-HGAS, the age-, sex-, comorbidity index-, and time-dependent aortic valve replacement-adjusted mortality risk was higher in AF-HGAS (hazard ratio=1.82 [1.40-2.36], P<0.001) and AF-LGAS with HS (hazard ratio=1.54 [1.04-2.26], P=0.03) but not different in AF-LGAS without HS or SR-LGAS (both P=not significant). CONCLUSIONS: Severe AS was common in AF-LGAS. AVCS in AF-LGAS were not different from SR-HGAS. AVCS were higher and mortality worse in AF-LGAS when HS were present.