Endothelial Activation and Stress Index (EASIX) as an Early Predictor for Mortality and Overall Survival in Hematological and Non-Hematological Patients with COVID-19: Multicenter Cohort Study

Autor: Marta Rosiek-Biegus, Aleksander Zińczuk, Łukasz Szukalski, Marta Morawska, Elżbieta Kalicińska, Tomasz Wróbel, Justyna Rybka, Joanna Drozd-Sokołowska, Krzysztof Simon, Paula Jabłonowska, Monika Biernat, Marcin Rymko, Justyna Janocha-Litwin, Anna Waszczuk-Gajda
Rok vydání: 2021
Předmět:
Zdroj: Journal of Clinical Medicine
Volume 10
Issue 19
Journal of Clinical Medicine, Vol 10, Iss 4373, p 4373 (2021)
ISSN: 2077-0383
DOI: 10.3390/jcm10194373
Popis: COVID-19, as a disease involving the endothelium of multiple organs, is characterized by high mortality rates among hospitalized patients. Patients with hematological malignancies are particularly at risk of an unfavorable course of COVID-19. The endothelial activation and stress index (EASIX) score has been used as a simple predictor of overall survival (OS) in specific groups of hematological cancer patients. EASIX, as a biomarker of endothelial dysfunction, might play a prognostic role in patients with COVID-19. Here, we performed a comprehensive retrospective analysis of the EASIX score in 523 hospitalized COVID-19 patients with or without coexisting hematological cancer. Hematological cancer COVID-19 patients had higher EASIX scores compared to the overall population with COVID-19. In hematological patients, EASIX was a strong predictor of the occurrence of sepsis during COVID-19. Our findings demonstrated EASIX as a strong predictor of intensive care unit admission, in-hospital mortality, the occurrence of acute renal failure and the need for hemodialysis, both in hematological and non-hematological COVID-19 patients. Patients with a high EASIX score on COVID-19 diagnosis had significantly inferior OS compared to patients with low EASIX. We showed for the first time that EASIX might serve as a simple, universal prognostic tool of OS in both hematological and non-hematological COVID-19 patients.
Databáze: OpenAIRE
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