Health
According to scientists, Covid-19 patients can be divided into three groups
Scientists have identified three different types of COVID-19 disease characteristics in patients, depending on their comorbidities, complications, and clinical outcomes. This is an advance that may help target future interventions to the highest risk individuals. A new study published in the journal PLOS ONE analyzed electronic health records (EHRs) from 14 hospitals in the Midwestern United States and 60 primary care clinics in Minnesota.
According to researchers, including researchers at the University of Minnesota in the United States, the study included 7,538 patients with confirmed COVID-19 between March 7, 2020 and August 25, 2020, of which 1,022 patients required hospitalization. Nearly 60% of the patients included in the study presented what the researchers called “phenotype II.” They said that about 23 percent of patients exhibited “phenotype I” or “harmful phenotype,” which was associated with the worst clinical outcome.
The researchers said these patients had the highest levels of comorbidities associated with heart and kidney dysfunction. According to this study, 173 patients (16.9%) showed “phenotype III” or “favorable phenotype,” and scientists said this was associated with the best clinical outcome. Although complications and mortality in this group were lowest, scientists found that these patients had the highest incidence of respiratory complications and had a 10% risk of readmission compared to other phenotypes. Said it was expensive. Overall, they said that phenotypes I and II were associated with a 7.30-fold and 2.57-fold increased risk of death compared to phenotype III.
Based on the results, scientists said that such phenotype-specific medicine could improve the results of COVID-19. However, they believe that further research is needed to determine the usefulness of these findings in clinical practice. Patients do not suffer from COVID-19 with uniform problems. Affected groups not only gain a better understanding of the disease process, but this also allows them to accurately direct future interventions to the patients at highest risk, “scientists added.
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