Based on the social exchange theory, the aim of this study is to identify the association between job stress state anger, emotional exhaustion and job turnover intention. This study postulates that job related stress and state anger among nurses during COVID-19 subsequently leads to their job turnover intentions. In addition, the study also aims to see the mediating role of emotional exhaustion between COVID-19-related job stress, state anger, and turnover intentions. The sample of this study is gathered from 335 registered nurses working in Pakistani hospitals dealing with COVID-19-related patients. The interrelationships between variables are checked by using structural equation modeling through AMOS. Key findings confirm that COVID-19-related job stress and state anger had a significant effect on nurses’ turnover intentions. Furthermore, emotional exhaustion mediated the relationship between COVID-19-related job stress, state anger, and turnover intentions. There is a lack of research which has assessed the impact of Novel COVID-19-related job stress and state anger on nurses’ turnover intentions in hospitals, providing empirical evidence from a developing country-Pakistan. This study offers managerial implications for hospital management and health policymakers. Moreover, nursing managers need to pay attention to nurses’ turnover intentions who are facing the issue at the front line as patients receive their initial treatment from nurses in the COVID-19 outbreak.

COVID-19 is a rapidly disseminating infectious disease conferred by the World Health Organization (WHO) as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics data have been identified for patients with COVID-19, but mortality-related risk factors and a comprehensive clinical course of disease in a developing country have not been specifically defined. This retrospective, single-center cohort study involved all successive inpatients having a positive COVID-19 polymerase chain reaction (PCR), with deceased or discharged clinical outcomes from 1 January to 10 May 2021. Data were extracted from electronic medical records on demographic, clinical, radiological, and laboratory findings as well as complications faced and treatment provided during follow-up, involving serial samples for viral RNA identification, and compared between the dead and survivors. To investigate the risk factors associated with in-hospital mortality, we employed the multivariate logistic regression model. In this study, 2048 patients were involved, 1458 of whom were discharged, and 590 died in hospital. More than half of patients were identified as male with old age being the potential risk factor of mortality. Exactly 94.8% of all patients presented with fever at the time of admission. Several comorbidities were present in the study population, with the most frequent comorbidity being cardiovascular diseases (1177 of 2048) and hypertension (975 of 2048) followed by cerebrovascular disease and diabetes mellitus. Mortality rates for infected patients were observed as higher in severe patients (46.3%) compared with non-severe cases (26.1%) during a follow-up. Multivariate regression analysis showed a significant association of in-hospital mortality of patients with older age, presence of hypertension and cardiovascular diseases as underlying comorbidities, increased level of cardiac troponin I and d-dimer concentration on admission, as well as septicemia and ARDS as a complication during illness. To minimize the risk of death in COVID19 patients, as well as the risk of severe complications, urgent public health measures should be properly planned and implemented on those vulnerable populations. To detect early manifestations of clinical problems, thorough and regular follow-up is warranted.