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Background: To determine the role of diabetes mellitus (DM) in the coronavirus disease 2019 (COVID-19), we explored the clinical characteristics of patients with DM and compared risk factors such as age, glycemic control, and medications to those without DM. Methods: This was a retrospective cohort study of 117 confirmed patients with COVID-19 which conducted at a tertiary hospital in Daegu, South Korea. The primary outcome was defined as the severe and critical outcome (SCO), of which the composite out comes of acute respiratory distress syndrome, septic shock, intensive care unit care, and 28-day mortality. We analyzed what clini cal features and glycemic control-related factors affect the prognosis of COVID-19 in the DM group. Results: After exclusion, 110 participants were finally included. DM patients (n=29) was older, and showed higher blood pres sure compared to non-DM patients. DM group showed higher levels of inflammation-related biomarkers and severity score, and highly progressed to SCO. After adjustment with other risk factors, DM increased the risk of SCO (odds ratio [OR], 10.771; P

Supplemental Digital Content is available in the text., Objective This study aimed to investigate the relationship between blood pressure variability (BPV) and clinical outcomes in patients with coronavirus disease 2019 (COVID-19) and hypertension. Methods A total of 136 patients hospitalized with COVID-19 were enrolled in this study. Patients were grouped according to the presence of hypertension and BPV. Mean arterial pressure (MAP) measured at 8 a.m. and 8 p.m. was analyzed, and BPV was calculated as the coefficient of variation of MAP (MAPCV). High BPV was defined as MAPCV values above the median. We compared the age, level of C-reactive protein (CRP), creatine kinase-MB (CK-MB), N-terminal pro-B type natriuretic peptide (NT-proBNP), creatinine and in-hospital mortality and investigated the relationship among the groups. Results COVID-19 patients with hypertension were older (70 ± 12 vs. 53 ± 17 years; P < 0.001), had higher levels of CRP (9.4 ± 9.2 vs. 5.3 ± 8.2 mg/dL; P = 0.009), MAPCV (11.4 ± 4.8 vs. 8.9 ± 3.2; P = 0.002), and higher in-hospital mortality (19.6% vs. 5.9%; P = 0.013) than those without hypertension. There was a proportional relationship between BPV and age, levels of CRP, CK-MB, NT-proBNP, creatinine and in-hospital mortality (all, P < 0.05). In Cox regression analysis, advanced age [≥80 years, hazard ratio (HR) 10.4, 95% confidence interval (CI) 2.264–47.772, P = 0.003] and higher MAPCV (HR 1.617, 95% CI, 1.281–2.040, P < 0.001) were significantly associated with in-hospital mortality. Conclusion High BPV in COVID-19 patients with hypertension is significantly associated with in-hospital mortality. Advanced age and systemic inflammation are proportional to high BPV. Additional attention is needed for COVID-19 patients with hypertension and high BPV.

Background It is difficult to distinguish subtle differences shown in computed tomography (CT) images of coronavirus disease 2019 (COVID-19) and bacterial pneumonia patients, which often leads to an inaccurate diagnosis. It is desirable to design and evaluate interpretable feature extraction techniques to describe the patient's condition. Methods This is a retrospective cohort study of 170 confirmed patients with COVID-19 or bacterial pneumonia acquired at Yeungnam University Hospital in Daegu, Korea. The Lung and lesion regions were segmented to crop the lesion into 2D patches to train a classifier model that could differentiate between COVID-19 and bacterial pneumonia. The K-means algorithm was used to cluster deep features extracted by the trained model into 20 groups. Each lesion patch cluster was described by a characteristic imaging term for comparison. For each CT image containing multiple lesions, a histogram of lesion types was constructed using the cluster information. Finally, a Support Vector Machine classifier was trained with the histogram and radiomics features to distinguish diseases and severity. Results The 20 clusters constructed from 170 patients were reviewed based on common radiographic appearance types. Two clusters showed typical findings of COVID-19, with two other clusters showing typical findings related to bacterial pneumonia. Notably, there is one cluster that showed bilateral diffuse ground-glass opacities (GGOs) in the central and peripheral lungs and was considered to be a key factor for severity classification. The proposed method achieved an accuracy of 91.2% for classifying COVID-19 and bacterial pneumonia patients with 95% reported for severity classification. The CT quantitative parameters represented by the values of cluster 8 were correlated with existing laboratory data and clinical parameters. Conclusion Deep chest CT analysis with constructed lesion clusters revealed well-known COVID-19 CT manifestations comparable to manual CT analysis. The constructed histogram features improved accuracy for both diseases and severity classification, and showed correlations with laboratory data and clinical parameters. The constructed histogram features can provide guidance for improved analysis and treatment of COVID-19., Graphical Abstract

Sterol regulatory element binding protein-2 (SREBP-2) is activated by cytokines or pathogen, such as virus or bacteria, but its association with diminished cholesterol levels in COVID-19 patients is unknown. Here, we evaluated SREBP-2 activation in peripheral blood mononuclear cells of COVID-19 patients and verified the function of SREBP-2 in COVID-19. Intriguingly, we report the first observation of SREBP-2 C-terminal fragment in COVID-19 patients’ blood and propose SREBP-2 C-terminal fragment as an indicator for determining severity. We confirmed that SREBP-2-induced cholesterol biosynthesis was suppressed by Sestrin-1 and PCSK9 expression, while the SREBP-2-induced inflammatory responses was upregulated in COVID-19 ICU patients. Using an infectious disease mouse model, inhibitors of SREBP-2 and NF-κB suppressed cytokine storms caused by viral infection and prevented pulmonary damages. These results collectively suggest that SREBP-2 can serve as an indicator for severity diagnosis and therapeutic target for preventing cytokine storm and lung damage in severe COVID-19 patients.

Background Since its first detection in December 2019, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 infection has spread rapidly around the world. Although there have been several studies investigating prognostic factors for severe COVID-19, there have been no such studies in Korea. Methods We performed a retrospective observational study of 110 patients with confirmed COVID-19 hospitalized at a tertiary hospital in Daegu, Korea. Demographic, clinical, laboratory, and outcome data were collected and analyzed. Severe disease was defined as a composite outcome of acute respiratory distress syndrome, intensive care unit care, or death. Results Diabetes mellitus (odds ratio [OR], 19.15; 95% confidence interval [CI], 1.90–193.42; P = 0.012), body temperature ≥ 37.8°C (OR, 10.91; 95% CI, 1.35–88.36; P = 0.025), peripheral oxygen saturation < 92% (OR, 33.31; 95% CI, 2.45–452.22; P = 0.008), and creatine kinase-MB (CK-MB) > 6.3 (OR, 56.84; 95% CI, 2.64–1,223.78, P = 0.010) at admission were associated with higher risk of severe COVID-19. The likelihood of development of severe COVID-19 increased with an increasing number of prognostic factors. Conclusion In conclusion, we found that diabetes mellitus, body temperature ≥ 37.8°C, peripheral oxygen saturation < 92%, and CK-MB > 6.3 are independent predictors of severe disease in hospitalized COVID-19 patients. Appropriate assessment of prognostic factors and close monitoring to provide the necessary interventions at the appropriate time in high-risk patients may reduce the case fatality rate of COVID-19., Graphical Abstract

Background The case fatality rate of coronavirus disease 2019 (COVID-19) is estimated to be between 4.3% and 11.0%. Currently there is no effective antiviral treatment for COVID-19. Thus, early recognition of patients at high risk is important. Methods We performed a retrospective observational study of 110 patients with severe acute respiratory syndrome coronavirus 2 infection. We compared the effectiveness of three scoring systems: the Systemic Inflammatory Response Syndrome (SIRS), quick Sequential Organ Failure Assessment (qSOFA), and National Early Warning Score (NEWS) systems, for predicting the prognosis of COVID-19. The area under the receiver operating characteristic curve (AUROC) was used for these assessments, and Kaplan-Meier survival curves were used to identify the cumulative risk for 28-day mortality according to the NEWS stratification. Results For predicting 28-day mortality, NEWS was superior to qSOFA (AUROC, 0.867 vs. 0.779, P < 0.001), while there was no significant difference between NEWS and SIRS (AUROC, 0.867 vs. 0.639, P = 0.100). For predicting critical outcomes, NEWS was superior to both SIRS (AUROC, 0.918 vs. 0.744, P = 0.032) and qSOFA (AUROC, 0.918 vs. 0.760, P = 0.012). Survival time was significantly shorter for patients with NEWS ≥ 7 than for patients with NEWS < 7. Conclusion Calculation of the NEWS at the time of hospital admission can predict critical outcomes in patients with COVID-19. Early intervention for high-risk patients can thereby improve clinical outcomes in COVID-19 patients., Graphical Abstract

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on a global scale urges prompt and effective countermeasures. Recently, a study has reported that coronavirus disease-19 (COVID-19), the disease caused by SARS-CoV-2 infection, is associated with a decrease in albumin level, an increase in NETosis, blood coagulation, and cytokine level. Here, we present drug-loaded albumin nanoparticles as a therapeutic agent to resolve the clinical outcomes observed in severe SARS-CoV-2 patients. PEGylated nanoparticle albumin-bound (PNAB) was used to promote prolonged bioactivity of steroidal ginsenoside saponins, PNAB-Rg6 and PNAB-Rgx365. Our data indicate that the application of PNAB-steroidal ginsenoside can effectively reduce histone H4 and NETosis-related factors in the plasma, and alleviate SREBP2-mediated systemic inflammation in the PBMCs of SARS-CoV-2 ICU patients. The engineered blood vessel model confirmed that these drugs are effective in suppressing blood clot formation and vascular inflammation. Moreover, the animal model experiment showed that these drugs are effective in promoting the survival rate by alleviating tissue damage and cytokine storm. Altogether, our findings suggest that these PNAB-steroidal ginsenoside drugs have potential applications in the treatment of symptoms associated with severe SARS-CoV-2 patients, such as coagulation and cytokine storm.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of coronavirus not previously identified in humans. Globally, the number of confirmed cases and mortality rates of coronavirus disease 2019 (COVID-19) have risen dramatically. Currently, there are no FDA-approved antiviral drugs and there is an urgency to develop treatment strategies that can effectively suppress SARS-CoV-2-mediated cytokine storms, acute respiratory distress syndrome (ARDS), and sepsis. As symptoms progress in patients with SARS-CoV-2 sepsis, elevated amounts of cell-free DNA (cfDNA) are produced, which in turn induce multiple organ failure in these patients. Furthermore, plasma levels of DNase-1 are markedly reduced in SARS-CoV-2 sepsis patients. In this study, we generated recombinant DNase-1-coated polydopamine-poly(ethylene glycol) nanoparticulates (named long-acting DNase-1), and hypothesized that exogenous administration of long-acting DNase-1 may suppress SARS-CoV-2-mediated neutrophil activities and the cytokine storm. Our findings suggest that exogenously administered long-acting nanoparticulate DNase-1 can effectively reduce cfDNA levels and neutrophil activities and may be used as a potential therapeutic intervention for life-threatening SARS-CoV-2-mediated illnesses.

Although some information on the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and a few selected cases has been reported, data on the clinical characteristics and outcomes of patients hospitalized therewith in South Korea are lacking. We conducted a retrospective single-center study of 98 consecutive hospitalized patients with confirmed SARS-CoV-2 infection at Yeungnam University Medical Center in Daegu, South Korea. Sixty patients were women (61.2%), and the mean age was 55.4±17.1 years. Thirteen patients (13.3%) were treated in the intensive care unit (ICU). The mean interval from symptom onset to hospitalization was 7.7±4.5 days. Patients who received ICU care were significantly older and were more likely to have diabetes mellitus. The National Early Warning Score on the day of admission was significantly higher in patients requiring ICU care. Acute respiratory distress syndrome (13/13 patients; 100%), septic shock (9/13; 69.2%), acute cardiac injury (9/13; 69.2%), and acute kidney injury (8/13; 61.5%) were more common in patients who received ICU care. All patients received antibiotic therapy, and most (97/98 patients; 99.0%) received antiviral therapy (lopinavir/ritonavir). Hydroxychloroquine was used in 79 patients (80.6%), and glucocorticoid therapy was used in 18 patients (18.4%). In complete blood counts, lymphopenia was the most common finding (40/98 patients; 40.8%). Levels of all proinflammatory cytokines were significantly higher in ICU patients. As of March 29, 2020, the mortality rate was 5.1%. Here, we report the clinical characteristics and laboratory findings of SARS-CoV-2 patients in South Korea up to March 29, 2020.