Articles: coronavirus.
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The SARS-CoV-2 pandemic has had profound implications on healthcare institutions. ⋯ Spinal injury continues to occur across almost all categories, albeit at considerably reduced numbers. RTAs and falls remained the most common MOI. Awareness needs to be drawn to the reduction of malignancy-related referrals to dissuade people with such symptoms from avoiding presentation to hospital over periods of social restrictions.
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It is still not known how an immunosuppressive state affects the response to coronavirus disease 2019 (COVID-19) in children and adolescents. The aim of this study was to evaluate clinical characteristics, outcomes, and follow-up results of COVID-19 in pediatric patients with a history of immunocompromise or malignancy, retrospectively. ⋯ Immunocompromised children and adolescents with COVID-19 should be monitored closely, especially those with an end-stage malignancy, low LYM count, or high CRP and ferritin levels.
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Observational Study
Clusters of inflammation in COVID-19: descriptive analysis and prognosis on more than 15,000 patients from the Spanish SEMI-COVID-19 Registry.
Uncontrolled inflammation following COVID-19 infection is an important characteristic of the most seriously ill patients. The present study aims to describe the clusters of inflammation in COVID-19 and to analyze their prognostic role. This is a retrospective observational study including 15,691 patients with a high degree of inflammation. ⋯ In detail and, having cluster C1 as reference, the model revealed a worse prognosis for all other clusters: C2 (OR = 1.30, p = 0.001), C3 (OR = 1.14, p = 0.178), C4 (OR = 2.28, p < 0.001), C5 (OR = 1.07, p = 0.479), C6 (OR = 2.29, p < 0.001), and C7 (OR = 1.28, p = 0.001). We identified 7 groups based on the presence of lymphopenia, elevated CRP, LDH, ferritin, and D-dimer at the time of hospital admission for COVID-19. Clusters C4 (lymphopenia + LDH + CRP), C6 (ferritin + D-dimer), and C7 (D-dimer) had the worst prognosis in terms of in-hospital mortality.
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Protective long-term immunity following coronavirus disease 2019 (COVID-19) is unclear. The study evaluated the relationship between the vaccination status and risk factors in the re-infection of patients with a diagnosis of COVID-19 who reported to the Public Health Management System in a province in south-eastern Turkey. ⋯ We are concerned that the re-infection rates and mortality may increase due to new variant strains. Vaccination is the greatest weapon against progression to critical illness in re-infections, even with existing mutations. Therefore, it is important for those without a full vaccination schedule to be vaccinated, even if they have been previously infected.
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The effect of socio-economic factors, ethnicity, and other factors, on the morbidity and mortality of COVID-19 at the sub-population-level, rather than at the individual level, and their temporal dynamics, is only partially understood. Fifty-three county-level features were collected between 4/2020 and 11/2020 from 3,071 US counties from publicly available data of various American government and news websites: ethnicity, socio-economic factors, educational attainment, mask usage, population density, age distribution, COVID-19 morbidity and mortality, presidential election results, and ICU beds. We trained machine learning models that predict COVID-19 mortality and morbidity using county-level features and then performed a SHAP value game theoretic importance analysis of the predictive features for each model. ⋯ Thus, socio-economic features such as ethnicity, education, and economic disparity are the major factors for predicting county-level COVID-19 mortality rates. Between counties, low variance factors (e.g., age) are not meaningful predictors. The inversion of some correlations over time can be explained by COVID-19 spreading from urban to rural areas.