1. Biomarkers of Coagulation and Inflammation in COVID-19-Associated Ischemic Stroke
- Author
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Khadean Moncrieffe, Jorge Luna, Jenelys Fernandez-Torres, David Flomenbaum, Joseph Dardick, Ava L. Liberman, Avinash Malaviya, Daniel L. Labovitz, Nikunj K. Patel, Charles Esenwa, Joshua Z. Willey, Aaron Lord, Joshua A. Benton, Koto Ishida, Inessa Goldman, Peter Mabie, Andrea Lendaris, Aureliana Toma, Shadi Yaghi, Natalie T Cheng, Jose Torres, Kathryn Kirchoff-Torres, Jennifer A. Frontera, Jenny Lu, Ainie Soetanto, Amelia K. Boehme, Thomas Snyder, Ryan Holland, Johanna Seiden, and David J. Altschul
- Subjects
Male ,2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Myocardial Infarction ,Inflammation ,Blood Sedimentation ,Severity of Illness Index ,Fibrin Fibrinogen Degradation Products ,Machine Learning ,Leukocyte Count ,medicine ,ischemic stroke ,Cluster Analysis ,Humans ,Thrombophilia ,Hospital Mortality ,Aged ,Retrospective Studies ,Advanced and Specialized Nursing ,Aged, 80 and over ,Venous Thrombosis ,L-Lactate Dehydrogenase ,business.industry ,Interleukin-6 ,SARS-CoV-2 ,COVID-19 ,Fibrinogen ,Middle Aged ,mortality ,C-Reactive Protein ,Logistic Models ,Coagulation ,Ischemic stroke ,Immunology ,Ferritins ,ComputingMethodologies_DOCUMENTANDTEXTPROCESSING ,Biomarker (medicine) ,biomarker ,Female ,Partial Thromboplastin Time ,Brief Reports ,Neurology (clinical) ,medicine.symptom ,Cardiology and Cardiovascular Medicine ,business ,Pulmonary Embolism - Abstract
Supplemental Digital Content is available in the text., Background and Purpose: We sought to determine if biomarkers of inflammation and coagulation can help define coronavirus disease 2019 (COVID-19)–associated ischemic stroke as a novel acute ischemic stroke (AIS) subtype. Methods: We performed a machine learning cluster analysis of common biomarkers in patients admitted with severe acute respiratory syndrome coronavirus 2 to determine if any were associated with AIS. Findings were validated using aggregate data from 3 large healthcare systems. Results: Clustering grouped 2908 unique patient encounters into 4 unique biomarker phenotypes based on levels of c-reactive protein, D-dimer, lactate dehydrogenase, white blood cell count, and partial thromboplastin time. The most severe cluster phenotype had the highest prevalence of AIS (3.6%, P
- Published
- 2021