In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 1 ( 2022-1-14), p. e0262600-
Abstract:
In patients with severe forms of COVID-19, thromboelastometry has been reported to display a hypercoagulant pattern. However, an algorithm to differentiate severe COVID-19 patients from nonsevere patients and healthy controls based on thromboelastometry parameters has not been developed. Forty-one patients over 18 years of age with positive qRT-PCR for SARS-CoV-2 were classified according to the severity of the disease: nonsevere (NS, n = 20) or severe (S, n = 21). A healthy control (HC, n = 9) group was also examined. Blood samples from all participants were tested by extrinsic (EXTEM), intrinsic (INTEM), non-activated (NATEM) and functional assessment of fibrinogen (FIBTEM) assays of thromboelastometry. The thrombodynamic potential index (TPI) was also calculated. Severe COVID-19 patients exhibited a thromboelastometry profile with clear hypercoagulability, which was significantly different from the NS and HC groups. Nonsevere COVID-19 cases showed a trend to thrombotic pole. The NATEM test suggested that nonsevere and severe COVID-19 patients presented endogenous coagulation activation (reduced clotting time and clot formation time). TPI data were significantly different between the NS and S groups. The maximum clot firmness profile obtained by FIBTEM showed moderate/elevated accuracy to differentiate severe patients from NS and HC. A decision tree algorithm based on the FIBTEM-MCF profile was proposed to differentiate S from HC and NS. Thromboelastometric parameters are a useful tool to differentiate the coagulation profile of nonsevere and severe COVID-19 patients for therapeutic intervention purposes.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0262600
DOI:
10.1371/journal.pone.0262600.g001
DOI:
10.1371/journal.pone.0262600.g002
DOI:
10.1371/journal.pone.0262600.g003
DOI:
10.1371/journal.pone.0262600.g004
DOI:
10.1371/journal.pone.0262600.g005
DOI:
10.1371/journal.pone.0262600.t001
DOI:
10.1371/journal.pone.0262600.t002
DOI:
10.1371/journal.pone.0262600.t003
DOI:
10.1371/journal.pone.0262600.s001
DOI:
10.1371/journal.pone.0262600.s002
DOI:
10.1371/journal.pone.0262600.r001
DOI:
10.1371/journal.pone.0262600.r002
DOI:
10.1371/journal.pone.0262600.r003
DOI:
10.1371/journal.pone.0262600.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2267670-3
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