Association between hopelessness and job burnout among Chinese nurses during the COVID-19 epidemic: The mediating role of career calling and the moderating role of social isolation.

Background: The COVID-19 pandemic has led to an increased workload and work pressure on nurses owing to the unpredictable changes during this challenging situation. Herein, we explored the relationship between hopelessness and job burnout in nurses working in China against the backdrop of the COVID-19 outbreak. Method: This was a cross-sectional study involving 1216 nurses in two hospitals in Anhui Province. The data was collected using an online survey. The mediation and moderation model was constructed, and the data was analyzed using SPSS PROCESS macro software. Results: Our results showed that the nurses had an average job burnout score of 1.75 ± 0.85. Further analysis revealed a negative correlation between hopelessness and career calling (r = -0.551, P < 0.01) and a positive correlation between hopelessness and job burnout (r = 0.133, P < 0.01). Additionally, a negative correlation was demonstrated between career calling and job burnout (r = -0.138, P < 0.01). Moreover, career calling strongly mediated (by 40.9%) the relationship between hopelessness and job burnout in the nurses. Finally, social isolation in the nurses was a moderating factor for the association between hopelessness and job burnout (ß = 0.028, t = 2.851, P < 0.01). Conclusion: Burnout severity in nurses increased during the COVID-19 pandemic. Career calling mediated the relationship between hopelessness and burnout, with greater burnout levels in nurses who experienced social isolation. Therefore, we suggest that job burnout in nurses can be improved by mitigating the effects of hopelessness and social isolation through psychological interventions and enhancing their sense of career calling through education to strengthen their professional identity.

Novel nucleocapsid protein-targeting phenanthridine inhibitors of SARS-CoV-2.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unprecedented in human history. As a major structural protein, nucleocapsid protein (NPro) is critical to the replication of SARS-CoV-2. In this work, 17 NPro-targeting phenanthridine derivatives were rationally designed and synthesized, based on the crystal structure of NPro. Most of these compounds can interact with SARS-CoV-2 NPro tightly and inhibit the replication of SARS-CoV-2 in vitro. Compounds 12 and 16 exhibited the most potent anti-viral activities with 50% effective concentration values of 3.69 and 2.18 µM, respectively. Furthermore, site-directed mutagenesis of NPro and Surface Plasmon Resonance (SPR) assays revealed that 12 and 16 target N-terminal domain (NTD) of NPro by binding to Tyr109. This work found two potent anti-SARS-CoV-2 bioactive compounds and also indicated that SARS-CoV-2 NPro-NTD can be a target for new anti-virus agents.

Predictive Score of Risk Associated with Progression of Patients with COVID-19 Pneumonia in Wuhan, China: the ALA Score.

Background The Coronavirus Disease 2019 (COVID-19) had become a Public Health Emergency of International Concern with more than 90 million confirmed cases worldwide. Therefore, this study aims to establish a predictive score model of progression to severe type in patients with COVID-19. Methods This is a retrospective cohort study of 151 patients with COVID-19 diagnosed by nucleic acid test or specific serum antibodies from February 13, 2020, to March 14, 2020, hospitalized in a COVID-19-designed hospital in Wuhan, China. Results Of the 151 patients with average age of 63 years, 64 patients were male (42.4%), and 29 patients (19.2%) were classified as severe group. Multivariate analysis showed that age > 65 years (odds ratio [OR] = 9.72, 95%CI: 2.92-32.31, P < 0.001), lymphocyte count ≤ 1.1 × 109/L (OR = 3.42, 95%CI: 1.24-9.41, P = 0.017) and AST > 35 U/L (OR = 3.19, 95%CI: 1.11-9.19, P = 0.032) were independent risk factors for the disease severity. The area under curve (AUC) of receiver operating characteristic curve of the probabilities of the composite continuous variable (age + lymphocyte + AST) is 0.796. Finally, a predictive score model called ALA was established, and its AUC was 0.83 (95%CI: 0.75-0.92). Using a cutoff value of 9.5 points, the positive and negative predictive values were 54.1% (38-70.1%) and 92.1% (87.2-97.1%), respectively. Conclusion The ALA score model can quickly identify severe patients with COVID-19, so as to help clinicians to better choose accurate management strategy.

Factors Associated with a Positive Severe Acute Respiratory Syndrome Coronavirus 2 Testing in Suspected Cases Presenting with Pneumonia: A Retrospective Cohort Study in a Single Medical Center.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a global emerging infectious disease. OBJECTIVES: To analyze the initial clinical characteristics of COVID-19 suspected and confirmed patients on admission in order to find out which kinds may be more likely to get positive nucleic acid testing results, and to explore the risk factors associated with all-cause death. METHODS: Medical records from 309 highly suspected cases with pneumonia were collected from February 13, 2020, to March 14, 2020, in a COVID-19-designated hospital of Wuhan. The majority of the clinical data were collected on the first day of hospital admission. RESULTS: Of 309 patients with median age 64 years (interquartile ranges [IQR], 53-72 years), 111 patients (35.9%) were confirmed by nucleic acid testing (median age 64 years, IQR: 56-71 years; 48 males). Of those 111 patients, 13 (11.7%) patients died. In multivariate analysis, factors associated with positive testing included fatigue (odds ratios [OR] = 3.14; 95% confidence interval [CI]: 1.88-5.24, p < 0.001), cough (OR = 0.55; 95% CI: 0.32-0.95, p = 0.032), no less than 1 comorbidity (OR = 1.77; 95% CI: 1.06-2.98, p = 0.030), and severe pneumonia (OR = 2.67; 95% CI: 1.20-5.97, p = 0.016). Furthermore, age, dyspnea, noneffective antibiotic treatment, white blood cell, lymphocyte, platelets, and organ dysfunction (e.g., higher lactate dehydrogenase) were significantly associated with all-cause in-hospital death in patients with COVID-19. CONCLUSION: Patients with severe forms of this disease were more likely to get positive results. Age and organ dysfunction were associated with a greater risk of death.

Numerical Study of Three Ventilation Strategies in a prefabricated COVID-19 inpatient ward.

Prefabricated inpatient wards have been proven to be an efficient alternative to quickly extend the caring capacity for patients. In this study, three typical ventilation strategies were studied using computational fluid dynamics in a prefabricated Coronavirus disease 2019 double-patient ward. Pollutants are the respiratory droplets and aerosols injected from two manikins. They are modelled as particles with different diameters (3 µm, 6 µm, 12 µm, 20 µm, 45 µm and 175 µm) by the Eulerian-Lagrangian model. Three ventilation strategies with an identical air change rate of 12.3 h-1 but different layouts of inlets and outlets are implemented. The flow field, flow structures and particle trajectories have been analysed and compared among the three ventilation strategies. The fate of particles is analysed and compared quantitatively. It is found that small particles (<20 µm) can move along with the main flow streams. Most of them are removed by ventilation to the outlet(s). Large particles (>45 µm) cannot move with the flow streams over a long path. Most of them deposit on solid surfaces in different regions of the ward in each ventilation strategy. Health workers should pay close attention to these polluted areas. Targeted cleaning of the polluted areas is necessary in a prefabricated inpatient ward. To promote the removal of some large particles (e.g., 45 µm) by the outlet(s), the outlet(s) should be installed inside the landing area of large particles and close to the polluted source(s).