thesis
oaioai:amsdottorato.cib.unibo.it:8457

Biomarker di sepsi e disfunzione d'organo nel cane e nel gatto

Abstract

Background Multiorgan dysfunction syndrome (MODS), the progressive dysfunction of organ systems following an acute threat to systemic homeostasis, is a common complication of systemic inflammatory response syndrome (SIRS) and sepsis in the intensive care unit (ICU). Bloodstream biomarkers for MODS prediction and prognostication have received growing attention in human medicine. Literature concerning MODS occurrence and significance is scant in dogs and absent in cats. Criteria for the systematic evaluation of organ dysfunction are lacking, and the use of diagnostic and prognostic biomarkers is limited in veterinary critical care medicine. Aims The aim of the proposed research is to investigate novel biomarkers for the prediction of illness severity, organ dysfunction and prognosis in critical dogs and cats hospitalized in the ICU of a veterinary university hospital (VUH). Materials and Methods Critically ill dogs and cats hospitalized in the ICU of the VUH of Bologna during the PhD (2014-2017) and diagnosed with SIRS and sepsis have been selected for the studies. Conclusion The role of biomarkers is becoming crucial in critical care medicine, as they can assist in patient management and predict early and late complications of critical illness. The present thesis contributes to characterize SIRS and sepsis in dogs and cats, and gives novel insights on biomarkers of disease severity and organ dysfunction. A systematic screening for MODS has been proposed in the performed studies, highlighting the need to early recognize this condition at the time of ICU admission and during hospital stay. The prognostic impact of selected organ dysfunction and MODS development has been observed. The presented results improve our understanding of the host response to inflammation and infection, and are the basis for an on-going process to characterize MODS and its sequelae in critical care veterinary medicine

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oaioai:amsdottorato.cib.unibo.it:8457Last time updated on 1/3/2019View original full text link

This paper was published in AMS Tesi di Dottorato.

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