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Predictors and patterns of empirical antibiotic therapy and associated outcomes in COVID-19 patients: a retrospective study in a tertiary care facility in South India

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The coronavirus disease (COVID-19) led to a global health crisis. Inappropriate use of antibiotics in COVID-19 patients has been a concern, leading to antimicrobial resistance. This study evaluated the patterns and predictors of empirical antibiotic therapy in COVID-19 patients and associated outcomes. Methods: A hospital-based retrospective study was conducted with 525 patients admitted to Kasturba Hospital, Manipal, India, with moderate and severe COVID-19 from 1 March to 1 August 2021. They were divided based on empirical therapy, and predictors of antibiotic usage were assessed by logistic regression. Results: Four hundred and eighty (91.4%) COVID-19 patients received at least one course of antibiotics, with 440 (83.8%) initiating empirical therapy. Patients with severe COVID-19 manifestations were more likely to be prescribed empirical antibiotics. Multivariable analysis showed that patients initiated on empirical antibiotics had significantly elevated levels of procalcitonin [OR: 3.91 (95% CI: 1.66–9.16) (p = 0.001)], invasive ventilation [OR: 3.93 (95% CI: 1.70–9.09) (p = 0.001)], shortness of breath [OR: 2.25 (95% CI: 1.30–3.89) (p = 0.003)] and higher CRP levels [OR: 1.01 (95% CI: 1.00–1.01) (p = 0.005)]. Most antibiotics (65.9%) were prescribed from the ‘Watch’ group, the highest being ceftriaxone. Only 23.8% of the patients had microbiologically confirmed infections. Conclusion: The study identified predictors for initiating empirical antibacterial therapy in our setting.

Original languageEnglish
Pages (from-to)333-341
Number of pages9
JournalExpert Review of Anti-Infective Therapy
Volume22
Issue number5
DOIs
Publication statusPublished - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Microbiology (medical)
  • Infectious Diseases
  • Virology

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