Hepatitis C virus (HCV) affects over 180 million people worldwide and it's the leading cause of chronic liver diseases and hepatocellular carcinoma. HCV is classified into seven major genotypes and a series of subtypes. In general, HCV genotype 4 (HCV-4) is common in the Middle East and Africa, where it is responsible for more than 80% of HCV infections. Although HCV-4 is the cause of approximately 20% of the 180 million cases of chronic hepatitis C worldwide, it has not been a major subject of research yet. The aim of the current study is to survey the morbidities and disease complications among Egyptian population infected with HCV-4 using data mining advanced computing methods mainly and other complementary statistical analysis.
Six thousand six hundred sixty subjects, aged between 17 and 58 years old, from different Egyptian Governorates were screened for HCV infection by ELISA and qualitative PCR. HCV-positive patients were further investigated for the incidence of liver cirrhosis and esophageal varices. Obtained data were analyzed by data mining approach.
Among 6660 subjects enrolled in this survey, 1018 patients (15.28%) were HCV-positive. Proportion of infected-males was significantly higher than females; 61.6% versus 38.4% (P = 0.0052). Around two-third of infected-patients (635/1018; 62.4%) were presented with liver cirrhosis. Additionally, approximately half of the cirrhotic patients (301/635; 47.4%) showed degrees of large esophageal varices (LEVs), with higher variceal grade observed in males. Age for esophageal variceal development was 47 ± 1. Data mining analysis yielded esophageal wall thickness (>6.5 mm), determined by conventional U/S, as the only independent predictor for esophageal varices.
This study emphasizes the high prevalence of HCV infection among Egyptian population, in particular among males. Egyptians with HCV-4 infection are at a higher risk to develop cirrhotic liver and esophageal varices. Data mining, a new analytic technique in medical field, shed light in this study on the clinical importance of esophageal wall thickness as a useful predictor for risky esophageal varices using decision tree algorithm.