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Journal Article

Citation

Weinstein RB, Schuemie MJ, Ryan PB, Stang PE. Drug Healthc. Patient Saf. 2016; 8: 39-48.

Affiliation

Epidemiology, Janssen Research and Development, LLC, Titusville, NJ, USA.

Copyright

(Copyright © 2016, Dove Press)

DOI

10.2147/DHPS.S95399

PMID

27099532

PMCID

PMC4824282

Abstract

BACKGROUND: Presumed seasonal use of acetaminophen-containing products for relief of cold/influenza ("flu") symptoms suggests that there might also be a corresponding seasonal pattern for acute liver injury (ALI), a known clinical consequence of acetaminophen overdose.

OBJECTIVE: The objective of this study was to determine whether there were any temporal patterns in hospitalizations for ALI that would correspond to assumed acetaminophen use in cold/flu season.

METHODS: In the period 2002-2010, monthly hospitalization rates for ALI using a variety of case definitions were calculated. Data sources included Truven MarketScan(®) Commercial Claims and Encounters (CCAE) and Medicare Supplemental and Coordination of Benefits (MDCR) databases. We performed a statistical test for seasonality of diagnoses using the periodic generalized linear model. To validate that the test can distinguish seasonal from nonseasonal patterns, we included two positive controls (ie, diagnoses of the common cold [acute nasopharyngitis] and influenza), believed to change with seasons, and two negative controls (female breast cancer and diabetes), believed to be insensitive to season.

RESULTS: A seasonal pattern was observed in monthly rates for common cold and influenza diagnoses, but this pattern was not observed for monthly rates of ALI, with or without comorbidities (cirrhosis or hepatitis), breast cancer, or diabetes. The statistical test for seasonality was significant for positive controls (P<0.001 for each diagnosis in both databases) and nonsignificant for ALI and negative controls.

CONCLUSION: No seasonal pattern was observed in the diagnosis of ALI. The positive and negative controls showed the expected patterns, strengthening the validity of the statistical and visual tests used for detecting seasonality.


Language: en

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