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Updated: May 6, 2026

Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis
Published on: October 17, 2018
Changing in blood cells for infection detection: "Monocyte distribution width" acts as a key determinant in
Agostino Ognibene1, Maria Lorubbio1, Sara Montemerani2
1Laboratory Medicine Unit, Azienda AUSL Toscana Sudest, San Donato Hospital, Arezzo, Italy.
Background:
Early identification of bloodstream infections (BSI) in the Emergency Department (ED) remains a clinical challenge. Monocyte Distribution Width (MDW), a novel biomarker available from the complete blood count, was prospectively evaluated for its diagnostic and prognostic utility in patients with suspected infection.
Methods:
We conducted a prospective, observational cohort study enrolling 608 adult ED patients. Following a comprehensive diagnostic workup, patients were retrospectively adjudicated into three primary groups: No Infection (n = 196), Localized Infection (n = 235), and Bloodstream Infection (BSI) (n = 134). The diagnostic accuracy of MDW was compared to procalcitonin (PCT) and C-reactive protein (CRP) using receiver operating characteristic (ROC) analysis.
Results:
In this cohort, MDW demonstrated high accuracy for BSI detection (Area Under the Curve [AUC] = 0.936), representing a statistically significant improvement over both PCT (AUC = 0.818; p < 0.0001) and CRP (AUC = 0.829; p < 0.0001). It also showed good accuracy in discriminating localized infections from the no-infection group (AUC = 0.748). Notably, among the biomarkers tested, MDW was the only biomarker significantly elevated in non-survivors compared to survivors (p = 0.001), indicating a unique prognostic value for in-hospital mortality.
Conclusions:
In ED patients with suspected infection, MDW is a highly effective biomarker for the early detetion of BSI, demonstrating significantly higher diagnostic accuracy than PCT and CRP in this study. Its ability to help stratify patients with localized versus systemic infection and to predict mortality makes it a valuable tool for early risk assessment and clinical decision-making.
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