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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. MDW, PCT, CRP, and PSP were evaluated at admission (T0), after 24 h (T24), 48 h (T48), 72 h (T72), at day 5 (T5), and at discharge (TD). Results: Patients with sepsis displayed higher levels of PCT and PSP than patients without sepsis at each timepoint; differently, CRP displayed statistically significant differences only at T0, while MDW only at T0 and T24. Patients with increasing levels of PSP displayed lower median survival time than patients with decreasing levels; differences reached statistical significance only at 48 h (20 vs. 29 days, log rank test, p = 0.046). Interestingly, PSP was an independent predictor of ICU mortality at 48 and 72 h after hospital admission. Also, the kinetic of PSP had prognostic value, with increased values at 48 h after admission being associated with reduced survival. Conclusion: Our findings support the role of PSP and its kinetic as a predictor of ICU mortality.
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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. At admission, patients were classified as septic or not according to Sepsis-3 criteria. MDW, CRP, PCT, and lactate were measured daily in the first 5 days of hospitalization. ICU mortality was also recorded. RESULTS: We included 193 patients, 62 with sepsis and 131 without sepsis (controls). 58% and 26â¯% of the patients, with and without sepsis respectively, died during ICU stay. MDW showed the highest accuracy for sepsis detection, superior to CRP, PCT, and lactate (AUC of 0.840, 0.755, 0.708, 0.622, respectively). At admission, no biomarker predicts ICU mortality in patients with sepsis. The kinetic of all biomarkers during the first 5 days of hospitalization was associated with ICU mortality. Noteworthy, above all, the kinetic of MDW showed the best accuracy. Specifically, an increase or decrease in MDW from day 1-4 and 5 was significantly associated with mortality or survival, respectively. CONCLUSIONS: MDW is a reliable diagnostic and prognostic sepsis biomarker, better than traditional biomarkers.
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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., sex and age, and laboratory parameters, i.e., cell blood count (CBC) parameters, inclusive of monocyte distribution width (MDW), and C-reactive protein (CRP). The dataset included 1667 PCT measurements of different patients. Based on a PCT cut-off of 0.50 ng/mL, we found 1090 negative (65.4%) and 577 positive (34.6%) results. We performed a 70:15:15 train:validation:test splitting based on the outcome. Results: Random Forest, Support Vector Machine and eXtreme Gradient Boosting showed optimal performances for predicting PCT positivity, with an area under the curve ranging from 0.88 to 0.89. Conclusions: The ML models developed could represent a useful tool to predict PCT positivity, avoiding unusefulness PCT requests. ML models are based on laboratory tests commonly ordered together with PCT but have the great advantage to be easy to measure and low-cost.
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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. In this article, we explore the relationship between MDW and the different pathogens causing infection. Noteworthy, MDW is not a biological molecule, but it is calculated by a mathematical formula based on monocyte characteristics. Monocytes represent the first line defence against microorganisms and undergo activation upon infection, independently from the invading pathogen. According to the knowledge on the biomarker biology and the few literatures evidence, MDW may be considered a biomarker of sepsis, independent of the causative pathogen. However, further investigations are warranted before drawing definite conclusion.
