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Exploring Prior Antibiotic Exposure Characteristics for COVID-19 Hospital Admission Patients: OpenSAFELY

Authors :
Ya-Ting Yang
David Wong
Xiaomin Zhong
Ali Fahmi
Darren M. Ashcroft
Kieran Hand
Jon Massey
Brian Mackenna
Amir Mehrkar
Sebastian Bacon
Ben Goldacre
Victoria Palin
Tjeerd van Staa
Source :
Antibiotics, Vol 13, Iss 6, p 566 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Previous studies have demonstrated the association between antibiotic use and severe COVID-19 outcomes. This study aimed to explore detailed antibiotic exposure characteristics among COVID-19 patients. Using the OpenSAFELY platform, which integrates extensive health data and covers 40% of the population in England, the study analysed 3.16 million COVID-19 patients with at least two prior antibiotic prescriptions. These patients were compared to up to six matched controls without hospitalisation records. A machine learning model categorised patients into ten groups based on their antibiotic exposure history over the three years before their COVID-19 diagnosis. The study found that for COVID-19 patients, the total number of prior antibiotic prescriptions, diversity of antibiotic types, broad-spectrum antibiotic prescriptions, time between first and last antibiotics, and recent antibiotic use were associated with an increased risk of severe COVID-19 outcomes. Patients in the highest decile of antibiotic exposure had an adjusted odds ratio of 4.8 for severe outcomes compared to those in the lowest decile. These findings suggest a potential link between extensive antibiotic use and the risk of severe COVID-19. This highlights the need for more judicious antibiotic prescribing in primary care, primarily for patients with higher risks of infection-related complications, which may better offset the potential adverse effects of repeated antibiotic use.

Details

Language :
English
ISSN :
20796382
Volume :
13
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Antibiotics
Publication Type :
Academic Journal
Accession number :
edsdoj.38005afc32e44b33a9bb21eb0e349c89
Document Type :
article
Full Text :
https://doi.org/10.3390/antibiotics13060566