Epidemiology and infection
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Observational Study
Laboratory findings and a combined multifactorial approach to predict death in critically ill patients with COVID-19: a retrospective study.
To describe the laboratory findings of cases of death with coronavirus disease 2019 (COVID-19) and to establish a scoring system for predicting death, we conducted this single-centre, retrospective, observational study including 336 adult patients (≥18 years old) with severe or critically ill COVID-19 admitted in two wards of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology in Wuhan, who had definite outcomes (death or discharge) between 1 February 2020 and 13 March 2020. Single variable and multivariable logistic regression analyses were performed to identify mortality-related factors. We combined multiple factors to predict mortality, which was validated by receiver operating characteristic curves. ⋯ The combined prediction model was developed by these factors with a sensitivity of 100.0% and specificity of 97.2%. In conclusion, decreased Lymr, elevated BUN, and raised DD were found to be in association with death outcomes in critically ill patients with COVID-19. A scoring system was developed to predict the clinical outcome of these patients.
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This study aims to identify the risk factors associated with mortality and survival of COVID-19 cases in a state of the Brazilian Northeast. It is a historical cohort with a secondary database of 2070 people that presented flu-like symptoms, sought health assistance in the state and tested positive to COVID-19 until 14 April 2020, only moderate and severe cases were hospitalised. The main outcome was death as a binary variable (yes/no). ⋯ Mortality was enhanced by the variables: elderly (HR 3.6; 95% CI 2.3-5.8; P < 0.001), neurological diseases (HR 3.9; 95% CI 1.9-7.8; P < 0.001), pneumopathies (HR 2.6; 95% CI 1.4-4.7; P < 0.001) and cardiovascular diseases (HR 8.9; 95% CI 5.4-14.5; P < 0.001). In conclusion, mortality by COVID-19 in Ceará is similar to countries with a large number of cases of the disease, although deaths occur later. Elderly people and comorbidities presented a greater risk of death.
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The COVID-19 pandemic is exerting major pressures on society, health and social care services and science. Understanding the progression and current impact of the pandemic is fundamental to planning, management and mitigation of future impact on the population. Surveillance is the core function of any public health system, and a multi-component surveillance system for COVID-19 is essential to understand the burden across the different strata of any health system and the population. ⋯ Monitoring changes in healthcare utilisation is key to interpreting COVID-19 surveillance data, which can then be used to better understand the impact of the pandemic on the population. Syndromic surveillance systems have had to adapt to encompass these changes, whilst also innovating by taking opportunities to work with data providers to establish new data feeds and develop new COVID-19 indicators. These developments are supporting the current public health response to COVID-19, and will also be instrumental in the continued and future fight against the disease.
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At the present time, COVID-19 is spreading rapidly [1]. The global prevention and control of COVID-19 is focused on the estimation of the relevant incubation period, basic reproduction number (R0), effective reproduction number (Rt) and death risk. Although the prevention and control of COVID-19 requires a reliable estimation of the relevant incubation period, R0, Rt and death risk. ⋯ So far, people have not paid enough attention to asymptomatic carriers. The asymptomatic carriers discussed in this study are recessive infections, that is, those who have never shown symptoms after onset of infection. We will discuss three aspects: detection, infectivity and proportion of healthy carriers.