Presepsin Predicts Severity and Secondary Bacterial Infection in COVID-19 by Bioinformatics Analysis.

Introduction: Novel coronavirus pneumonia (COVID-19) is an acute respiratory disease caused by the novel coronavirus SARS-CoV-2. Severe and critical illness, especially secondary bacterial infection (SBI) cases, accounts for the vast majority of COVID-19-related deaths. However, the relevant biological indicators of COVID-19 and SBI are still unclear, which significantly limits the timely diagnosis and treatment. Methods: The differentially expressed genes (DEGs) between severe COVID-19 patients with SBI and without SBI were screened through the analysis of GSE168017 and GSE168018 datasets. By performing Gene Ontology (GO) enrichment analysis for significant DEGs, significant biological processes, cellular components, and molecular functions were selected. To understand the high-level functions and utilities of the biological system, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed. By analyzing protein-protein interaction (PPI) and key subnetworks, the core DEGs were found. Results: 85 DEGs were upregulated, and 436 DEGs were downregulated. The CD14 expression was significantly increased in the SBI group of severe COVID-19 patients (P < 0.01). The area under the curve (AUC) of CD14 in the SBI group in severe COVID-19 patients was 0.9429. The presepsin expression was significantly higher in moderate to severe COVID-19 patients (P < 0.05). Presepsin has a diagnostic value for moderate to severe COVID-19 with the AUC of 0.9732. The presepsin expression of COVID-19 patients in the nonsurvivors was significantly higher than that in the survivors (P < 0.05). Conclusion: Presepsin predicts severity and SBI in COVID-19 and may be associated with prognosis in COVID-19.

Bacterial and fungal co-infections among COVID-19 patients in intensive care unit.

This study aimed to investigate the frequency and characteristics of respiratory co-infections in COVID-19 patients in the intensive care unit (ICU). In this retrospective observational study, pathogens responsible for potential co-infections were detected by the bacterial culture, real-time polymerase chain reaction (RT-PCR), or serological fungal antigen tests. Demographic and clinical characteristics, as well as microbial results, were analyzed. Bacterial culture identified 56 (58.3%) positive samples for respiratory pathogens, with the most common bacteria being Burkholderia cepacia (18, 18.8%). RT-PCR detected 38 (76.0%) and 58 (87.9%) positive results in the severe and critical groups, respectively. Most common pathogens detected were Stenotrophomonas maltophilia (28.0%) and Pseudomonas aeruginosa (28.0%) in the severe group and S. maltophilia (45.5%) in the critical group. P. aeruginosa was detected more during the early stage after ICU admission. Acinetobacter baumannii and Staphylococcus aureus were more frequently identified during late ICU admission. Fungal serum antigens were more frequently positive in the critical group than in the severe group, and the positive rate of fungal serum antigens frequency increased with prolonged ICU stay. A high frequency of respiratory co-infections presented in ICU COVID-19 patients. Careful examinations and necessary tests should be performed to exclude these co-infections.

Analysis of clinical features and related factors of coronavirus disease 2019 in Shanghai

Objective • To explore the common clinical features of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)-infected local patients in Shanghai and their related influencing factors. Methods • A total of 320 patients admitted to Shanghai Public Health Clinical Center from January to March 2020 and diagnosed as having coronavirus disease 2019(COVID-19) were selected. Clinical data of the patients were collected to analyze their characteristics. Using the statistical operation formula of R language, the correlation analysis of hospitalization days, days of increased hypersensitive C-reactive protein concentration (allergic days), days of lung CT improvement (CT days), and days required for nucleic acid turning negative with the main clinical manifestations and laboratory data was carried out. The correlation factors affecting the above four variables were analyzed. Results • Among the 320 patients, the proportions of mild type, moderate type, serious type and critical type were 6.25%, 83.44%, 6.88% and 3.44%, respectively;91.25% of them had a history of exposure to Hubei. The proportions of fever, cough, sputum and fatigue were 79.06%, 46.56%, 21.56% and 15.31%, respectively. Spearman correlation analysis showed that the concentrations of lactate dehydrogenase, interleukin-2(IL-2) and IL-6 were positively correlated with the above four variables, respectively (all P<0.05), albumin concentration was negatively correlated with allergic days (P=0.018), and CD4+ cell count was negatively correlated with CT days and days required for nucleic acid turning negative (both P<0.05). Stepwise multiple linear regression analysis showed that procalcitonin (PCT) concentration was negatively correlated with hospitalization days, CT days and allergic days (both P<0.05), and disease type was positively correlated with hospitalization days, allergic days, CT days and days required for nucleic acid turning negative (all P<0.05). Conclusion • Moderate type is common in the local patients in Shanghai;fever, cough and fatigue are common symptoms, and most of the patients are accompanied by lung CT abnormalities. The therapeutic effect and prognosis of these patients are closely related to disease type, concentrations of PCT and IL-6, as well as CD4+ cell count.