Your browser doesn't support javascript.
loading
Novel non-invasive biological predictive index for liver fibrosis in hepatitis C virus genotype 4 patients.
Khattab, Mahmoud; Sakr, Mohamed Amin; Fattah, Mohamed Abdel; Mousa, Youssef; Soliman, Elwy; Breedy, Ashraf; Fathi, Mona; Gaber, Salwa; Altaweil, Ahmed; Osman, Ashraf; Hassouna, Ahmed; Motawea, Ibrahim.
Afiliação
  • Khattab M; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Sakr MA; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Fattah MA; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Mousa Y; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Soliman E; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Breedy A; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Fathi M; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Gaber S; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Altaweil A; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Osman A; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Hassouna A; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
  • Motawea I; Mahmoud Khattab, Mohamed Abdel Fattah, Youssef Mousa, Elwy Soliman, Ibrahim Motawea, Department of Internal Medicine, Minia University, Minia 61111, Egypt.
World J Hepatol ; 8(32): 1392-1401, 2016 Nov 18.
Article em En | MEDLINE | ID: mdl-27917265
ABSTRACT

AIM:

To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy.

METHODS:

A cohort of 332 patients infected with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensin-converting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance (HOMA-IR).

RESULTS:

Fibrosis stages were distributed based on Metavir score as follows F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis (F0-F) = 179, moderate fibrosis (F2) = 64, and advanced fibrosis (F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage (P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤ -0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis.

CONCLUSION:

Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article