Acetaminophen for the patent ductus arteriosus: has safety been adequately demonstrated?
Clyde J WrightDavid J McCulleySouvik MitraErik A JensenPublished in: Journal of perinatology : official journal of the California Perinatal Association (2023)
Patent ductus arteriosus (PDA) is the most common cardiovascular condition diagnosed in premature infants. Acetaminophen was first proposed as a potential treatment for PDA in 2011. Since that time acetaminophen use among extremely preterm neonates has increased substantially. The limited available data demonstrate that acetaminophen reduces PDA without evident hepatotoxicity. These findings have led some to suggest that acetaminophen is a safe and effective therapy for PDA closure. However, the lack of apparent hepatoxicity is predictable. Acetaminophen induced cellular injury is due to CYP2E1 derived metabolites; and hepatocyte CYP2E1 expression is low in the fetal and neonatal period. Here, we review preclinical and clinical data that support the hypothesis that the lung, which expresses high levels of CYP2E1 during fetal and early postnatal development, may be particularly susceptible to acetaminophen induced toxicity. Despite these emerging data, the true potential pulmonary risks and benefits of acetaminophen for PDA closure are largely unknown. The available clinical studies in are marked by significant weakness including low sample sizes and minimal evaluation of extremely preterm infants who are typically at highest risk of pulmonary morbidity. We propose that studies interrogating mechanisms linking developmentally regulated, cell-specific CYP2E1 expression and acetaminophen-induced toxicity as well as robust assessment of pulmonary outcomes in large trials that evaluate the safety and efficacy of acetaminophen in extremely preterm infants are needed.
Keyphrases
- liver injury
- drug induced
- preterm infants
- low birth weight
- pulmonary hypertension
- poor prognosis
- high glucose
- diabetic rats
- electronic health record
- oxidative stress
- magnetic resonance
- smoking cessation
- risk assessment
- insulin resistance
- human health
- machine learning
- single cell
- artificial intelligence
- data analysis
- mesenchymal stem cells
- deep learning