Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning.

TitleRoutine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning.
Publication TypeJournal Article
Year of Publication2020
AuthorsYang HS, Hou Y, Vasovic LV, Steel PAD, Chadburn A, Racine-Brzostek SE, Velu P, Cushing MM, Loda M, Kaushal R, Zhao Z, Wang F
JournalClin Chem
Date Published2020 11 01
KeywordsAdult, Aged, Clinical Laboratory Techniques, Coronavirus Infections, COVID-19, COVID-19 Testing, Female, Hematologic Tests, Humans, Laboratories, Machine Learning, Male, Middle Aged, Models, Theoretical, Pandemics, Pneumonia, Viral, Retrospective Studies, Reverse Transcriptase Polymerase Chain Reaction, ROC Curve, Young Adult

BACKGROUND: Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PCR from nasopharyngeal swabs specimens, however the results are not promptly obtainable in all patient care locations. Routine laboratory testing, in contrast, is readily available with a turn-around time (TAT) usually within 1-2 hours.

METHOD: We developed a machine learning model incorporating patient demographic features (age, sex, race) with 27 routine laboratory tests to predict an individual's SARS-CoV-2 infection status. Laboratory testing results obtained within 2 days before the release of SARS-CoV-2 RT-PCR result were used to train a gradient boosting decision tree (GBDT) model from 3,356 SARS-CoV-2 RT-PCR tested patients (1,402 positive and 1,954 negative) evaluated at a metropolitan hospital.

RESULTS: The model achieved an area under the receiver operating characteristic curve (AUC) of 0.854 (95% CI: 0.829-0.878). Application of this model to an independent patient dataset from a separate hospital resulted in a comparable AUC (0.838), validating the generalization of its use. Moreover, our model predicted initial SARS-CoV-2 RT-PCR positivity in 66% individuals whose RT-PCR result changed from negative to positive within 2 days.

CONCLUSION: This model employing routine laboratory test results offers opportunities for early and rapid identification of high-risk SARS-CoV-2 infected patients before their RT-PCR results are available. It may play an important role in assisting the identification of SARS-CoV-2 infected patients in areas where RT-PCR testing is not accessible due to financial or supply constraints.

Alternate JournalClin Chem
PubMed ID32821907
PubMed Central IDPMC7499540
Related Faculty: 
Amy Chadburn, M.D. He Sarina Yang, M.D., Ph.D. Massimo Loda, M.D. Melissa Cushing, M.D. Priya Velu, M.D., Ph.D. Sabrina Racine-Brzostek, M.D., Ph.D. Zhen Zhao, Ph.D.


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