ABSTRACT
Several descriptive studies have reported that higher neutrophil count (NC) may be correlated with poor prognosis in patients with confirmed COVID-19 infection. However, the findings from these studies are limited by methodology and data analysis. This study is a cohort study. We nonselectively and consecutively collected a total of 663 participants in a Chinese hospital from January 7 to February 28. Standardized and two-piecewise Cox regression model were employed to evaluate the association between baseline neutrophil count (bNC), neutrophil count change rate (NCR), and death. bNC had a U-shaped association with death. In the range of 0.1 to ≤1.49 × 109 /L (hazard ratio [HR] = 0.19, 95% confidence interval [CI] = 0.05-0.66) and >3.55 × 109 /L of bNC (HR = 2.82, 95% CI = 1.19-6.67), the trends on bNC with mortality were opposite. By recursive algorithm, the bNC at which the risk of the death was lower in the range of >1.49 to ≤3.55 × 109 /L (HR = 13.64, 95% CI = 0.25-74.71). In addition, we find that NCRs (NCR1 and NCR2) are not associated with COVID-19-related deaths. Compared with NCR, bNC has the potential to be used for early risk stratification in patients with COVID-19 infection. The relationship between bNC and mortality was U-shaped. The safe range of bNC was 1.64-4.0 × 109 /L. Identifying the correlation may be helpful for early risk stratification and medical decision-making.
Subject(s)
COVID-19/immunology , COVID-19/mortality , Neutrophils/immunology , SARS-CoV-2/immunology , China , Female , Hospitalization/statistics & numerical data , Humans , Lymphocyte Count , Male , Middle Aged , Prognosis , Retrospective Studies , Risk , Risk FactorsABSTRACT
Disasters such as an earthquake, a flood, and an epidemic usually lead to large numbers of casualties accompanied by disruption of the functioning of local medical institutions. A rapid response of medical assistance and support is required. Mobile hospitals have been deployed by national and international organizations at disaster situations in the past decades, which play an important role in saving casualties and alleviating the shortage of medical resources. In this paper, we briefly introduce the types and characteristics of mobile hospitals used by medical teams in disaster rescue, including the aspects of structural form, organizational form, and mobile transportation. We also review the practices of mobile hospitals in disaster response and summarize the problems and needs of mobile hospitals in disaster rescue. Finally, we propose the development direction of mobile hospitals, especially on the development of intelligence, rapid deployment capabilities, and modularization, which provide suggestions for further research and development of mobile hospitals in the future.
Subject(s)
Civil Defense/instrumentation , Disasters , Mobile Health Units/trends , Civil Defense/methods , Civil Defense/trends , HumansABSTRACT
PURPOSE: Huashi Baidu formula (HSBDF) was developed to treat the patients with severe COVID-19 in China. The purpose of this study was to explore its active compounds and demonstrate its mechanisms against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through network pharmacology and molecular docking. METHODS: All the components of HSBDF were retrieved from the pharmacology database of TCM system. The genes corresponding to the targets were retrieved using UniProt and GeneCards database. The herb-compound-target network was constructed by Cytoscape. The target protein-protein interaction network was built using STRING database. The core targets of HSBDF were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The main active compounds of HSBDF were docked with SARS-CoV-2 and angiotensin converting enzyme II (ACE2). RESULTS: Compound-target network mainly contained 178 compounds and 272 corresponding targets. Key targets contained MAPK3, MAPK8, TP53, CASP3, IL6, TNF, MAPK1, CCL2, PTGS2, etc. There were 522 GO items in GO enrichment analysis (p < .05) and 168 signaling pathways (p < .05) in KEGG, mainly including TNF signaling pathway, PI3K-Akt signaling pathway, NOD-like receptor signaling pathway, MAPK signaling pathway, and HIF-1 signaling pathway. The results of molecular docking showed that baicalein and quercetin were the top two compounds of HSBDF, which had high affinity with ACE2. CONCLUSION: Baicalein and quercetin in HSBDF may regulate multiple signaling pathways through ACE2, which might play a therapeutic role on COVID-19.