Faculty, Staff and Student Publications
Language
English
Publication Date
7-14-2023
Journal
Journal of Clinical Medicine
DOI
10.3390/jcm12144688
PMID
37510807
PMCID
PMC10381000
PubMedCentral® Posted Date
July 2023
PubMedCentral® Full Text Version
Post-print
Abstract
In COVID-19 patients, antibiotics overuse is still an issue. A predictive scoring model for the diagnosis of bacterial pneumonia at intensive care unit (ICU) admission would be a useful stewardship tool. We performed a multicenter observational study including 331 COVID-19 patients requiring invasive mechanical ventilation at ICU admission; 179 patients with bacterial pneumonia; and 152 displaying negative lower-respiratory samplings. A multivariable logistic regression model was built to identify predictors of pulmonary co-infections, and a composite risk score was developed using β-coefficients. We identified seven variables as predictors of bacterial pneumonia: vaccination status (OR 7.01; 95% CI, 1.73-28.39); chronic kidney disease (OR 3.16; 95% CI, 1.15-8.71); pre-ICU hospital length of stay ≥ 5 days (OR 1.94; 95% CI, 1.11-3.4); neutrophils ≥ 9.41 × 10
Keywords
bacterial co-infection, COVID-19, bacterial pneumonia, prognostic tool, antimicrobial stewardship
Published Open-Access
yes
Recommended Citation
Tanzarella, Eloisa Sofia; Vargas, Joel; Menghini, Marco; et al., "An Observational Study To Develop A Predictive Model For Bacterial Pneumonia Diagnosis In Severe COVID-19 Patients-C19-Pneumoscore" (2023). Faculty, Staff and Student Publications. 1375.
https://digitalcommons.library.tmc.edu/uthmed_docs/1375
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