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Evaluation of hepatitis C virus infection based on big data of hospital / 中华肝脏病杂志
Chinese Journal of Hepatology ; (12): 426-428, 2018.
Article in Chinese | WPRIM | ID: wpr-806713
ABSTRACT
Objective@#To evaluate the feasibility of hepatitis C virus (HCV) infection by survey methods based on big data of hospital.@*Methods@#Inpatients data of anti-HCV was collected in 2016 and 2011. Patient’s data related to Department of Liver Diseases were excluded. The research population was divided into Surgical and Non-surgical Department. The characteristics of the two groups were analyzed and the changing trends of anti -HCV positive rate in different years was compared and analyzed.@*Results@#Patients in the surgical and non-surgical department of hospital were equally distributed across gender, urban and rural areas, and region, but the distribution of patients in surgical departments were relatively equal in all age groups. The positive rate of anti -HCV in hospitalized patients in 2016 was 0.82%, and anti -HCV positive rate was 0.58% in surgical department of 1~55 years old. Among them, anti-HCV was positive in 0.06% who underwent surgical procedure at the age of ≤25 (born after 1993 and screened for hepatitis C antibody), which was significantly lower than those in other age groups were. The anti -HCV positive rate of patients (all age groups) was lower in 2016 than that in 2011(0.75% vs. 0.97%). The anti-HCV positive rates of surgical department in both years had a decreasing trend with age.@*Conclusion@#The prevalence rate of anti-HCV, among patients population of operation departments, might reflect the prevalence rate of HCV infection among general population. Using the convenience of hospital data acquisition, we might dynamically understand the change of HCV infection.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Hepatology Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Hepatology Year: 2018 Type: Article