TY - JOUR
T1 - Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19
AU - McRae, Michael P.
AU - Simmons, Glennon W.
AU - Christodoulides, Nicolaos J.
AU - Lu, Zhibing
AU - Kang, Stella K.
AU - Fenyo, David
AU - Alcorn, Timothy
AU - Dapkins, Isaac P.
AU - Sharif, Iman
AU - Vurmaz, Deniz
AU - Modak, Sayli S.
AU - Srinivasan, Kritika
AU - Warhadpande, Shruti
AU - Shrivastav, Ravi
AU - McDevitt, John T.
N1 - Funding Information:
Funding was provided by NIH through the National Institute of Dental and Craniofacial Research (NIH grant no. 3U01DE017793-02S1 and 5U01DE017793-2). The content is solely the responsibility of the authors and does not necessarily represent or reflect views of the NIH, or the Federal Government.
Publisher Copyright:
© 2020 The Royal Society of Chemistry.
PY - 2020/6/21
Y1 - 2020/6/21
N2 - SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). Although this analysis represents patients with cardiac comorbidities (hypertension), the inclusion of biomarkers from other pathophysiologies implicated in COVID-19 (e.g., D-dimer for thrombotic events, CRP for infection or inflammation, and PCT for bacterial co-infection and sepsis) may improve future predictions for a more general population. These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.
AB - SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). Although this analysis represents patients with cardiac comorbidities (hypertension), the inclusion of biomarkers from other pathophysiologies implicated in COVID-19 (e.g., D-dimer for thrombotic events, CRP for infection or inflammation, and PCT for bacterial co-infection and sepsis) may improve future predictions for a more general population. These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.
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UR - http://www.scopus.com/inward/citedby.url?scp=85086682019&partnerID=8YFLogxK
U2 - 10.1039/d0lc00373e
DO - 10.1039/d0lc00373e
M3 - Article
C2 - 32490853
AN - SCOPUS:85086682019
VL - 20
SP - 2075
EP - 2085
JO - Lab on a Chip - Miniaturisation for Chemistry and Biology
JF - Lab on a Chip - Miniaturisation for Chemistry and Biology
SN - 1473-0197
IS - 12
ER -