Unbound MEDLINE

[Utility of biochemical models predictive of liver fibrosis grade in inmates with hepatitis C.] Gastroenterologia y hepatologia [Gastroenterol Hepatol] Journal article

 
Title[Utility of biochemical models predictive of liver fibrosis grade in inmates with hepatitis C.]
Author(s)Portilla J, López-Burgos A, Saiz-De-La-Hoya-Zamácola P, Sánchez-Payá J, Bedía-Collantes M M, Faraco-Atienzar I, Lissen E 
InstitutionUnidad de Enfermedades Infecciosas, Hospital General Universitario de Alicante, Alicante, España.
SourceGastroenterol Hepatol 2009 May 26.
AbstractOBJECTIVE: To evaluate the utility of two biochemical tests (APRI and FIB-4) to predict liver fibrosis (LF) in prison inmates with chronic hepatitis C.
METHOD: We performed a cross-sectional study in 165 inmates with chronic hepatitis C and liver biopsy from two Spanish prisons. LF was staged according to the Metavir Index and was subsequently reclassified as mild or absent (LF1), significant (LF2) or serious (LF3). APRI and FIB-4 were calculated in all patients. The predictive value was calculated by the area under the curve and the optimal cut-off was obtained based on the best specificity value for each LF stage. Then, we analyzed the sensitivity, positive predictive value (PPV) and negative predictive value (NPV) for each cut-off point.
RESULTS: LF1 was found in 116 inmates (80.3%), significant LF in 49 (29.3%) and serious LF in 24 (14.5%). An APRI value 0.55 or FIB-4 1.0 showed a PPV of 91% and 92%, respectively, for the presence of any grade of LF (1), but both tests had low diagnostic sensitivity: 61.8% and 61.1%, respectively. An APRI value 0.86 or FIB-4 1.3 showed a high NPV for serious LF (92.5% and 88.4% respectively).
CONCLUSIONS: Both tests have a high predictive capacity to detect the presence of LF in inmates with chronic hepatitis C, but their predictive value in detecting intermediate stages of LF is low. Moreover, a significant number of inmates with LF are not identified.
LanguageSPA
Pub Type(s)JOURNAL ARTICLE
PubMed ID19477553
  
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