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Background: The cardiac manifestations of coronavirus disease 2019 (COVID-19) patients with cardiovascular disease (CVD) remain unclear. We aimed to investigate the prognostic value of echocardiographic parameters in patients with COVID-19 infection and underlying CVD. Methods: One hundred fifty-seven consecutive hospitalized COVID-19 patients were enrolled. The left ventricular (LV) and right ventricular (RV) structure and function were assessed using bedside echocardiography. Results: Eighty-nine of the 157 patients (56.7%) had underlying CVD. Compared with patients without CVD, those with CVD had a higher mortality (22.5 vs. 4.4%, p = 0.002) and experienced more clinical events including acute respiratory distress syndrome, acute heart injury, or deep vein thrombosis. CVD patients presented with poorer LV diastolic and RV systolic function compared to those without CVD. RV dysfunction (30.3%) was the most frequent, followed by LV diastolic dysfunction (9.0%) and LV systolic dysfunction (5.6%) in CVD patients. CVD patients with high-sensitivity troponin I (hs-TNI) elevation or requiring mechanical ventilation therapy demonstrated worsening RV function compared with those with normal hs-TNI or non-intubated patients, whereas LV systolic or diastolic function was similar. Impaired RV function was associated with elevated hs-TNI level. RV function and elevated hs-TNI level were independent predictors of higher mortality in COVID-19 patients with CVD. Conclusions: Patients with COVID-19 infection and underlying CVD displayed impaired LV diastolic and RV function, whereas LV systolic function was normal in most patients. Importantly, RV function parameters are predictive of higher mortality.
Pubmed ID: 33796573
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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