Health
Predicting 30-day mortality risk for alcohol-related hepatitis patients-ScienceDaily
Mayo Clinic researchers have developed a new scoring system to help healthcare professionals predict the 30-day mortality risk of alcohol-related hepatitis patients. This tool seems to more accurately identify patients who are at greatest risk of death and who are likely to survive.
A new scoring system called the Alcohol-Related Hepatitis Mortality Index (MIAAH) is at least as accurate as existing models in identifying patients with alcohol-related hepatitis at high risk of death. Mayo Clinic Minutes..
“We believe that MIAAH will probably be refined over time, perhaps in combination with existing models, but our study found that MIAAH is a useful tool for assessing mortality risk. “The Mayo Clinic Gastroenterologist and lead author of the study, Dr. Douglas Simonette, said. “Given the significant mortality rates seen in patients with alcohol-related hepatitis, it is important to assess the severity and prognosis of the disease.”
Alcohol-related hepatitis is an acute inflammatory process of the liver that occurs in patients who consume excessive amounts of alcohol. Patients with mild illness often improve with limited treatment, but severe illness is associated with significant short-term mortality. No pharmacological treatment has been found to reduce 90-day mortality in severe cases. Accurate prognostic tools are essential for clinicians to identify patients at high risk of death and determine appropriate treatment.
With at least four prognostic models available, Mayo’s research team has set out to develop a new system for more accurate prediction of 30-day mortality. Using anonymized patient health records from the Mayo Clinic in Rochester from 1998 to 2018, researchers identified 266 adult patients diagnosed with alcohol-related hepatitis. Of these patients, the 30-day mortality rate was 19.2%. In this study, we derived several variables such as blood urea nitrogen and bilirubin and developed a model scoring system incorporating these variables.
The MIAAH model was then used to predict the results of an external validation cohort of 249 patients from the University of South Dakota and University of Kansas Healthcare Centers. It finally turns out that this model is as accurate as existing tools for identifying patients at high risk of short-term death.
“MIAAH also showed favorable performance characteristics in its ability to more and more accurately identify patients at high risk of death and those who are likely to survive,” said Mayo Clinic’s resident physician and study. The lead author, Dr. Camille Kezel, said. “It also has the advantage of working well for patients, whether or not they have been treated with steroids, which makes it generalizable.”
Despite decades of research, treatment options for patients with alcohol-related hepatitis are limited and their effectiveness is questionable. The prognosis model is important in determining which treatment is valuable and whether the patient is responding to the treatment. Modeling is also essential in determining if a patient is a candidate for a liver transplant.
“This is why prognostic models that accurately identify short-term mortality risk have such value,” says Dr. Simonet. “In this study, we set out to create a new model with more consistent and reliable accuracy based on laboratory variables and demographic data that are routinely obtained on admission. Although it may include a combination of models, MIAAH will be an important tool for helping patients. “
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material Provided by Mayo Clinic.. Original written by Jay First. Note: Content can be edited in style and length.
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