Unit:
Κατεύθυνση Κλινικές Μελέτες: Σχεδιασμός και ΕκτέλεσηLibrary of the School of Health Sciences
Author:
Symeonidou Ioanna-Eleni
Supervisors info:
Σεργεντάνης Θεόδωρος, Επίκουρος Καθηγητής, Τμήμα Πολιτικών Δημόσιας Υγείας, ΠΑΔΑ
Γαβριατοπούλου Μαρία, Επίκουρη Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Ψαλτοπούλου Θεοδώρα, Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Original Title:
Προγνωστικά συστήματα για τη θνητότητα της COVID-19 λοίμωξης: βιβλιογραφική ανασκόπηση
Translated title:
Prognostic models for predicting mortality of COVID-19 patients: literature review
Summary:
The COVID-19 pandemic has put enormous pressure on healthcare systems all over the world. Clinical manifestations and symptoms of COVID-19 infection are very heterogeneous and range from asymptomatic clinical picture or mild respiratory symptoms to very severe pneumonia or even acute respiratory distress syndrome (ARDS), septic shock and multiple organ dysfunction. In those severe cases, COVID-19 patients need to be transferred to intensive care units (ICU) for mechanical ventilation or/and intubation. The use of prognostic models that combine several clinical, laboratory, demographic data or/and imaging features in order to estimate the risk of COVID-19 patients deteriorating or even dying, are of great importance and usefulness for triaging patients and for clinical decision-making.
This study presents a literature review on prognostic models which aim to predict COVID-19 mortality. We first present studies evaluating the potential prognostic value in COVID-19 patients of established scoring systems that are widely used in other conditions to stratify risk and predict outcomes. We then include new COVID-19-specific prognostic models and stratification tools, which have been developed and/or validated the last years in order to predict mortality of patients with COVID-19. Analysis of the established scores showed a wide variation between studies in terms of their performance in COVID-19 patients. Similarly, although several new prognostic models show high performance, many lack generalizability due to insufficient validation. Therefore, multicenter prospective studies are needed to validate the predictive models and draw firm conclusions regarding their performance and clinical potential.
Main subject category:
Health Sciences
Keywords:
Mortality of COVID-19, Prognostic models, Nomograms
Number of references:
147
File:
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Symeonidou_Ioanna_Eleni_Msc.pdf
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File access is restricted only to the intranet of UoA.
