Dynamic model could aid management of overdose patients
MedWire News: Mathematicians have developed a formula to help emergency room doctors predict liver injury and dysfunction in patients with acetaminophen overdose.
"It's an opportunity to use mathematical methods to improve medical practice and save lives," said Frederick Adler (University of Utah, Salt Lake City), a Professor of Mathematics and Biology and study co-author, in a press statement.
Acetaminophen (paracetamol) overdose is the leading cause of liver injury in the developed world. Survival largely depends on two parameters: the size of the initial dose and time elapsed prior to administration of N-acetylcysteine.
Very early administration of N-acetylcysteine (within 12 hours of overdose) results in almost 100% survival, explain Christopher Remien, also from the University of Utah, and fellow authors writing in Hepatology.
Current models of acetaminophen toxicity rely on the time between ingestion and hospital admission but are frequently inaccurate because the timing of overdose is often unobtainable or unreliable.
Remien's team therefore sought to develop a more accurate system, in which they used differential equations to model the dynamics of hepatocyte damage following acetaminophen overdose.
Their "Model for Acetaminophen-induced Liver Damage" (MALD) initially used three admission biochemistry results - aspartate aminotransferase (AST), alanine aminotransferase (ALT), and international normalized ratio (INR) - to estimate overdose amount, time elapsed since overdose, and likely outcome.
The team tested their model on 53 patients admitted to a university hospital with acetaminophen overdose. Excluding patients who underwent liver transplantation, it predicted death versus recovery with a specificity of 95%, sensitivity of 75%, positive predictive value of 75%, and negative predictive value of 95%.
Adding a fourth value - an initial serum creatinine exceeding 3.4 mg/dL - improved the model's predictive ability, giving a specificity of 91%, sensitivity of 100%, positive predictive value of 67%, and negative predictive value of 100%.
These values compare favorably with the King's College Criteria, a well-validated method for predicting death without transplantation in acetaminophen-induced acute liver failure, which has a specificity of 100%, sensitivity of 13%, positive predictive value of 100%, and negative predictive value of 86%.
"This is the first dynamical rather than statistical approach to determine poor prognosis in patients with life-threatening liver disease due to acetaminophen overdose," write Remien et al.
"MALD provides a method to estimate overdose amount, time elapsed since overdose, and outcome from patient laboratory values commonly available on admission in cases of acute liver failure due to acetaminophen overdose and should be validated in multicentric prospective evaluation."
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By Joanna Lyford