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We present this case study to provide guidance on how best to utilize medical calculators to assist with diagnosis and treatment for this patient.  In the discussion section, we recommend specific medical calculators that will help physicians with clinically appropriate decision making.

Case Study: A Teacher With Signs Liver Problems

Laurie is a 56 year old high school teacher. She is overweight with a history of diabetes, hypertension, peptic ulcer disease, and chronic arthritis. Because of the stress of teaching she often unwinds at night with a drink or two (or three). For her arthritis she takes an herbal medicine recommended by a co-worker as a Chinese wonder drug. She also takes medication for her diabetes and hypertension together with a proton pump inhibitor (PPI).

She went to her doctor because she noted that her belly was expanding and her clothes were no longer fitting. The doctor noted signs suspicious for portal hypertension. Her liver function tests were elevated.  Markers for viral hepatitis were negative. She did not have any known exposures to infectious diseases or chemicals.

The patient was referred to a gastroenterologist who expanded the workup. The serum ANA and filamentous actin (F-actin) were both mildly elevated. The antimitochondrial antibodies were negative. The gastroenterologist decided that a liver needle biopsy might help to establish a diagnosis.

An image-guided needle biopsy of the liver was performed by a radiologist without complications. The radiologist noted some ascites fluid during the procedure. The radiologist did not see abnormalities of the bile ducts or evidence of sclerosing cholangitis, although it was noted that gallbladder showed several large gallstones.

The liver biopsy showed bridging fibrosis but no clear evidence of cirrhosis. A striking change was an interface hepatitis with numerous plasma cells. Moderate steatosis was present. No excess of iron was seen on iron stain.

The gastroenterologist took a careful medication history and excluded potential hepatotoxic drug exposures. He reviewed the herbal remedy and did not think that it was likely to be hepatotoxic based on its reported ingredients. In light of the patient’s history and findings the gastroenterologist made the diagnosis of autoimmune hepatitis.

Discussion

There are many conditions that can adversely affect the liver. The differential diagnosis in this patient includes:

  1. Alcoholic liver disease
  2. Non-alcoholic steatohepatitis (NASH) with evidence of metabolic syndrome
  3. Autoimmune hepatitis
  4. Herbal remedy related hepatitis
  5. Biliary cirrhosis

The challenge is to determine which of these are present and to what extent. Once the causes are known then steps can be taken:

  1. To stop the sources of hepatic injury
  2. To reverse existing damage so that the liver (and patient) can recover.

Fortunately the liver can recover from many types of injury.

Role of Liver Biopsy

Liver biopsy can be helpful in identifying a cause for liver disease, especially when the clinical findings are ambiguous or overlapping. Generally, a liver biopsy should only be performed if it will change treatment or management of the patient. In nonalcoholic liver disease (NAFLD), chronic hepatitis, or other liver disease, it can be used to determine the extent of liver damage and fibrosis. Liver biopsies are also useful for unexplained liver function tests or liver disease.

  • Indications for Performing a Liver BiopsyIndications for Performing a Liver Biopsy
  • The Histological Semiquantitative Scoring System (SSS) for Evaluation of Hepatic Fibrosis in Needle Liver Biopsy SpecimensThe Histological Semiquantitative Scoring System (SSS) for Evaluation of Hepatic Fibrosis in Needle Liver Biopsy Specimens

Autoimmune Hepatitis (AI)

Autoimmune (AI) hepatitis is a chronic disease of often unknown etiology. Several possible inciting events, such as viral infections, drugs, environmental exposures, have been linked to development of autoimmune hepatitis. Women develop AI hepatitis more often than men, 7-8 to 1. AI Hepatitis is seen most often among two age groups, late pediatric (10y-20y) and again in middle age (45y-70y). Cases have been diagnosed in infants as well as the elderly.

  • Types of Autoimmune HepatitisTypes of Autoimmune Hepatitis
  • Revised IAHG Scoring System for Autoimmune HepatitisRevised IAHG Scoring System for Autoimmune Hepatitis
  • Indications for Liver Transplantation in a Patient with Fulminant Autoimmune HepatitisIndications for Liver Transplantation in a Patient with Fulminant Autoimmune Hepatitis

Alcoholic Liver Disease

Alcohol abuse may lead to a variety of pathology in the liver including steatosis, steatohepatitis, cirrhosis, and hepatocellular carcinoma. Clinical manifestations of the disease will depend on severity, but patients are typically asymptomatic until developing hepatitis or cirrhosis (presenting with signs of hepatic decompensation). Classic laboratory findings in alcoholic liver disease is moderately elevated transaminases, with the asparate aminotransferase (AST) to alanine aminotransferase (ALT) typically greater than 1.5.

  • Risk Factors for Development of Alcoholic HepatitisRisk Factors for Development of Alcoholic Hepatitis
  • ANI (Alcoholic Liver Disease to Nonalcoholic Fatty Liver Disease Index) Model for Evaluating a Patient with SteatohepatitisANI (Alcoholic Liver Disease to Nonalcoholic Fatty Liver Disease Index) Model for Evaluating a Patient with Steatohepatitis
  • Prognostic Score for a Patient with Alcoholic Hepatitis (ABIC Score)Prognostic Score for a Patient with Alcoholic Hepatitis (ABIC Score)
  • Glasgow Alcoholic Hepatitis Score (GAHS)Glasgow Alcoholic Hepatitis Score (GAHS)
  • MELD Score and Other Risk Factors in a Patient with Alcoholic HepatitisMELD Score and Other Risk Factors in a Patient with Alcoholic Hepatitis
  • The Alcohol Symptom ChecklistThe Alcohol Symptom Checklist

Nonalcoholic Steatohepatitis (NASH)

Nonalcoholic fatty liver disease is divided into nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH). NASH is characterized by hepatic inflammation and histologically is not able to be differentiated from alcoholic steatohepatitis. Factors associated with disease progression include older age, diabetes, and body mass index. Hepatocellular carcinoma is often associated with cirrhosis stemming from nonalcoholic fatty liver disease.

  • Grading and Staging Scheme for Nonalcoholic SteatohepatitisGrading and Staging Scheme for Nonalcoholic Steatohepatitis
  • Risk Factors for Nonalcoholic SteatohepatitisRisk Factors for Nonalcoholic Steatohepatitis
  • Predictors of Hepatic Fibrosis in Patients with Nonalcoholic SteatohepatitisPredictors of Hepatic Fibrosis in Patients with Nonalcoholic Steatohepatitis
  • Fatty Liver Index (FLI) for Predicting Hepatic SteatosisFatty Liver Index (FLI) for Predicting Hepatic Steatosis
  • WHO Definition of the Metabolic SyndromeWHO Definition of the Metabolic Syndrome

Drugs-induced Liver Disease

Drug-induced liver disease in the most common cause of acute liver failure in the United States. Over a thousand drugs have been known to cause drug-induced liver injury, with the most common drug in the United States being acetaminophen. Amoxicillin is also a common cause worldwide. Many patients present asymptomatic with disease only detected because of abnormalities in laboratory testing. Patients may, however, present with symptoms including malaise, nausea, vomiting, right upper quadrant pain, jaundice, or dark urine. Diagnosis can often be difficult and relies on a detailed history and ruling out other causes of liver disease. Primary treatment is stopping the offending agent.

  • International Consensus Meeting Criteria for Drug-Induced Liver DisordersInternational Consensus Meeting Criteria for Drug-Induced Liver Disorders
  • Protocol for Identifying Drug-Induced Liver InjuryProtocol for Identifying Drug-Induced Liver Injury

Of concern for patients who abuse alcohol and who have pain is the use of acetaminophen which can be toxic to the liver in high doses.

  • Amount of Acetaminophen Consumed Daily By a Person Abusing an Over-the-Counter (OTC) or Prescription MedicationAmount of Acetaminophen Consumed Daily By a Person Abusing an Over-the-Counter (OTC) or Prescription Medication
  • Recognition of Acetaminophen Hepatotoxicity in Chronic AlcoholicsRecognition of Acetaminophen Hepatotoxicity in Chronic Alcoholics

Herbal Remedies

Many people take an herbal remedy and because they are “natural” they are assumed to be safe. One of the first recognized examples proving how wrong this can be is the Veno-Occlusive Disease (VOD) caused by pyrrolizidine alkaloids in bush teas.

When evaluating an herbal remedy for toxicity it is important to know if there are any unstated additives.

  • Herbal Supplements Associated with HypertensionHerbal Supplements Associated with Hypertension

Take Home Points

  • In practice many people have more than one cause for a clinical or laboratory finding, and the challenge is to separate them out. A complete workup and evaluation of laboratory data along with detailed history can often identify the cause.
  • The Medical Algorithms Company has within its vast database of medical algorithms, specialized Medal Packs to assist clinicians in the diagnosis, workup, and treatment of difficult to discern conditions, such as hepatitis.
    • Within the hepatitis Medal Pack, users are able to browse the following subtopics:
      • Patient Evaluation
      • Temporal Course and Activity
      • Causes of Hepatitis
      • Additional Concerns
      • Differential Diagnosis of Hepatitis
      • Management of Viral Hepatitis
      • Patient Concerns
  • Using Medal Packs can improve diagnostic accuracy and reduce risk for incomplete workup. In turn, Medal Packs may be able to reduce hospital stay and overall healthcare costs while improving patient care.
  • Medal Packs are available on our website and via our iOS and Android app, and can serve as handy reference to physicians both in and out of the office.
  • The medical algorithms highlighted in this case study are available at The Medical Algorithms Company and also on the apervita health analytics platform.

About the Authors

Adam Vohra is a Health Innovation Fellow at Apervita. He is currently a dual-degree MD/MBA student in his final year at The University of Chicago Pritzker School of Medicine and Booth School of Business. He plans to pursue a residency in internal medicine next year. Adam is interested in issues related to health care quality and delivery and has published research on predictors of intensive care unit admission for pneumonia. He is currently working on research to create analytics to predict heart failure readmissions. Adam is also involved heavily in health care policy and currently serves on the Board of Trustees of the Illinois State Medical Society as the sole medical student member. In the past, Adam has also represented medical students in the American Medical Association House of Delegates. Prior to coming to The University of Chicago, Adam completed his undergraduate studies at Northwestern University where he studied biology and political science.

Dr. Chad Rudnick, MD, FAAP is a board-certified pediatrician in Boca Raton, FL. He is the Medical Director of The Medical Algorithms Company. A proponent of incorporating medical technology into his practice, Dr. Rudnick uses telemedicine and medical algorithms from The Medical Algorithms Company in his daily practice to better serve his patients and their families. An accomplished medical writer, he maintains a popular pediatric blog, All Things Pediatric, and has written for numerous online and print publications including KevinMD.com.

John Svirbely, MD is a founder and Chief Medical Officer of The Medical Algorithms Company and the primary author of its medical algorithms. John is a co-founder of the Medical Algorithms Project and has developed its medical content for nearly 20 years. He has a BA degree from the Johns Hopkins University and his MD from the University of Maryland. He is a board-certified pathologist with a fellowship in medical microbiology and biomedical computing at Ohio State University. Currently he is in private practice in Cincinnati, Ohio. He has authored multiple books and articles on medical algorithms.

 


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