Open AccessCOVID-19–Associated Coagulopathy and Inflammatory Response: What Do We Know Already and What Are the Knowledge Gaps?
Author(s) -
Klaus Görlinger,
Daniel Dirkmann,
Ajay Gandhi,
Paolo Simioni
Publication year - 2020
Publication title -
anesthesia and analgesia/anesthesia and analgesia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.404
H-Index - 201
eISSN - 1526-7598
pISSN - 0003-2999
DOI - 10.1213/ane.0000000000005147
Subject(s) - coagulopathy , medicine , thromboelastometry , intensive care medicine , disseminated intravascular coagulation , intensive care unit , sepsis , extracorporeal membrane oxygenation
Patients with coronavirus disease 2019 (COVID-19) frequently experience a coagulopathy associated with a high incidence of thrombotic events leading to poor outcomes. Here, biomarkers of coagulation (such as D-dimer, fibrinogen, platelet count), inflammation (such as interleukin-6), and immunity (such as lymphocyte count) as well as clinical scoring systems (such as sequential organ failure assessment [SOFA], International Society on Thrombosis and Hemostasis disseminated intravascular coagulation [ISTH DIC], and sepsis-induced coagulopathy [SIC] score) can be helpful in predicting clinical course, need for hospital resources (such as intensive care unit [ICU] beds, intubation and ventilator therapy, and extracorporeal membrane oxygenation [ECMO]) and patient's outcome in patients with COVID-19. However, therapeutic options are actually limited to unspecific supportive therapy. Whether viscoelastic testing can provide additional value in predicting clinical course, need for hospital resources and patient's outcome or in guiding anticoagulation in COVID-19-associated coagulopathy is still incompletely understood and currently under investigation (eg, in the rotational thromboelastometry analysis and standard coagulation tests in hospitalized patients with COVID-19 [ROHOCO] study). This article summarizes what we know already about COVID-19-associated coagulopathy and-perhaps even more importantly-characterizes important knowledge gaps.