关键词: 新型冠状病毒肺炎, 流行病学, 临床特征, 危险因素

Abstract: Objective To explore epidemiological and clinical characteristics of corona virus disease 2019(COVID-19) in southern Liaoning Province aiming for its pathogenesis and providing evidence to support and optimize the diagnosis, treatment and prevention. Methods A retrospective analysis was performed by collecting the case information, case history and clinical indicators in 24 hours of admission including asymptomatic and mild/moderate type confirmed cases from February 2020 to January 2021 in southern Liaoning Province. The epidemiological characteristics were studied by descriptive analysis.The clinical characteristics of asymptomatic infection group and mild/moderate infection group were compared by t test, Mann-Whitney U test or pearson χ² test. The differential indexes were included in the binary Logistic regression model for further analysis. Results In 218 cases of COVID-19, 59 were asymptomatic(27.06%) and 159 were mild/moderate(72.94%). The ratio of males to females was 0.79∶1.00. Among all the patients,155 cases(71.10%) aged 31-60 years old, 78 cases(35.78%) were workers and 212 cases(97.25%) were located in Dalian. There were significant differences in age, length of hospital stay, platelet(PLT), lactic dehydrogenase(LDH), total protein(TP), albumin (ALB), blood uric acid (BUA) and c-reactive protein (CRP) between the two groups. The logistic regression model showed that age, LDH and CRP were the risk factors of clinical symptoms after virus infection (P＜0.05). Conclusions In southern Liaoning Province most of COVID-19 cases are mild/moderate. The majority of patients come from Dalian and the main age distribution is 31-60 years old. In terms of clinical diagnosis and treatment, it is suggested that LDH and CRP should be examined as soon as possible for older risk population, that may support early prediction of the disease progress and take more effective prevention and control measures.

Key words: corona virus disease 2019, epidemiology, clinical characteristics, risk factors