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.
Background
Catastrophic antiphospholipid syndrome and lupus myocarditis are two rare life-threatening conditions.
Case Summary
We present a case of a 47-year-old woman admitted in profound cardiogenic shock due to catastrophic antiphospholipid syndrome and lupus myocarditis requiring advanced heart failure therapies, including early mechanical circulatory support. She improved with steroids, immunoglobulins, mycophenolate, and eculizumab.
Discussion
This case highlights the importance of early identification of cardiogenic shock secondary to catastrophic antiphospholipid syndrome and lupus myocarditis, the arrhythmogenic complications of myocarditis, and the subsequent management of the disease progression with mechanical and medical support.
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 (β = -324.1, p < 0.0001) whereas differences were not significant for NHB (β = -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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.