Machine learning analysis highlights the down-trending of the proportion of COVID-19 patients with a distinct laboratory result profile

Abstract

AbstractBackgroundNew 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.MethodsWe 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.ResultsA 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 COVID19-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.ConclusionsOur study visualized the down-trending of the proportion of SARS-CoV-2 patients with the distinct COVID19-HRP. 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.