Background: In this study, we explored the accuracy of two new sepsis biomarkers, monocyte distribution width (MDW) and presepsin (PSP), compared to traditional ones, C-reactive protein (CRP) and Procalcitonin (PCT), to identify sepsis and predict intra-hospital mortality by analyzing their kinetic at different time points during hospitalization stay.
Methods: We enrolled 104 patients admitted to the intensive care unit (ICU) of University Hospital "Paolo Giaccone", Palermo. Among these, 30 (29%) had a clinical diagnosis of sepsis.
Objectives: Monocyte distribution width (MDW) is a measure of monocyte anisocytosis. In this study, we assessed the role of MDW, in comparison to C-reactive protein (CRP), procalcitonin (PCT), and lactate, as a screening and prognostic biomarker of sepsis in intensive care unit (ICU) by longitudinally measuring it in the first 5 days of hospital stay.
Methods: We considered all consecutive patients admitted to the ICU.
Aim: The aim of this study was to develop machine learning (ML) models to mitigate the inappropriate request of Procalcitonin (PCT) in clinical wards.
Material And Methods: We built six different ML models based on both demographical data, i.e.
Sepsis is a life-threatening syndrome due to a dysregulated host response to infection, which can be caused by bacterial, viral, or fungal infection. Thus, it is crucial to know how the different microorganisms influence the levels of a biomarker. In the last decade, monocyte distribution width (MDW) has emerged as a promising sepsis biomarker, especially in acute settings, such as the Emergency Department and Intensive Care Unit.
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