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Evaluation of occult hepatitis B infection in tissue donors: a multicenter analysis in Spain.

Jacinto Sánchez IbáñezAna Vilarrodona SerratTeresa Seoane PilladoClara Rodriguez AierbeRafael Villalba MontoroJavier Calvo BenitoMarta Pevida LopezSergio Fernández PanequeElena Vuelta LopezMaria Jose Martínez LorenzoManuel González RomeroAngelina Cañizares CastellanosSilvia Sauleda Oliveras
Published in: Cell and tissue banking (2019)
Traditionally, when antibody to the Hepatitis B core antigen (anti-HBc) and antibody to the Hepatitis B surface antigen (anti-HBs) are positive, the donor is considered suitable. However, the literature contains cases with this profile and circulating hepatitis B virus DNA. The aim of the study is to analyze the incidence of occult hepatitis B virus infection (OBI). Retrospective data were evaluated for deceased tissue donors in ten Tissue Establishments (Spain) during 2017. The data included demographic data and the serological markers for hepatitis B that each tissue establishment performed. A total number of 1933 tissue donors were evaluated. A total of 180 donors were excluded: 6 (0.3%) with Hepatitis B surface antigen (HBs positive), and 174 in which DNA testing was not performed. Anti-HBc was positive in 175 donors (10%), in which anti-HBs was negative in 30 (17.1%) and positive in 145 (82.9%). In total, 27 donors with DNA positive (1.5%) were found, of which 3 of 117 donors (1.7%) showed anti-HBc negative and anti-HBs positive (> 10 IU/ml), 4 of 30 donors (13.3%) showed anti-HBc positive and anti-HBs negative and 20 of 145 donors (13.8%) showed both anti-HBc and anti-HBs positive. The highest probability of finding DNA occurs when anti-HBc is positive, regardless of the presence of anti-HBs. In our study, the probability of OBI was 1.5%. The classic concept that when anti-HBc and anti-HBs are positive (even with a titer of over 100 IU/ml) the donor can be accepted should, therefore, be reconsidered, and DNA testing should be mandatory.
Keyphrases
  • hepatitis b virus
  • kidney transplantation
  • circulating tumor
  • risk factors
  • machine learning
  • electronic health record