Antibiotic use among admitted pediatric patients in the United States with status asthmaticus before and during the COVID-19 pandemic

Abstract

Objective: Hospital admission trends of children with status asthmaticus diminished during the Coronavirus-19 (COVID-19) pandemic of 2020, possibly secondary to several factors such as school closures and use of face masks. What effect this had on antibiotic prescribing practices has yet to be described. The objective of our study was to evaluate the use of antibiotics in hospitalized children with a diagnosis of status asthmaticus before and during the COVID pandemic.Methods: A retrospective cross-sectional analysis was conducted using the TriNetX® cloud-based program with a national and institutional database. Each database was queried for all inpatient pediatric encounters from 3 to 18 years old, admitted with a diagnosis of status asthmaticus in the spring seasons of 2017–2019. Admission data and antibiotic usage were queried during the COVID-19 pandemic year of 2020 from both databases and compared amongst all study years.Results: In 2020, there was an overall decrease in the number of admissions as compared to the average number from 2017–2019, by 76.9% in the national database (p < 0.05) and 91.2% in the institutional database. The rates of antibiotic prescriptions significantly dropped among the national database (p < 0.001, z = 3.39) and remained non-significantly changed among the institutional database (p = 0.944 and z = 0.073).Conclusions: Our study demonstrates that the COVID-19 pandemic year of 2020 coincided with a significant decrease in hospital admissions and antibiotic prescribing prevalence among children with status asthmaticus on a national level. Nonetheless, our reported trends in antibiotic prescribing are still grossly similar to that of pre-pandemic times and may demonstrate a continued need for antimicrobial stewardship.

Keywords:

• Control/Management
• epidemiology
• therapy
• treatment

Acknowledgements

Melanie Keister, Office of Clinical Trials, Stony Brook University, for her assistance in the utilization of TrinetX and in the IRB approval process. Joshua Grossman, Ph.D. candidate in Computational Social Sciences, Stanford University, for assistance with the statistical analysis.

Declaration of interest

No potential conflict of interest was reported by the authors.

Funding

The author(s) reported there is no funding associated with the work featured in this article.