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Expert Rev Anti Infect Ther ; 22(5): 333-341, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38189087

RESUMEN

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.


Asunto(s)
Antibacterianos , Tratamiento Farmacológico de COVID-19 , COVID-19 , Centros de Atención Terciaria , Humanos , Antibacterianos/administración & dosificación , India/epidemiología , Estudios Retrospectivos , Masculino , Femenino , Persona de Mediana Edad , Adulto , Anciano , SARS-CoV-2 , Índice de Severidad de la Enfermedad , Pautas de la Práctica en Medicina/estadística & datos numéricos , Respiración Artificial/estadística & datos numéricos
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