Antibiotics (Jun 2024)

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

  • 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

DOI
https://doi.org/10.3390/antibiotics13060566
Journal volume & issue
Vol. 13, no. 6
p. 566

Abstract

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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.

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