Premorbid Echocardiography And Risk of Hospitalization In COVID-19 (preprint)

Background: COVID-19 has caused an unprecedented global pandemic, with cardiovascular risk factors predicting outcomes. We investigated whether baseline trans-thoracic echocardiography could refine risk beyond clinical risk factors. Methods: Symptomatic COVID-19 positive (RT-PCR) adults across St Luke’s University Health Network between March 1st-October 31st 2021, with trans-thoracic echocardiography (TTE) within 15-180 days preceding COVID-19 positivity were selected. Demographic/clinical/echocardiographic variables were extracted from patients’ EHR and compared between groups stratified by disease severity. Logistic regression was used to identify independent predictors of hospitalization. Results: 192 patients were included. 87 (45.3%) required hospitalization, 34 (17.7%) suffered severe disease (need for ICU care/mechanical ventilation/in-hospital death). Age, co-morbidities, and several echocardiographic abnormalities were more prevalent in moderate-severe versus mild disease. On multivariate analysis, age (OR 1.039, 95% CI 1.011-1.067), coronary artery disease (OR 4.184, 95% CI 1.451-12.063), COPD (OR 6.886, 95% CI 1.396-33.959) and left atrial (LA) diameter ≥4.0cm (OR 2.379, 95% CI 1.031-5.493) predicted need for hospitalization. Model showed excellent discrimination (ROC AUC 0.809, 95% CI 0.746-0.873). Conclusion: Baseline LA enlargement independently predicts risk of hospitalization in COVID-19. When available, baseline LA enlargement could identify patients for 1) closer outpatient follow-up, and 2) counseling vaccine-hesitancy.

Computational investigation reveals that the mutant strains of SARS-CoV2 are highly infectious than wildtype (preprint)

Remarkable infectivity of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) is due to the rapid emergence of various strains, thus enable the virus to rule the world. Over the course of SARS-CoV2 pandemic, the scientific communities worldwide are responding to newly emerging genetic variants. However, the mechanism behind the persistent infection of these variants is still not known due to the paucity of study of these variants at molecular level. In this scenario, computational methods have immense utility in understanding the molecular and functional properties of different variants. Therefore, in this study various mutants (MTs) of SpikeS1 receptor binding domain (RBD) of highly infectious SARS-CoV2 strains were carried and elucidated the protein structure and dynamics using molecular dynamics (MD) approach. MD simulation study showed that all MTs exhibited stable structures with altered functional properties. Furthermore, the binding strength of different MTs along with WT (wildtype) was revealed through protein-protein docking and observed that MTs showed high binding affinities than WT. Hence, this study shed light on the molecular basis of infection caused by different variants of SARS-CoV2, which might play an important role in to cease the transmission and pathogenesis of virus and also implicate in rational designing of a specific drug.