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- Daniela Mazzaccaro, Francesca Giacomazzi, Matteo Giannetta, Alberto Varriale, Rosa Scaramuzzo, Alfredo Modafferi, Giovanni Malacrida, Paolo Righini, Massimiliano M Marrocco-Trischitta, and Giovanni Nano.
- Operative Unit of Vascular Surgery, IRCCS Policlinico San Donato, San Donato Milanese, 20026 Milan, Italy.
- J Clin Med. 2020 Jun 8; 9 (6).
IntroductionAim of the study is to assess the occurrence of early stage coagulopathy and disseminated intravascular coagulation (DIC) in patients with mild to moderate respiratory distress secondary to SARS-CoV-2 infection.Materials And MethodsData of patients hospitalized from 18 March 2020 to 20 April 2020 were retrospectively reviewed. Two scores for the screening of coagulopathy (SIC and non-overt DIC scores) were calculated. The occurrence of thrombotic complication, death, and worsening respiratory function requiring non-invasive ventilation (NIV) or admission to ICU were recorded, and these outcomes were correlated with the results of each score. Chi-square test, receiver-operating characteristic curve, and logistic regression analysis were used as appropriate. p Values < 0.05 were considered statistically significant.ResultsData of 32 patients were analyzed. Overt-DIC was diagnosed in two patients (6.2%), while 26 (81.2%) met the criteria for non-overt DIC. Non-overt DIC score values ≥4 significantly correlated with the need of NIV/ICU (p = 0.02) and with the occurrence of thrombotic complications (p = 0.04). A score ≥4 was the optimal cut-off value, performing better than SIC score (p = 0.0018). Values ≥4 in patients with thrombotic complications were predictive of death (p = 0.03).ConclusionsOvert DIC occurred in 6.2% of non-ICU patients hospitalized for a mild to moderate COVID-19 respiratory distress, while 81.2% fulfilled the criteria for non-overt DIC. The non-overt DIC score performed better than the SIC score in predicting the need of NIV/ICU and the occurrence of thrombotic complications, as well as in predicting mortality in patients with thrombotic complications, with a score ≥4 being detected as the optimal cut-off.
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