Transcatheter aortic valve replacement in a patient with quadricuspid aortic valve stenosis and regurgitation.

We report the case of an 80-year-old woman with known quadricuspid aortic valve (QAV), severe aortic stenosis, and moderate-to-severe regurgitation who recently underwent a transcatheter aortic valve replacement (TAVR).

Validation of American Society of Echocardiography Guideline-Recommended Parameters of Right Ventricular Dysfunction Using Artificial Intelligence Compared With Cardiac Magnetic Resonance Imaging.

BACKGROUND: Right ventricular (RV) function is important in the evaluation of cardiac function, but its assessment using standard transthoracic echocardiography (TTE) remains challenging. Cardiac magnetic resonance imaging (CMR) is considered the gold standard. The American Society of Echocardiography recommends surrogate measures of RV function and RV ejection fraction (RVEF) by TTE, including fractional area change (FAC), free wall strain (FWS), and tricuspid annular planar systolic excursion (TAPSE), but they require technical expertise in acquisition and quantification. METHODS: The aim of this study was to evaluate the sensitivity, specificity, and positive and negative predictive values of FAC, FWS, and TAPSE derived using a rapid, novel artificial intelligence (AI) software (LVivoRV) from a single-plane transthoracic echocardiographic apical four-chamber, RV-focused view without ultrasound-enhancing agents for detecting abnormal RV function compared with CMR-derived RVEF. RV dysfunction was defined as RVEF < 50% and RVEF < 40% on CMR. RESULTS: TTE and CMR were performed within a median of 10 days (interquartile range, 2-32 days) of each other in 225 consecutive patients without interval procedural or pharmacologic intervention. The sensitivity and negative predictive value to detect CMR-defined RV dysfunction when all three AI-derived parameters (FAC, FWS, and TAPSE) were abnormal were 91% and 96%, while those of expert physician reads were 91% and 97%. Specificity and positive predictive value were lower (50% and 32%) compared with expert physician-read echocardiograms (82% and 56%). CONCLUSIONS: AI-derived measurements of FAC, FWS, and TAPSE had excellent sensitivity and negative predictive value for ruling out significant RV dysfunction (CMR RVEF < 40%), comparable with that of expert physician readers, but lower specificity. Thus AI, using American Society of Echocardiography guidelines, may serve as a useful screening tool for rapid bedside assessment to exclude significant RV dysfunction.

Advances in Coronary Computed Tomographic Angiographic Imaging of Atherosclerosis for Risk Stratification and Preventive Care.

The diagnostic evaluation of coronary artery disease is undergoing a dramatic transformation with a new focus on atherosclerotic plaque. This review details the evidence needed for effective risk stratification and targeted preventive care based on recent advances in automated measurement of atherosclerosis from coronary computed tomography angiography (CTA). To date, research findings support that automated stenosis measurement is reasonably accurate, but evidence on variability by location, artery size, or image quality is unknown. The evidence for quantification of atherosclerotic plaque is unfolding, with strong concordance reported between coronary CTA and intravascular ultrasound measurement of total plaque volume (r >0.90). Statistical variance is higher for smaller plaque volumes. Limited data are available on how technical or patient-specific factors result in measurement variability by compositional subgroups. Coronary artery dimensions vary by age, sex, heart size, coronary dominance, and race and ethnicity. Accordingly, quantification programs excluding smaller arteries affect accuracy for women, patients with diabetes, and other patient subsets. Evidence is unfolding that quantification of atherosclerotic plaque is useful to enhance risk prediction, yet more evidence is required to define high-risk patients across varied populations and to determine whether such information is incremental to risk factors or currently used coronary computed tomography techniques (eg, coronary artery calcium scoring or visual assessment of plaque burden or stenosis). In summary, there is promise for the utility of coronary CTA quantification of atherosclerosis, especially if it can lead to targeted and more intensive cardiovascular prevention, notably for those patients with nonobstructive coronary artery disease and high-risk plaque features. The new quantification techniques available to imagers must not only provide sufficient added value to improve patient care, but also add minimal and reasonable cost to alleviate the financial burden on our patients and the health care system.

Randomized Trial of Anticoagulation Strategies for Noncritically Ill Patients Hospitalized With COVID-19.

BACKGROUND: Prior studies of therapeutic-dose anticoagulation in patients with COVID-19 have reported conflicting results. OBJECTIVES: We sought to determine the safety and effectiveness of therapeutic-dose anticoagulation in noncritically ill patients with COVID-19. METHODS: Patients hospitalized with COVID-19 not requiring intensive care unit treatment were randomized to prophylactic-dose enoxaparin, therapeutic-dose enoxaparin, or therapeutic-dose apixaban. The primary outcome was the 30-day composite of all-cause mortality, requirement for intensive care unit-level of care, systemic thromboembolism, or ischemic stroke assessed in the combined therapeutic-dose groups compared with the prophylactic-dose group. RESULTS: Between August 26, 2020, and September 19, 2022, 3,398 noncritically ill patients hospitalized with COVID-19 were randomized to prophylactic-dose enoxaparin (n = 1,141), therapeutic-dose enoxaparin (n = 1,136), or therapeutic-dose apixaban (n = 1,121) at 76 centers in 10 countries. The 30-day primary outcome occurred in 13.2% of patients in the prophylactic-dose group and 11.3% of patients in the combined therapeutic-dose groups (HR: 0.85; 95% CI: 0.69-1.04; P = 0.11). All-cause mortality occurred in 7.0% of patients treated with prophylactic-dose enoxaparin and 4.9% of patients treated with therapeutic-dose anticoagulation (HR: 0.70; 95% CI: 0.52-0.93; P = 0.01), and intubation was required in 8.4% vs 6.4% of patients, respectively (HR: 0.75; 95% CI: 0.58-0.98; P = 0.03). Results were similar in the 2 therapeutic-dose groups, and major bleeding in all 3 groups was infrequent. CONCLUSIONS: Among noncritically ill patients hospitalized with COVID-19, the 30-day primary composite outcome was not significantly reduced with therapeutic-dose anticoagulation compared with prophylactic-dose anticoagulation. However, fewer patients who were treated with therapeutic-dose anticoagulation required intubation and fewer died (FREEDOM COVID [FREEDOM COVID Anticoagulation Strategy]; NCT04512079).

Cardiovascular Complications of Interatrial Conduction Block: JACC State-of-the-Art Review.

Interatrial block (IAB) is an electrocardiographic pattern describing the conduction delay between the right and left atria. IAB is classified into 3 degrees of block that correspond to decreasing conduction in the region of Bachmann's bundle. Although initially considered benign in nature, specific subsets of IAB have been associated with atrial arrhythmias, elevated thromboembolic stroke risk, cognitive impairment, and mortality. As the pathophysiologic relationships between IAB and stroke are reinforced, investigation has now turned to the potential benefit of early detection, atrial imaging, cardiovascular risk factor modification, antiarrhythmic pharmacotherapy, and stroke prevention with oral anticoagulation. This review provides a contemporary overview of the epidemiology, pathophysiology, diagnosis, and management of IAB, with a focus on future directions.

Left Ventricular Thrombus Following Acute Myocardial Infarction: JACC State-of-the-Art Review.

The incidence of left ventricular (LV) thrombus following acute myocardial infarction has markedly declined in recent decades caused by advancements in reperfusion and antithrombotic therapies. Despite this, embolic events remain the most feared complication of LV thrombus necessitating systemic anticoagulation. Mechanistically, LV thrombus development depends on Virchow's triad (ie, endothelial injury from myocardial infarction, blood stasis from LV dysfunction, and hypercoagulability triggered by inflammation, with each of these elements representing potential therapeutic targets). Diagnostic modalities include transthoracic echocardiography with or without ultrasound-enhancing agents and cardiac magnetic resonance. Most LV thrombi develop within the first 2 weeks post-acute myocardial infarction, and the role of surveillance imaging appears limited. Vitamin K antagonists remain the mainstay of therapy because the efficacy of direct oral anticoagulants is less well established. Only meager data support the routine use of prophylactic anticoagulation, even in high-risk patients.

Assessment and validation of a novel fast fully automated artificial intelligence left ventricular ejection fraction quantification software.

BACKGROUND: Quantification of left ventricular ejection fraction (LVEF) by transthoracic echocardiography (TTE) is operator-dependent, time-consuming, and error-prone. LVivoEF by DIA is a new artificial intelligence (AI) software, which displays the tracking of endocardial borders and rapidly quantifies LVEF. We sought to assess the accuracy of LVivoEF compared to cardiac magnetic resonance imaging (cMRI) as the reference standard and to compare LVivoEF to the standard-of-care physician-measured LVEF (MD-EF) including studies with ultrasound enhancing agents (UEAs). METHODS: In 273 consecutive patients, we compared MD-EF and AI-derived LVEF to cMRI. AI-derived LVEF was obtained from a non-UEA four-chamber view without manual correction. Thirty-one patients were excluded: 25 had interval interventions or incomplete TTE or cMRI studies and six had uninterpretable non-UEA apical views. RESULTS: In the 242 subjects, the correlation between AI and cMRI was r = .890, similar to MD-EF and cMRI with r = .891 (p = 0.48). Of the 126 studies performed with UEAs, the correlation of AI using the unenhanced four-chamber view was r = .89, similar to MD-EF with r = .90. In the 116 unenhanced studies, AI correlation was r = .87, similar to MD-EF with r = .84. From Bland-Altman analysis, LVivoEF underreported the LVEF with a bias of 3.63 ± 7.40% EF points compared to cMRI while MD-EF to cMRI had a bias of .33 ± 7.52% (p = 0.80). CONCLUSIONS: Compared to cMRI, LVivoEF can accurately quantify LVEF from a standard apical four-chamber view without manual correction. Thus, LVivoEF has the ability to improve and expedite LVEF quantification.

Echocardiography in the time of Covid-19: Ultrasound enhancing agents save time and augment diagnostic information.

BACKGROUND: There are currently no clear guidelines regarding the use of ultrasound enhancing agents (UEAs) with transthoracic echocardiography (TTE) for patients hospitalized with Covid-19. We investigated whether the performance of TTE with UEAs provides more diagnostic information and allows for shorter acquisition time compared to unenhanced TTE imaging in this patient population. METHODS: We analyzed the TTEs of 107 hospitalized Covid-19 patients between April and June 2020 who were administered UEAs (Definity®, Lantheus). The time to acquire images with and without UEAs was calculated. A level III echocardiographer determined if new, clinically significant findings were visualized with the addition of UEAs. RESULTS: There was a mean of 11.84±3.59 UEA cineloops/study vs 20.74±8.10 non-UEA cineloops/study (p < 0.0001). Mean time to acquire UEA cineloop images was 72.28±28.18 s/study compared to 188.07±86.04 s/study for non-UEA cineloop images (p < 0.0001). Forty-eight patients (45%) had at least one new finding on UEA imaging, with a total of 62 new findings seen. New information gained with UEAs was more likely to be found in patients with acute respiratory distress syndrome (21 vs 9, p < 0.001) and in those on mechanical ventilation (21 vs 15, p = 0.046). CONCLUSIONS: TTE with UEAs required less time and fewer cineloop images compared to non-UEA imaging in patients hospitalized with Covid-19. Additionally, Covid-19 patients with severe respiratory disease benefited most with regard to new diagnostic information. Health care personnel should consider early use of UEAs in select hospitalized Covid-19 patients in order to reduce exposure and optimize diagnostic yield.

Using Clinical and Echocardiographic Characteristics to Characterize the Risk of Ischemic Stroke in Patients with COVID-19.

BACKGROUND: COVID-19 has been associated with an increased incidence of ischemic stroke. The use echocardiography to characterize the risk of ischemic stroke in patients hospitalized with COVID-19 has not been explored. METHODS: We conducted a retrospective study of 368 patients hospitalized between 3/1/2020 and 5/31/2020 who had laboratory-confirmed infection with SARS-CoV-2 and underwent transthoracic echocardiography during hospitalization. Patients were categorized according to the presence of ischemic stroke on cerebrovascular imaging following echocardiography. Ischemic stroke was identified in 49 patients (13.3%). We characterized the risk of ischemic stroke using a novel composite risk score of clinical and echocardiographic variables: age <55, systolic blood pressure >140 mmHg, anticoagulation prior to admission, left atrial dilation and left ventricular thrombus. RESULTS: Patients with ischemic stroke had no difference in biomarkers of inflammation and hypercoagulability compared to those without ischemic stroke. Patients with ischemic stroke had significantly more left atrial dilation and left ventricular thrombus (48.3% vs 27.9%, p = 0.04; 4.2% vs 0.7%, p = 0.03). The unadjusted odds ratio of the composite novel COVID-19 Ischemic Stroke Risk Score for the likelihood of ischemic stroke was 4.1 (95% confidence interval 1.4-16.1). The AUC for the risk score was 0.70. CONCLUSIONS: The COVID-19 Ischemic Stroke Risk Score utilizes clinical and echocardiographic parameters to robustly estimate the risk of ischemic stroke in patients hospitalized with COVID-19 and supports the use of echocardiography to characterize the risk of ischemic stroke in patients hospitalized with COVID-19.

Racial and ethnic differences in severity of coronary calcification among patients undergoing PCI: Results from a single-center multiethnic PCI registry.

BACKGROUND: Although population-based studies have demonstrated racial heterogeneity in coronary artery calcium (CAC) burden, the degree to which such associations extend to percutaneous coronary intervention (PCI) cohorts remains poorly characterized. We sought to evaluate the associations between race/ethnicity and CAC in a PCI population. METHODS: This single center retrospective study analyzed 1025 patients with prior CAC who underwent PCI between January 1, 2012 and May 15, 2020. Patients were grouped as non-Hispanic White (NHW, N = 779), non-Hispanic Black (NHB, N = 81) and Hispanic (H, N = 165). Associations between race and CAC (Agatston units) were examined using negative binomial regression while adjusting for baseline parameters. RESULTS: Among the 1025 patients (mean age 65.8, 70% male) who underwent PCI, NHW, NHB, and H populations had median CAC scores of 760, 500, and 462 Agatston units, respectively (p < 0.0001). Hispanic patients displayed a higher burden of diabetes mellitus, hypertension and hyperlipidemia compared with other groups. After adjusting for baseline differences and compared with NHW, the inverse association between Hispanic and CAC persisted (ß = -324.1, p < 0.0001) whereas differences were not significant for NHB (ß = -51.5, p = 0.67). CONCLUSIONS: Despite a higher risk clinical phenotype, Hispanic patients who underwent PCI had significantly lower CAC compared with non-Hispanic patients. Thus, current risk stratification models using universalized CAC scores may underestimate the risk for the Hispanic population. Race/ethnicity-informed CAC thresholds may better guide clinical decisions.

Guillain-Barré Syndrome After Primary Cytomegalovirus Infection in a Patient With a Heart Transplant.

A 56-year-old man underwent cardiac transplantation in April 2018. His post-operative course was uncomplicated and he had normal allograft function. On December 2019 he was admitted for fever and diarrhea and was found to have cytomegalovirus infection. A few weeks later, he presented with Guillain-Barré Syndrome. (Level of Difficulty: Advanced.).

A Personalized Approach to Chronic Kidney Disease and Cardiovascular Disease: JACC Review Topic of the Week.

Cardiovascular disease is the most common cause of death in patients with end-stage renal disease (ESRD). The initiation of dialysis for treatment of ESRD exacerbates chronic electrolyte and hemodynamic perturbations. Rapid large shifts in effective intravascular volume and electrolyte concentrations ultimately lead to subendocardial ischemia, increased left ventricular wall mass, and diastolic dysfunction, and can precipitate serious arrhythmias through a complex pathophysiological process. These factors, unique to advanced kidney disease and its treatment, increase the overall incidence of acute coronary syndrome and sudden cardiac death. To date, risk prediction models largely fail to incorporate the observed cardiovascular mortality in the CKD population; however, multimodality imaging may provide an additional prognostication and risk stratification. This comprehensive review discusses the cardiovascular risks associated with hemodialysis, and explores the pathophysiology and the novel utilization of multimodality imaging in CKD to promote a personalized approach for these patients with implications for future research.

Characterization of Myocardial Injury in Patients With COVID-19.

BACKGROUND: Myocardial injury is frequent among patients hospitalized with coronavirus disease-2019 (COVID-19) and is associated with a poor prognosis. However, the mechanisms of myocardial injury remain unclear and prior studies have not reported cardiovascular imaging data. OBJECTIVES: This study sought to characterize the echocardiographic abnormalities associated with myocardial injury and their prognostic impact in patients with COVID-19. METHODS: We conducted an international, multicenter cohort study including 7 hospitals in New York City and Milan of hospitalized patients with laboratory-confirmed COVID-19 who had undergone transthoracic echocardiographic (TTE) and electrocardiographic evaluation during their index hospitalization. Myocardial injury was defined as any elevation in cardiac troponin at the time of clinical presentation or during the hospitalization. RESULTS: A total of 305 patients were included. Mean age was 63 years and 205 patients (67.2%) were male. Overall, myocardial injury was observed in 190 patients (62.3%). Compared with patients without myocardial injury, those with myocardial injury had more electrocardiographic abnormalities, higher inflammatory biomarkers and an increased prevalence of major echocardiographic abnormalities that included left ventricular wall motion abnormalities, global left ventricular dysfunction, left ventricular diastolic dysfunction grade II or III, right ventricular dysfunction and pericardial effusions. Rates of in-hospital mortality were 5.2%, 18.6%, and 31.7% in patients without myocardial injury, with myocardial injury without TTE abnormalities, and with myocardial injury and TTE abnormalities. Following multivariable adjustment, myocardial injury with TTE abnormalities was associated with higher risk of death but not myocardial injury without TTE abnormalities. CONCLUSIONS: Among patients with COVID-19 who underwent TTE, cardiac structural abnormalities were present in nearly two-thirds of patients with myocardial injury. Myocardial injury was associated with increased in-hospital mortality particularly if echocardiographic abnormalities were present.

Machine Learning in Cardiology-Ensuring Clinical Impact Lives Up to the Hype.

Despite substantial advances in the study, treatment, and prevention of cardiovascular disease, numerous challenges relating to optimally screening, diagnosing, and managing patients remain. Simultaneous improvements in computing power, data storage, and data analytics have led to the development of new techniques to address these challenges. One powerful tool to this end is machine learning (ML), which aims to algorithmically identify and represent structure within data. Machine learning's ability to efficiently analyze large and highly complex data sets make it a desirable investigative approach in modern biomedical research. Despite this potential and enormous public and private sector investment, few prospective studies have demonstrated improved clinical outcomes from this technology. This is particularly true in cardiology, despite its emphasis on objective, data-driven results. This threatens to stifle ML's growth and use in mainstream medicine. We outline the current state of ML in cardiology and outline methods through which impactful and sustainable ML research can occur. Following these steps can ensure ML reaches its potential as a transformative technology in medicine.