Research presented recently at the American Diabetes Association (ADA) 77th Scientific Sessions in San Diego warned that clinicians managing blood glucose levels in critically ill children should ascertain that they are not treating false elevations of blood glucose caused by acetaminophen interaction.

The researchers from Boston and Philadelphia determined that after acetaminophen is administered, clinicians should wait between 2.4 and 3.7 hours to avoid treating falsely elevated blood glucose levels. Peak concentrations of acetaminophen were found to be higher when measured by continuous glucose monitor (CGM) devices when administered intravenously vs. enterally or rectally.

Acetaminophen and Stevens-Johnson Syndrome

Besides causing elevated blood glucose levels in children, acetaminophen has been linked to other serious illnesses, including Stevens-Johnson Syndrome (SJS), a life-threatening and extremely painful condition.

Symptoms of SJS include:

  • Cough
  • Headache
  • Rash
  • Blisters
  • Widespread damage to the surface of the skin

Stevens-Johnson Syndrome typically requires hospitalization and in some cases can even result in death. In 2013, the U.S. Food and Drug Administration (FDA) issued a warning directing the makers of acetaminophen products to intensify their warnings about Stevens-Johnson Syndrome and advising patients who develop symptoms of the skin disease to stop taking acetaminophen and seek immediate medical attention. The warning came after the FDA its own Adverse Event Reporting System, identifying 107 cases of adverse skin reactions between 1969 and 2012 that were connected to acetaminophen.

Acetaminophen has also been linked to toxic epidermal necrolysis (TEN) and acute generalized exanthematous pustulosis (AGEP). While AGEP usually resolves within two weeks of stopping the medication, TEN usually requires hospitalization and can be fatal. A serious skin reaction can occur at any time, even in those who have taken acetaminophen previously without incident, and there is no way of predicting who might be most at risk.

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