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dc.contributor.authorMcRae, Michael P et al.
dc.date.accessioned2020-06-30T19:01:52Z
dc.date.available2020-06-30T19:01:52Z
dc.date.issued2020-06-03
dc.identifier.urihttps://doi.org/10.1039/D0LC00373Een_US
dc.identifier.urihttps://hdl.handle.net/20.500.12663/1866
dc.description.abstractSARS-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.en_US
dc.languageEnglishen_US
dc.subjectCOVID-19en_US
dc.subjectCoronavirusen_US
dc.subjectBetacoronavirusen_US
dc.subjectIntensive Care Unitsen_US
dc.subjectPolymerase Chain Reactionen_US
dc.subjectClinical Decision-Makingen_US
dc.titleClinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19en_US
eihealth.countryGlobal (WHO/OMS)en_US
eihealth.categoryInfection prevention and control, including health care workers protectionen_US
eihealth.typePublished Articleen_US
eihealth.maincategoryProtect Health Care Workers / Proteger la Salud de los Trabajadoresen_US
dc.relation.ispartofjournalLab Chipen_US


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