Prognostic factors of acetaminophen exposure in the United States: An analysis of 39,000 patients.
Omid MehrpourFarhad SaeediAli HadianfarBruno MégarbaneChristopher HoytePublished in: Human & experimental toxicology (2021)
Acetaminophen is a frequently used over-the-counter or prescribed medication in the United States. Exposure to acetaminophen can lead to acute liver cytolysis, acute liver failure, acute kidney injury, encephalopathy, and coagulopathy. This retrospective cohort study (1/1/2012 to 12/31/2017) investigated the clinical outcomes of intentional and unintentional acetaminophen exposure using the National Poison Data System data. The frequency of outcomes, chronicity, gender, route of exposure, the reasons for exposure, and treatments as described. Binary logistic regression was used to estimate the prognostic factors and odds ratios (OR) with 95% confidence intervals (CI) for outcomes. This study included 39,022 patients with acetaminophen exposure. Our study demonstrated that the likelihood of developing severe outcomes increased by aging (OR = 1.12, 95% CI: 1.08-1.015) and was lower in females (OR = 0.88, 95% CI: 0.78-0.99). Drowsiness/lethargy (OR = 1.48, 95% CI: 1.22-1.82), agitation (OR = 1.66, 95% CI: 1.11-2.50), coma (OR = 23.95, 95% CI: 17.05-33.64), bradycardia (OR = 2.29, 95% CI: 1.22-4.32), rhabdomyolysis (OR = 8.84, 95% CI: 3.71-21.03), hypothermia (OR = 4.1, 95% CI: 1.77-9.51), and hyperthermia 2.10 (OR = 2.10, 95% CI: 1.04-4.22) were likely associated with major outcomes or death. Treatments included intravenous N-acetylcysteine (61%), oral N-acetylcysteine (10%), vasopressor (1%), hemodialysis (0.7%), fomepizole (0.1%), hemoperfusion (0.03%), and liver transplant (0.1%). In conclusion, it is important to consider clinical presentations of patients with acetaminophen toxicity that result in major outcomes and mortality to treat them effectively.
Keyphrases
- liver failure
- prognostic factors
- liver injury
- acute kidney injury
- drug induced
- cardiac surgery
- emergency department
- machine learning
- low dose
- big data
- adipose tissue
- respiratory failure
- mass spectrometry
- cardiovascular events
- coronary artery disease
- insulin resistance
- artificial intelligence
- peritoneal dialysis
- end stage renal disease
- high speed
- single molecule