Establishment of a bloodstream infection clusters prediction score in critically ill patients: an analysis of two-center retrospective cohorts

Abstract

Abstract Background: Bloodstream infections (BSI) are highly prevalent in hospitalized patients requiring intensive care. They are among the most serious infections amd are highly associated with sepsis or septic shock, which can lead to prolonged hospital stays and high healthcare costs. This study aimed at establishingan easy-to-use nomogram for predicting the prognosis of patients with BSI. Methods:This retrospective cohort study was performed between Jan 1, 2016, and Dec 31, 2021. It included BSI patients admitted to two intensive care units (ICUs) in the First Affiliated Hospital of Xiamen University (discovery cohort)and First Hospital of Shanxi Medical University (validation cohort). Their demographic and clinical data were collected, and a nomogram was developed for the discovery cohort. The developed nomogram wasexternally validated using patients in the validation cohort over a similar period. Results: A total of 360 patients in the discovery cohort and 310 patients in the validation cohort were included in statistical analyses. Four independent predictors (vasoconstrictor use before BSI, mechanical ventilation (MV) before BSI, Deep vein catheterization (DVC) before BSI, and antibiotic use before BSI) were identified and used to develop a bloodstream infections clustering (BSIC) score. Patients with scores of 0 to 4 were included in cluster 1, while those with scores of 5 to 8 were included in cluster 2. The Kaplan-Meier curve revealed a higher risk of death for cluster 2 when compared with cluster 1. Conclusion: The developed score has potential applications in the identification of high-risk critically ill BSI patients.