Work as a Frontline Volunteer During the COVID-19 Outbreak in Hubei, China: A Qualitative Inquiry of Male Nurses.

BACKGROUND: During the coronavirus (COVID-19) outbreak in 2019, an increased large number of male nurses volunteered for frontline assignment. Their excellent performance suggests that male nurses have several advantages over female nurses. However, research into the activities of Chinese male nurses engaged in frontline work during the COVID-19 pandemic remains limited. PURPOSE: This study was designed to summarize the reflections of male nurses on their experiences while volunteering for frontline COVID-19 duty in Hubei, China. METHODS: An interpretative qualitative descriptive study was conducted from May to July 2020 on male nurses who had volunteered for frontline COVID-19 duty in Hubei. Twelve male nurses were selected using a purposive sampling method. Data were collected using semistructured interviews, transcribed verbatim, and analyzed using thematic analysis. RESULTS: Four main themes and 11 subthemes were identified, including (a) changing the way of thinking at work (four subthemes), (b) clarity regarding career development (three subthemes), (c) change in life philosophy (two subthemes), and (d) personal growth (two subthemes). CONCLUSIONS: The experience of volunteering during the COVID-19 public health emergency influenced the male nurses positively in terms of improved organizational, management, and decision-making skills as well as improved performance. The beneficial attributes of male nurses should be taken into consideration when developing management policies related to nursing personnel.

Computed tomography–based COVID–19 triage through a deep neural network using mask–weighted global average pooling

Background There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore, this study aimed to develop a novel deep-learning approach for COVID-19 triage based on chest computed tomography (CT) images, including normal, pneumonia, and COVID-19 cases. Methods A total of 2,809 chest CT scans (1,105 COVID-19, 854 normal, and 850 non-3COVID-19 pneumonia cases) were acquired for this study and classified into the training set (n = 2,329) and test set (n = 480). A U-net-based convolutional neural network was used for lung segmentation, and a mask-weighted global average pooling (GAP) method was proposed for the deep neural network to improve the performance of COVID-19 classification between COVID-19 and normal or common pneumonia cases. Results The results for lung segmentation reached a dice value of 96.5% on 30 independent CT scans. The performance of the mask-weighted GAP method achieved the COVID-19 triage with a sensitivity of 96.5% and specificity of 87.8% using the testing dataset. The mask-weighted GAP method demonstrated 0.9% and 2% improvements in sensitivity and specificity, respectively, compared with the normal GAP. In addition, fusion images between the CT images and the highlighted area from the deep learning model using the Grad-CAM method, indicating the lesion region detected using the deep learning method, were drawn and could also be confirmed by radiologists. Conclusions This study proposed a mask-weighted GAP-based deep learning method and obtained promising results for COVID-19 triage based on chest CT images. Furthermore, it can be considered a convenient tool to assist doctors in diagnosing COVID-19.

Computed tomography-based COVID-19 triage through a deep neural network using mask-weighted global average pooling.

Background: There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore, this study aimed to develop a novel deep-learning approach for COVID-19 triage based on chest computed tomography (CT) images, including normal, pneumonia, and COVID-19 cases. Methods: A total of 2,809 chest CT scans (1,105 COVID-19, 854 normal, and 850 non-3COVID-19 pneumonia cases) were acquired for this study and classified into the training set (n = 2,329) and test set (n = 480). A U-net-based convolutional neural network was used for lung segmentation, and a mask-weighted global average pooling (GAP) method was proposed for the deep neural network to improve the performance of COVID-19 classification between COVID-19 and normal or common pneumonia cases. Results: The results for lung segmentation reached a dice value of 96.5% on 30 independent CT scans. The performance of the mask-weighted GAP method achieved the COVID-19 triage with a sensitivity of 96.5% and specificity of 87.8% using the testing dataset. The mask-weighted GAP method demonstrated 0.9% and 2% improvements in sensitivity and specificity, respectively, compared with the normal GAP. In addition, fusion images between the CT images and the highlighted area from the deep learning model using the Grad-CAM method, indicating the lesion region detected using the deep learning method, were drawn and could also be confirmed by radiologists. Conclusions: This study proposed a mask-weighted GAP-based deep learning method and obtained promising results for COVID-19 triage based on chest CT images. Furthermore, it can be considered a convenient tool to assist doctors in diagnosing COVID-19.

Thrombosis after SARS-CoV2 infection or COVID-19 vaccination: will a nonpathologic anti-PF4 antibody be a solution?-A narrative review.

The coronavirus disease 2019 (COVID-19) pandemic was triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a previously unknown strain of coronavirus. To fully understand the consequences and complications of SARS-CoV-2 infections, we have reviewed current literature on coagulation dysfunctions that are related to the disease and vaccination. While COVID-19 is more commonly considered as a respiratory illness, studies indicate that, in addition to respiratory illness, a coagulation dysfunction may develop in individuals after the initial infection, placing them at the risk of developing thrombotic events. Patients who died of COVID-19 had higher levels of D-dimer, a biomarker for blood clot formation and breakdown. Effective treatments for coagulation dysfunctions are critically needed to improve patient survival. On the other hand, antibodies against platelet factor 4 (PF4)/heparin may be found in patients with rare instances of vaccine-induced immunological thrombotic thrombocytopenia (VITT) following vaccination with adenovirus-based vaccines. VITT is characterized by atypical thrombosis and thrombocytopenia, similar to immune-mediated heparin-induced thrombocytopenia (HIT), but with no need for heparin to trigger the immune response. Although both adenovirus-based and mRNA-based vaccines express the Spike protein of SARS-CoV-2, VITT is exclusively related to adenovirus-based vaccines. Due to the resemblance with HIT, the use of heparin is highly discouraged against treating patients with thrombotic thrombocytopenia after SARS-CoV-2 infection or with VITT after vaccination. Intravenous immunoglobulin therapy coupled with anticoagulation is recommended instead. The well-studied anti-PF4 monoclonal antibody RTO, which does not induce pathologic immune complexes in the presence of heparin and has been humanized for a potential treatment modality for HIT, may provide a nonanticoagulant HIT-specific solution to the problem of increased blood coagulation after SARS-CoV-2 infection or the VITT after immunization.

Computational View toward the Inhibition of SARS-CoV-2 Spike Glycoprotein and the 3CL Protease.

Since the outbreak of the 2019 novel coronavirus disease (COVID-19), the medical research community is vigorously seeking a treatment to control the infection and save the lives of severely infected patients. The main potential candidates for the control of viruses are virally targeted agents. In this short letter, we report our calculations on the inhibitors for the SARS-CoV-2 3CL protease and the spike protein for the potential treatment of COVID-19. The results show that the most potent inhibitors of the SARS-CoV-2 3CL protease include saquinavir, tadalafil, rivaroxaban, sildenafil, dasatinib, etc. Ergotamine, amphotericin b, and vancomycin are most promising to block the interaction of the SARS-CoV-2 S-protein with human ACE-2.

Structural Features and PF4 Functions that Occur in Heparin-Induced Thrombocytopenia (HIT) Complicated by COVID-19.

Platelet factor 4 (PF4, CXCL4) is a small chemokine protein released by activated platelets. Although a major physiological function of PF4 is to promote blood coagulation, this cytokine is involved in innate and adaptive immunity in events when platelets are activated in response to infections. Coronavirus disease 2019 (COVID-19) patients have abnormal coagulation activities, and severe patients develop higher D-dimer levels. D-dimers are small protein products present in the blood after blood clots are degraded by fibrinolysis. To prevent clotting, heparin is often clinically used in COVID-19 patients. Some clinical procedures for the management of COVID-19 patients may include extracorporeal membrane oxygenation (ECMO) and renal replacement therapy (CRRT), which also require the use of heparin. Anti-PF4 antibodies are frequently detected in severe patients and heparin-induced thrombocytopenia (HIT) can also be observed. PF4 and its role in HIT as well as in pathologies seen in COVID-19 patients define a potential therapeutic option of using blocking antibodies in the treatment of COVID-19.

The absorbing filter Oxiris in severe coronavirus disease 2019 patients: A case series.

Hypercytokines cause acute respiratory distress syndrome (ARDS) in coronavirus disease 2019 (COVID-19) patients, which is the main reason for intensive care unit treatment and the leading cause of death in COVID-19 patients. Cytokine storm is a critical factor in the development of ARDS. This study evaluated the efficacy and safety of Oxiris filter in the treatment of COVID-19 patients. Five patients with COVID-19 who received continuous renal replacement therapy (CRRT) in Henan provincial people's hospital between January 23, 2019 and March 28, 2020, were enrolled in this study. Heart rate (HR), mean arterial pressure (MAP), oxygenation index (PaO2 /FiO2 ), renal function, C-reactive protein (CRP), cytokines, procalcitonin (PCT), acute physiology and chronic health evaluation II (APACHE II), sequential organ failure score (SOFA), and prognosis were compared after CRRT. Five COVID-19 patients, three males and two females, aged 70.2 ± 19.6 years, were enrolled. After treatment, HR (101.4 ± 14.08 vs. 83.8 ± 6.22 bpm/min), CRP (183 ± 25.21 vs. 93.78 ± 70.81 mg/L), IL-6 (3234.49 (713.51, 16038.36) vs. 181.29 (82.24, 521.39) pg/mL), IL-8 (154.86 (63.97, 1476.1) vs. 67.19 (27.84, 85.57) pg/mL), and IL-10 (17.43 (9.14, 41.22) vs. 4.97 (2.39, 8.70) pg/mL), APACHE II (29 ± 4.92 vs. 18.4 ± 2.07), and SOFA (17.2 ± 1.92 vs. 11.2 ± 3.4) significantly decreased (P < .05), while MAP (75.8 ± 4.92 vs. 85.8 ± 6.18 mm Hg), and PaO2 /FiO2 (101.2 ± 7.49 vs. 132.6 ± 26.15 mm Hg) significantly increased (P < .05). Among the five patients, negative conversion of nucleic acid test was found in three cases, while two cases died. No adverse events occurred during the treatment. Our study observed a reduced level of overexpressed cytokines, stabilization of hemodynamic status, and staged improvement of organ function during the treatment with Oxiris filter.

Systematic Pharmacological Strategies to Explore the Regulatory Mechanism of Ma Xing Shi Gan Decoction on COVID-19

OBJECTIVE: To use systematic pharmacological strategies to explore the regulatory mechanisms of Ma Xing Shi Gan Decoction (MXSGD) against the coronavirus disease 2019 (COVID-19). METHODS: Data on the compounds and targets of MXSGD were collected from the Traditional Chinese Medicene Systems Parmacology Database and Analysis Platform (TCMSP) and TCM Databases@Taiwan. Data on ACE2-related targets and the protein-protein interaction (PPI) were collected from the String database. The Cytoscape 3.7.2 was used to construct and analyze the networks. The DAVID platform was used for Gene Ontology (GO) and pathway enrichment analyses. RESULTS: Data on 272 MXSGD targets and 21 SARS-CoV-2 potential targets were collected. Four networks were constructed and analyzed based on the data: (1) compound-target network of MXSGD;(2) MXSGD-SARS-CoV-2-PPI network;(3) cluster of MXSGD-SARS-CoV-2-PPI network;(4) Herb-Pathway-Target network. The core targets included AKT1, MAPK3, IL-6, TP53, VEGFA, TNF, CASP3, EGFR, EGF and MAPK1. The antiviral biological processes were inflammatory responses (inflammatory cells, inflammatory cytokines and their signaling pathways), immune responses (T cells, monocytes, B cells and other immune cells), immune factors (IFN-γ, TNF-α and so on), virus defense, humoral immunity and mucosal innate immune response. The antivirus-related signaling pathways included TNF, NOD-like receptor, FoxO, PI3K-AKT and Toll-like receptor signaling pathways. CONCLUSIONS: MXSGD can control disease progression by regulating multiple compounds and targets;it can reduce inflammation and balance immunity by regulating several proteins that interact with ACE2 and signaling pathways closely related to disease development.