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Prediction of HCV vertical transmission: what factors should be optimized using data mining computational analysis
Author(s) -
Elrazek Abd,
Amer Mohamed,
ElHawary Bahaa,
Salah Altaher,
Bhagavathula Akshaya S.,
Alboraie M.,
Saab Samy
Publication year - 2017
Publication title -
liver international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.873
H-Index - 110
eISSN - 1478-3231
pISSN - 1478-3223
DOI - 10.1111/liv.13146
Subject(s) - medicine , transmission (telecommunications) , hepatitis c virus , viral load , pregnancy , hepatitis c , horizontal transmission , obstetrics , virology , virus , pediatrics , immunology , biology , electrical engineering , genetics , engineering
Background & Aims Neonates born to hepatitis C virus ( HCV )‐positive mothers are usually not screened for HCV . Unscreened children may act as active sources for social HCV transmission, and factors contributing for vertical HCV transmitting still remained controversial and needed optimization. We aimed to investigate the factors contributing for vertical HCV transmission in Egypt; the highest HCV prevalence worldwide. Methods We prospectively followed the neonates born to HCV ‐positive mother in the child‐bearing period, to identify mother‐to‐child transmission ( MTCT ) factors from January 2015 to March 2016. Data mining computational analysis was used to quantify the findings. Results Among 3000 randomized pregnant women, prevalence of HCV was 46/3000 (1.53%). HCV vertical transmission was identified in eight neonates (17.39%). Only high viral load identified at 975.000 IU was the predictor risk for MTCT . Conclusions Hepatitis C virus in pregnancy has substantial risk for vertical HCV transmission: High viral load in HCV ‐positive women increases the risk of HCV transmission to neonates. Screening pregnant women during early stage of pregnancy and optimizing the HCV viral load in HCV ‐positive women might prevent vertical HCV transmission to neonates.