New Mobile App Uses AI and Biomarkers to Determine COVID-19 Disease Severity

Researchers at the NYU College of Dentistry (New York, NY, USA) have created the app which uses artificial intelligence (AI) to assess risk factors and key biomarkers from blood tests, producing a COVID-19 “severity score.”

Using data from 160 hospitalized COVID-19 patients in Wuhan, China, the researchers identified four biomarkers measured in blood tests that were significantly elevated in patients who died versus those who recovered: C-reactive protein (CRP), myoglobin (MYO), procalcitonin (PCT), and cardiac troponin I (cTnI). These biomarkers can signal complications that are relevant to COVID-19, including acute inflammation, lower respiratory tract infection, and poor cardiovascular health.

The researchers then built a model using the biomarkers as well as age and sex, two established risk factors. They trained the model using a machine learning algorithm, a type of AI, to define the patterns of COVID-19 disease and predict its severity. When a patient’s biomarkers and risk factors are entered into the model, it produces a numerical COVID-19 severity score ranging from 0 (mild or moderate) to 100 (critical).

The model was validated using data from 12 hospitalized COVID-19 patients from Shenzhen, China, which confirmed that the model’s severity scores were significantly higher for the patients that died versus those who were discharged. As New York City emerged as the epicenter of the pandemic, the researchers further validated the model using data from more than 1,000 New York City COVID-19 patients.

To make the tool available and convenient for clinicians, they developed a mobile app that can be used at point-of-care to quickly calculate a patient’s severity score. The researchers now aim to roll out the app across the US in the coming weeks. It is possible that the COVID-19 severity score could be integrated with electronic health records, thereby providing clinicians with actionable information at an early stage for those diagnosed with COVID-19.

“Identifying and monitoring those at risk for severe cases could help hospitals prioritize care and allocate resources like ICU beds and ventilators. Likewise, knowing who is at low risk for complications could help reduce hospital admissions while these patients are safely managed at home,” said John T. McDevitt, PhD, professor of biomaterials at NYU College of Dentistry and professor of chemical and molecular engineering at NYU Tandon School of Engineering, who led the research. “We want doctors to have both the information they need and the infrastructure required to save lives. COVID-19 has challenged both of these key areas.”

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NYU College of Dentistry