Machine Learning Highlights Downtrending of COVID-19 Patients with a Distinct Laboratory Profile

He S Yang; Yu Hou; Hao Zhang; Amy Chadburn; Lars F Westblade; Richard Fedeli; Peter A D Steel; Sabrina E Racine-Brzostek; Priya Velu; Jorge L Sepulveda; Michael J Satlin; Melissa M Cushing; Rainu Kaushal; Zhen Zhao; Fei Wang

doi:10.34133/2021/7574903

Machine Learning Highlights Downtrending of COVID-19 Patients with a Distinct Laboratory Profile

Health Data Sci. 2021 Jun 16:2021:7574903. doi: 10.34133/2021/7574903. eCollection 2021.

Authors

He S Yang^{1

2}, Yu Hou³, Hao Zhang³, Amy Chadburn^{1

2}, Lars F Westblade^{1

2

4}, Richard Fedeli², Peter A D Steel^{2

5}, Sabrina E Racine-Brzostek^{1

2}, Priya Velu^{1

2}, Jorge L Sepulveda⁶, Michael J Satlin⁷, Melissa M Cushing^{1

2}, Rainu Kaushal^{2

3}, Zhen Zhao^{1

2}, Fei Wang³

Affiliations

¹ Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
² New York-Presbyterian Hospital/Weill Cornell Medical Campus, New York, NY, USA.
³ Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
⁴ Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
⁵ Department of Emergency Medicine, Weill Cornell Medicine, New York, NY, USA.
⁶ Department of Pathology, School of Medicine and Health Sciences, George Washington University, Washington DC, USA.
⁷ Division of Infectious Disease, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.

Abstract

Background: New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome.

Methods: We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis.

Results: A COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without the COVID12-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined, and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase.

Conclusions: Our longitudinal analysis illustrates the temporal change of laboratory test result profile in SARS-CoV-2 patients and the COVID-19 evolvement in a US epicenter. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources.