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BioMed Research International
Volume 2015, Article ID 429290, 7 pages
http://dx.doi.org/10.1155/2015/429290
Research Article

Predictors for Early Identification of Hepatitis C Virus Infection

1Kaohsiung Blood Center, Taiwan Blood Services Foundation, Kaohsiung 811, Taiwan
2Department of Medical Laboratory Science and Biotechnology, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 807, Taiwan
3Department of Clinical Laboratory, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
4Cishan Hospital, Ministry of Health and Welfare, Kaohsiung 842, Taiwan
5Department of Medical Imaging and Radiological Sciences, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 807, Taiwan
6Translational Research Center, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan
7Institute of Medical Science and Technology, National Sun Yat-Sen University, Kaohsiung 804, Taiwan
8Department of Anesthesiology, Chang Gung Memorial Hospital-Kaohsiung Medical Center, Chang Gung University College of Medicine, Kaohsiung 833, Taiwan
9Department of Biological Sciences, National Sun Yat-Sen University, Kaohsiung 804, Taiwan
10Edward Francis Small Teaching Hospital, Banjul 1515, Gambia
11Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan
12Department of Obstetrics and Gynecology, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan
13School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
14Department of Laboratory Medicine, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan

Received 8 September 2014; Accepted 28 November 2014

Academic Editor: Mohammad Ahmad Al-Shatouri

Copyright © 2015 Mei-Hua Tsai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Hepatitis C virus (HCV) infection can cause permanent liver damage and hepatocellular carcinoma, and deaths related to HCV deaths have recently increased. Chronic HCV infection is often undiagnosed such that the virus remains infective and transmissible. Identifying HCV infection early is essential for limiting its spread, but distinguishing individuals who require further HCV tests is very challenging. Besides identifying high-risk populations, an optimal subset of indices for routine examination is needed to identify HCV screening candidates. Therefore, this study analyzed data from 312 randomly chosen blood donors, including 144 anti-HCV-positive donors and 168 anti-HCV-negative donors. The HCV viral load in each sample was measured by real-time polymerase chain reaction method. Receiver operating characteristic curves were used to find the optimal cell blood counts and thrombopoietin measurements for screening purposes. Correlations with values for key indices and viral load were also determined. Strong predictors of HCV infection were found by using receiver operating characteristics curves to analyze the optimal subsets among red blood cells, monocytes, platelet counts, platelet large cell ratios, and mean corpuscular hemoglobin concentrations. Sensitivity, specificity, and area under the receiver operator characteristic curve were 75.6%, 78.5%, and 0.859, respectively.