Prevalence and clinical implication of thrombocytopenia and heparin-induced thrombocytopenia in patients who are critically ill with COVID-19.

As the COVID-19 pandemic continues to evolve, different clinical manifestations are better understood and studied. These include various haematologic disorders that have been shown to be associated with increased morbidity and mortality. We studied the prevalence of one unusual manifestation, heparin-induced thrombocytopenia (HIT) and its clinical implications in patients who are severely ill with COVID-19 in a single tertiary centre in Israel. The presence of thrombocytopenia, disseminated intravascular coagulation (DIC) and HIT, and their association with clinical course and outcomes were studied. One-hundred and seven patients with COVID-19 were included. Fifty-seven (53.2%) patients developed thrombocytopenia, which was associated with the worst outcomes (ventilation, DIC and increased mortality). Sixteen (28.0%) patients with thrombocytopenia were positive for HIT, all of which were supported by extracorporeal devices. HIT was independently associated with ventilation days, blood product transfusions, longer hospitalisation and mortality.Platelet abnormalities and HIT are common in patients who are critically ill with COVID-19 and are associated with the worst clinical outcomes. The mechanisms underlying HIT in COVID-19 are yet to be studied; HIT may contribute to the dysregulated immunologic response associated with COVID-19 critical illness and may play a significant part in the coagulopathy seen in these patients. As many patients with COVID-19 require aggressive thromboprophylaxis, further understanding of HIT and the implementation of appropriate protocols are important.

USING ARTIFICIAL INTELLIGENCE MODELS TO PREDICT DETERIORATION IN CRITICALLY ILL COVID-19 PATIENTS

B Introduction: b The COVID-19 pandemic resulted in a surge of critically ill adults that presented significant challenges to critical care providers. B Conclusions: b We have demonstrated that predictive models that were developed, trained and validated to predict respiratory failure and hemodynamic instability in non-COVID patients had reasonable performance in predicting deterioration in COVID-19 critically ill patients. [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)