Drug-induced acute interstitial nephritis (AIN) represents a growing cause of renal failure in current medical practice. While antimicrobials and non-steroidal anti-inflammatory drugs are typically associated with drug-induced AIN, few reports have been made on the involvement of other analgesics. We report our experience in managing a 17-year-old female with AIN and subsequent renal injury following an acetaminophen overdose in conjunction with acute alcohol intoxication. It is well established that acetaminophen metabolism, particularly at high doses, produces reactive metabolites that may induce renal and hepatic toxicity. It is also plausible however, that such reactive species could instead alter renal peptide immunogenicity, thereby inducing AIN. In the following report, we review a possible mechanism for the acetaminophen-induced AIN observed in our patient and also discuss the potential involvement of acute alcohol ingestion in disease onset. The objective of our report is to increase awareness of healthcare professionals to the potential involvement of these commonly used agents in AIN pathogenesis.
BackgroundCA-CDI accounts for up to 50% of all CDIs. Case–control studies (CCS) have been used to estimate the odds ratio (OR) of CA-CDI associated with antibiotic exposure. These ORs demonstrate significant heterogeneity across studies. Unlike CCS, a self-controlled case series (SCCS) design can be used to control for all time-invariant confounders leading to less biased effect estimates.MethodsAdults (≥18 years) registered (N = 139,670) with the Barrie and Community Family Health Team (BCFHT) were included in the study. Cases were defined as any patient with an incident case of CA-CDI and ≥1 antibiotic exposure occurring between January 1, 2011 and December 31, 2016. The SCCS model was used to estimate the association between antibiotic exposure and CA-CDI. The SCCS model yields estimates of the relative incidence rate of CA-CDI in exposure periods relative to non-exposure periods within a case. Exposure periods were defined as starting two days after any antibiotic prescription and ending 60 days later. Multiple exposure periods and time-varying confounders due to calendar year were included in the final model. The relative incidence rate ratio (IRR) was estimated using conditional poisson regression analysis. Proton pump inhibitor (PPI) use was included as an effect modifier. Antibiotics were divided into high-risk (fluoroquinolone, clindamycin, and cephalosporin) and low-risk exposures. Research ethics approval was obtained from the BFCHT research ethics board.ResultsAmong 544 total CDI cases, N = 189 CA-CDI cases met the inclusion criteria. Any antibiotic exposure increases the risk by ≥2-fold, with no difference observed between high and low-risk groups (IRR=1.11, 95% CI 0.53–2.36) (Table 1).ConclusionAntibiotic exposure increases the risk of CA-CDI, with IRR estimates similar to those observed for healthcare-associated-CDI. This, along with the control of all time-invariant confounders by the SCCS method suggests a less biased effect estimate previously reported from CCS.Table 1
Variable
IRR
95% Confidence Interval
P-value
Antibiotic Exposure GroupPPINoneYes0.80(0.62–1.03)0.09Low riskYes1.95(0.09–4.24)0.09High riskYes1.20(0.42–3.40)0.73OverallLow risk2.03(1.19–3.47)0.009High risk2.26(1.29–3.98)0.005Disclosures
All authors: No reported disclosures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.