Validation of a Whole Blood Machine Learning Strategy for Distinguishing Between Bacterial and Viral Infection in a Pediatric Hospital Setting

Authors

Ridwan B Ibrahim
Herda Ona
Anil K Chokkalla
Estella Tam
Sridevi Devaraj

Language

English

Publication Date

3-1-2024

Journal

Practical Laboratory Medicine

DOI

10.1016/j.plabm.2024.e00387

PMID

38511106

PMCID

PMC10952075

PubMedCentral® Posted Date

3-12-2024

PubMedCentral® Full Text Version

Post-print

Abstract

Similar symptoms between viral and bacterial diseases often make diagnosis difficult. This study assessed the clinical performance of the newly cleared whole-blood Bacterial versus Viral Score assay in our pediatric cohort to the previously validated serum assay and emergency department physician diagnosis. This assay shows excellent agreement (R = 0.997) with the serum assay and has great diagnostic accuracy when compared to physician diagnosis.

Keywords

Infection, Viremia, Bacteraemia, Antibiotics

Published Open-Access

yes

Recommended Citation

Ibrahim, Ridwan B; Ona, Herda; Chokkalla, Anil K; et al., "Validation of a Whole Blood Machine Learning Strategy for Distinguishing Between Bacterial and Viral Infection in a Pediatric Hospital Setting" (2024). Faculty and Staff Publications. 2882.
https://digitalcommons.library.tmc.edu/baylor_docs/2882