Severe Risk Factor Analysis And Prediction Model Establishment Of COVID-19

Objective:To identify the clinical characteristics and the risk factors for severe disease of the coronavirus disease 2019(COVID-19)patients,based on the risk factors,a predictive model of severe disease is established to detect the risk of severe disease in time for patients,and adjust treatment strategies to improve the treatment effect of severely ill patients.Methods:A total of 417 patients with COVID-19 diagnosed in the Third People’s Hospital of Shenzhen from January 13,2020 to February29,2020 were selected as the subjects.Among them,325 cases of mild and common patients were included in the mild group,and 92 cases of severe and critical patients were included in the severe group.Their epidemiological history,clinical features,laboratory examination were analyzed.Logistic regression was used to analyze the indexes that differentially expressed among patients with different disease severity,to build a model that could predict the disease progression in patients with COVID-19.Further enrollmented of 50 COVID-19 patients who met the admission criteria in the early stage,including 11 critical patients,25severe patients and 14 common patients,to measure and analyze the expression levels and changes of 48 cytokines in their plasma.It is found that the SARS-Co V-2 infection can induce a cytokine storm,and further search for cytokines that may be related to the severity of the disease,and establish a prediction model based on these cytokines..Results:(1)Among the 417 COVID-19 patients,22.1%was in severe or critical condition,the median age was 61years;Compared with the common group,the patients in the severe group were mostly male,older,with higher BMI,longer time from onset to diagnosis,and more complicated with underlying diseases.The above indicators were significantly different between the two groups(P<0.05).(2)The most common clinical symptoms of COVID-19 patients were fever and cough,and the number of fever and cough in the severe group was significantly higher than that in the common group,respectively(P<0.05).Most of the patients were treated with alpha-interferon and lopinavir and ritonavir tablets for antiviral therapy,and most of the severe patients were used glucocorticoid and gamma globulin for immunoregulatory therapy.The median length of hospitalized in severe patients was 29 days,which was significantly higher than that in common patients.After treatment,414 patients were been better and 3 patients were died.(3)The levels of LYM,PLT,CD4~+T lymphocyte count,CD8~+T lymphocyte count,e GFR and Na in severe group were significantly lower than those in common group(all P<0.05),while the levels of NEU,D-DIC,ALT,AST,Cr,LDH,MYO,BNP,Tn I,PCT,CRP,IL-6 and ESR in severe group were significantly higher than those in common group,respectively.(P<0.05).(4)Age≥55 years old and BMI>27kg/m~2,low level of CD4~+T lymphocytes(≤400/μL)and high level of IL-6(≥20pg/m L)are effective indicators for predicting the severity of disease in COVID-19 patients.(5)Abnormal expression of pro-inflammatory and anti-inflammatory factors in COVID-19 patients was found on admission,and a cytokine storm appeared.(6)IL-1b,IL-1ra,IL-6,IL-13,IL-18,HGF,MCP-3,MIG,M-CSF,G-CSF,MIP-1α,MIP-1β,CTACK and IP-10 were differentially expressed among patients with different disease severity.The expression levels of IP-10,HGF and MCP-3 were the highest in the critical patients,followed by severe patients.The differential expression of IL-1ra and M-CSF were mainly occurred in the early stage of disease development(0-7 days),while the differential expression of MIG and MIP-1αwere mainly occurred in the late stage of disease development(8-14 days and 15-27days).(7)The expression levels of IP-10,MCP-3,HGF,MIG,IL-1ra and MIP-1a were highly positive correlated with Murray score,their expression levels could reflect the disease progression and severity of COVID-19patients in some degree.(8)IP-10 and MCP-3 could as predictor for COVID-19 disease progression,the AUC value of the ROC curve of the model used to predict the disease progression was 0.990.Conclusions:Age,gender,body weight,combined with underlying diseases are risk factors for COVID-19 patients to develop severe disease.Patients with high fever,cough and abnormal clinical indicators should also be alert to the possibility of severe disease.Age older than 55 years,BMI higher than 27 kg/m~2,CD4~+T lymphocytes lower than 400/μL and IL-6 higher than 20 pg/m L were effective markers for predicting the disease severity in COVID-19 patients.Cytokine storms were significant observed in the severe COVID-19 patients,IP-10 and MCP-3 were effective markers for predicting the COVID-19 severity.