Risk stratification and data-driven phenotyping of peripherally inserted central catheter-related bloodstream infection: an explainable machine learning analysis of a large critical care cohort.

Abstract excerpt

BACKGROUND: Peripherally inserted central catheter-related bloodstream infections (PICC-CRBSIs) are significant causes of morbidity and mortality in critically ill patients. Therefore, improved risk stratification is required for targeted prevention. This study aimed to identify key predictors and novel patient phenotypes of PICC-CRBSI using explainable machine learning. METHODS: We conducted a retrospective...

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