Machine Learning Highlights Downtrending of COVID-19 Patients with a Distinct Laboratory Profile
| Autor: | Amy Chadburn, Jorge L Sepulveda, Yu Hou, Peter A D Steel, Priya Velu, Richard Fedeli, Fei Wang, Hao Zhang, Sabrina E Racine-Brzostek, Rainu Kaushal, Melissa M. Cushing, He S. Yang, Michael J. Satlin, Zhen Zhao, Lars F. Westblade |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Coronavirus disease 2019 (COVID-19) Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viruses Population Computer applications to medicine. Medical informatics R858-859.7 Machine learning computer.software_genre 03 medical and health sciences 0302 clinical medicine Medicine 030212 general & internal medicine education skin and connective tissue diseases education.field_of_study business.industry fungi Retrospective cohort study Emergency department Test (assessment) body regions 030104 developmental biology Laboratory Test Result Artificial intelligence business Viral load computer |
| Zdroj: | Health Data Science, Vol 2021 (2021) |
| ISSN: | 2765-8783 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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