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EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321205


Background: Since December 2019, COVID-19 has emerged in Wuhan, China and spread globally. As of now, there is still no explicit therapeutic regimen and the use of corticosteroid is also controversial. We aimed to explore the effectiveness of corticosteroid and provide evidence for the rational use of corticosteroid in different patients with COVID-19.Methods In this multi-centered, retrospective study, we extracted the clinical data of 649 cases with COVID-19 with definite outcome (discharged or dead) from 14 hospitals in Hubei province, and evaluated the clinical characteristics, treatment regimens, and their association with outcomes.Results Ninety-five of 649 patients had died. Older male patients with comorbidities had an increased risk of death and more obvious abnormalities in clinical indicators. Corticosteroid, γ-globulin treatment and invasive ventilation were more frequently used in non-survivors. Survivors with corticosteroid treatment had a prolonged hospitalization. The median time duration for temperature restore for non-survivors after corticosteroid treatment was longer than that of both survivors. The lymphocyte count on admission was lower in the patients treated with corticosteroids compared to those without corticosteroid treatment. Lymphocyte count recovered significantly after corticosteroid treatment in survivors, but not in non-survivors.Conclusions The responses to corticosteroid treatment were different in COVID-19 patients with different outcomes. The surviving patients with relatively lower lymphocyte count were more likely to be given corticosteroids. For non-survivors, the lymphocyte count was too low and the effect of corticosteroids was poor. Survivors under corticosteroid treatment had a prolonged hospitalization, but had a recovery of lymphocytes. The recovery of lymphocyte count and temperature after corticosteroid treatment may be used as predictors of prognosis of patients with COVID-19.

Nonlinear Dyn ; 101(3): 1527-1543, 2020.
Article in English | MEDLINE | ID: covidwho-706095


COVID-19 was declared as a pandemic by the World Health Organization on March 11, 2020. Here, the dynamics of this epidemic is studied by using a generalized logistic function model and extended compartmental models with and without delays. For a chosen population, it is shown as to how forecasting may be done on the spreading of the infection by using a generalized logistic function model, which can be interpreted as a basic compartmental model. In an extended compartmental model, which is a modified form of the SEIQR model, the population is divided into susceptible, exposed, infectious, quarantined, and removed (recovered or dead) compartments, and a set of delay integral equations is used to describe the system dynamics. Time-varying infection rates are allowed in the model to capture the responses to control measures taken, and distributed delay distributions are used to capture variability in individual responses to an infection. The constructed extended compartmental model is a nonlinear dynamical system with distributed delays and time-varying parameters. The critical role of data is elucidated, and it is discussed as to how the compartmental model can be used to capture responses to various measures including quarantining. Data for different parts of the world are considered, and comparisons are also made in terms of the reproductive number. The obtained results can be useful for furthering the understanding of disease dynamics as well as for planning purposes.