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MAURIZIO SORESI

Optimizing diagnostic approach to drug-induced liver injury

  • Autori: Minissale, Maria Giovanna; Soresi, Maurizio; Galia, Massimo; Agnello, Francesco; Giannitrapani, Lydia; Midiri, Massimo; Licata, Anna*
  • Anno di pubblicazione: 2018
  • Tipologia: Articolo in rivista (Articolo in rivista)
  • OA Link: http://hdl.handle.net/10447/326666

Abstract

Drug-induced liver injury (DILI) is often a trial even to expert clinicians, because sometimes diagnosis is not easy to be made. Guidelines of the American College of Gastroenterology (ACG) yielded in 2014, help to better understand the problem. The diagnosis of DILI is made through a detailed evaluation of clinical, serological, radiological and histological aspects. Biochemical data include liver function tests that allow to assess the pattern of damage, such as hepatocellular, cholestatic and mixed liver injury; serological data include testing for major and possibly minor hepatotropic viruses, non-organ specific autoantibodies. Clinical scenario might include jaundice, nausea, vomiting and extra-hepatic manifestations such as fever, pruritus, rash and eosinophilia. Investigation of the potential culprit drugs should involve firstly the temporal relationship between intake of the medication and onset of symptoms, thus the improvement after drug withdrawal. Overall, to complete the diagnostic evaluation, an abdominal ultrasound can be performed, as well as measurement of liver stiffness by transient elastography, and finally liver biopsy, which still represents the most accurate method to definitely assess liver damage. Sometimes, in such cases, computed tomography scan and magnetic resonance could help in the diagnosis of cases presenting with focal lesions of the liver, with cholestatic-like disease or vascular alterations, such as veno-occlusive disease. DILI diagnostic criteria help clinicians thinking of liver injury induced by drug, excluding other causes of liver disease. According to severity of liver damage and type of drug, it is possible to carefully predict the patient's outcome.