Clinical application of transient elastography in prediction of portal hypertension related complication in patients with chronic liver diseases

2012 Journal of the Egyptian Society of Parasitology 42;1 (79-88)

Liver cirrhosis (LC) is the final evaluative stage of chronic liver diseases with dynamic progressive process to multiple complications especially splenomegaly and esophageal varices(EV). Efforts have been made to develop non-invasive predictive models that may correlate with LC and EV. The role of liver stiffness measurement (LSM)- and spleen stiffness measurement (SSM) by transient elastography (TE) in the diagnosis of LC and prediction of EV was studied on 90 subjects selected from the outpatient clinics of Bakhash Hospitals. They were classified into three groups: GI included 10 healthy volunteers as a control group, GII included 20 chronic hepatitis (CH) patients and GIII included 60 cirrhotic patients. Patients in GIII were further subdivided equally into two subgroups A & B according to presence or absence of EV. GIII patients were evaluated by gastroscope for screening and grading of EV. All groups were subjected to complete blood picture, liver and kidney function testes and abdominal ultrasonography as well as LSM (right lobe) and SSM by using fibroscan. LS were significantly higher in LC patients as compared with CH patients and controls. At a cutoff value of 9.8 kPa, sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV) for LC were 90%, 73%, 55% &78% respectively. At a cutoff value of 17.75 kPa (no varices vs. varices at any grade), sensitivity, specificity, PPV & NPV for prediction of EV were 92%, 46.2%, 73% & 67.2% respectively. LS at cut off values of 14.4 KPa predicted the splenomegaly. SSM at 50.4 KPa being the best cut-off value for prediction of varices with sensitivity, specificity, PPV, NPV & accuracy were 81.2%, 73.2%, 88.7%, 48.8% & 79.4% respectively. Combination of LS >17 KPa & SS > 52, predicted EV with 87.6% diagnostic accuracy. As regard EV prediction, combination of LSM & SSM had a highest diagnostic accuracy than PSR (76.9% vs. 87.6).

Pubmed : 22662598