In a new study, researchers analyzed data from the COVID-19 Symptom Tracker app used by 3 million people in the United Kingdom.
They found that the use of immunosuppressant medication, use of a mobility aid, shortness of breath, fever, and fatigue are symptoms that increase the risk for severe COVID-19.
The research was conducted by a team at the Buck Institute.
Even though there are established risk factors for severe COVID-19, there are no good predictors that enable healthcare providers to assess who should seek advanced medical care.
In the study, the team found that out of the three million people who used the app about 11,000 people tested positive for the virus and about 500 ended up in the hospital.
The symptom-tracking app collects data from multiple angles, asking people to describe how they feel, the symptoms they are experiencing, and the medications they are using along with demographics and lifestyle factors such as nutrition and diet.
Results did not identify chronological age as a risk factor for severe COVID-19.
But the findings emphasize that any population that expresses the features identified in the model could be susceptible to a more severe form of COVID-19.
The findings that identify the use of immunosuppressant medications as a major predictor of more serious disease warrant more investigation.
The team says labs around the world are studying the overactive immune response that leads to the cytokine storm which is linked to severe COVID-19.
The findings highlight the need to understand the biology of what is at play in these cases.
The researchers hope to predict patients likely to become COVID “long haulers”—those who experience ongoing debilitating symptoms long after they recover from acute disease.
They say preliminary data suggests that there is a subgroup of COVID-19 patients who are aging faster in regards to their proteome.
Future work may help identify interventions that would restore their protein expression to a younger state.
One author of the study is Associate Professor David Furman, Ph.D. The study is published in the Journal of Medical Internet Research.
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