Prevalence of occult hepatitis C virus among hemodialysis patients in Tanta university hospitals: a single-center study.

Occult hepatitis C virus infection (OCI) is a newly defined type of infection by the chronic hepatitis virus (HCV) distinguished by the existence of HCV RNA in liver tissue and/or peripheral blood mononuclear cells (PBMCs) in patients whose plasma are devoid of both positive serology and RNA. Patients on maintenance hemodialysis evince a higher HCV prevalence than the general population due to high nosocomial transmission by the dialysis units. We investigated the prevalence of occult HCV infection in patients attending our university hemodialysis centers for maintenance hemodialysis. Sixty-two CHD patients negative for serum HCV tests were enrolled in the study. PMNCs were tested by real-time PCR for the presence of HCV RNA. For the 62 patients, the average duration since starting dialysis was 32.7 months and the mean (SD) alanine transaminase and aspartate transaminase were 25.74 ± 9.75 and 28.81 ± 11.32 IU/l, respectively. Out of the 62 CHD patients negative for serum anti-HCV and HCV RNA patients, only three (4.84%) were shown to have HCV RNA in their PBMCs implying the diagnosis of OCI; their viral load range was 1.24-4.15 IU/ml. All three OCI-proven patients gave no history of hepatic disease. In this study, we found that patients considered to be free of HCV can have HCV replicating in their PBMCs. This awareness points to the possibility of HCV being transmitted from apparently uninfected persons. A positive HCV RNA detection in PBMCs is dependable in determining OCI among high-risk subjects particularly when a liver biopsy is not an option. HCV transmission can occur through hemodialysis units signaling incorrect application of infection control measures in our Egyptian dialysis units. Additional studies on hemodialysis patients are necessary to realize the true magnitude of OCI among this patient group and to highlight the importance of incorporating HCV viral assays in PBMCs into the diagnostic algorithm.