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The Impact of Early Antibiotic Use on Clinical Outcomes of Patients Hospitalized with COVID-19: A Propensity Score-Matched Analysis (preprint)
researchsquare; 2023.
Preprint
in English
| PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-3751132.v1
ABSTRACT
Background:
Early empiric antibiotics were prescribed to numerous patients during the Coronavirus disease 2019(COVID-19) pandemic. However, the potential impact of empiric antibiotic therapy on the clinical outcomes of patients hospitalized with COVID-19 is yet unknown.Methods:
We conducted a retrospective cohort study in West China Hospital of Sichuan University between Dec 2022 to Mar 2023. The 12 propensity score matched patient populations were further developed to adjust confounding factors.Results:
We included a total of 1472 COVID-19 hospitalized patients, of whom 87.4% (1287 patients) received early antibiotic prescriptions. In propensity-score-matched datasets, our analysis comprised 139 patients withnon-antibiotic use(with 278 matched controls) and 27 patients withdeferred-antibiotic use(with 54 matched controls). Patients with older ages, multiple comorbidities, severe and critical COVID-19 subtypes, higher serum infection indicators and inflammatory indicators at admission were more likely to receive early antibiotic prescriptions. After adjusting confounding factors likely to influence the prognosis, no significant difference in all-cause mortality(HR=1.000(0.246-4.060), p=1.000) and ICU admission(HR=0.436(0.093-2.04), p=0.293)), need for mechanical ventilation(HR=0.723(0.296-1.763), p=0.476)) and tracheal intubation(HR=1.338(0.221-8.103), p=0.751)) were observed between early antibiotics use cohort and non-antibiotic use cohort.Conclusions:
Early antibiotics were frequently prescribed to patients in more severe disease condition at admission. However, early antibiotic treatment failed to demonstrate better clinical outcomes in hospitalized patients with COVID-19 in the propensity-score-matched cohorts.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-RESEARCHSQUARE
Main subject:
COVID-19
Language:
English
Year:
2023
Document Type:
Preprint
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