Multi-Biomarker Prediction Models for Multiple Infection Episodes Following Blunt Trauma.

ABSTRACT: Severe trauma predisposes patients to multiple independent infection episodes (MIIEs), leading to augmented morbidity and mortality. We developed a method to identify increased MIIE risk before clinical signs appear, which is fundamentally different from existing approaches entailing infections' detection after their establishment. Applying machine learning algorithms to genome-wide transcriptome data from 128 adult blunt trauma patients' (42 MIIE cases and 85 non-cases) leukocytes collected ≤48 hr of injury and ≥3 days before any infection, we constructed a 15-transcript and a 26-transcript multi-biomarker panel model with the least absolute shrinkage and selection operator (LASSO) and Elastic Net, respectively, which accurately predicted MIIE (Area Under Receiver Operating Characteristic

SUBMITTER: Tsurumi A 

PROVIDER: S-EPMC7539926 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature