Identification of Predictive Factors in Chronic Hepatitis C Patients with Non-Infected Individuals: A Comparative Analysis

Abstract

Hepatitis C virus is playing a key role in chronic liver disease all around the globe. Currently, in Pakistan, it is a huge burden on health and the economy, affecting about 6 to 8% of the overall population. HCV is dependent on the lipid metabolism of the patient to replicate and then disturb the blood cell count and liver enzymes to ultimately damage the liver. To distinguish the potential HCV patients from healthy individuals at an early stage is quite important for its control, which can be achieved by investigation of liver enzymes, complete blood count, and lipid profile of patients. In this study, 144 CHC and 20 controls were included. The serum of CHC patients was analyzed for HCV viral load and genotype. The liver function test, lipid profile, sugar levels, and complete blood count values were assessed in the laboratory. Receiver operating characteristics were used to find the biomarkers of infection. Logistic regression analysis revealed that liver enzymes (ALT, AST, ALP, γGT, albumin), blood cell count (globulin, platelets, MCHC RBC, WBC, monocytes% and lymphocytes%), lipid profile (HDL, LDL, VLDL, TC) were significant predictive factors in HCV infection. Similarly, ROC analysis suggested that ALT, AST, ALP, MCHC, TC, and VLDL variables have the potential to discriminate HCV infection from healthy individuals. Biochemical markers like liver enzymes, blood cell count, lipid profile are the main predictive factors of Chronic Hepatitis C patients as compare to the healthy group.