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.
The Human Disease Ontology (DO) (http://www.disease-ontology.org), database has undergone significant expansion in the past three years. The DO disease classification includes specific formal semantic rules to express meaningful disease models and has expanded from a single asserted classification to include multiple-inferred mechanistic disease classifications, thus providing novel perspectives on related diseases. Expansion of disease terms, alternative anatomy, cell type and genetic disease classifications and workflow automation highlight the updates for the DO since 2015. The enhanced breadth and depth of the DO’s knowledgebase has expanded the DO’s utility for exploring the multi-etiology of human disease, thus improving the capture and communication of health-related data across biomedical databases, bioinformatics tools, genomic and cancer resources and demonstrated by a 6.6× growth in DO’s user community since 2015. The DO’s continual integration of human disease knowledge, evidenced by the more than 200 SVN/GitHub releases/revisions, since previously reported in our DO 2015 NAR paper, includes the addition of 2650 new disease terms, a 30% increase of textual definitions, and an expanding suite of disease classification hierarchies constructed through defined logical axioms.
Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre-including this research content-immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
Background Coronavirus Disease 2019 (COVID-19) results in increased inflammatory markers previously associated with atrial arrhythmias. However, little is known about their incidence or specificity in COVID-19, or their association with outcomes. We determined the incidence, predictors and outcomes of atrial fibrillation or flutter (AF/AFL) in patients hospitalized with COVID-19, or hospitalized with Influenza. Methods This is a retrospective analysis of 3,970 patients admitted with PCR-positive COVID-19 between 2/4/2020-4/22/2020 with manual review performed of 1,110. The comparator arm included 1,420 patients with influenza hospitalized between 1/1/2017-1/1/2020. Results Among 3970 inpatients with COVID-19, the incidence of AF/AFL was 10% (N=375) and in patients without a history of atrial arrhythmias, 4% (N=146). Patients with new-onset AF/AFL were older with increased inflammatory markers including Interleukin-6 (93 vs 68 pg/ml, P<0.01), and more myocardial injury (Troponin-I: 0.2 vs 0.06ng/ml, P<0.01). AF/AFL were associated with increased mortality (46% vs 26%, P<0.01). Manual review captured a somewhat higher incidence of AF/AFL (13%, N=140). Compared to inpatients with COVID-19, patients with Influenza (N=1420) had similar rates of AF/AFL (12%, n=163) but lower mortality. The presence of AF/AFL correlated with similarly increased mortality in both COVID-19 (RR 1.77) and Influenza (RR 1.78). Conclusions AF/AFL occurs in a subset of patients hospitalized with either COVID-19 or Influenza, and is associated with inflammation and disease severity in both infections. The incidence and associated increase in mortality in both cohorts suggests that AF/AFL in not specific to COVID-19, but is rather a generalized response to the systemic inflammation of severe viral illnesses.
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.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.