Chennai: Researchers have identified three different types of Covid-19 disease traits in patients, based on their comorbidities, complications, and clinical outcomes.
This development is likely to help target future interventions to the most risk-prone individuals.
Published in the journal PLOS ONE, the new study analysed the electronic health records (EHRs) from 14 hospitals in the midwestern US and from 60 primary care clinics in the state of Minnesota.
Scientists, including those from the University of Minnesota in the US, said the study included 7,538 patients with confirmed Covid-19 between 7 March and 25 August, 2020, of which 1,022 patients required hospitalisation.
Nearly 60 per cent of the patients included in the research presented with what the researchers called ‘phenotype II.’
Researchers said about 23 per cent of the patients presented with ‘phenotype I,’ or the ‘adverse phenotype,’ which was associated with the worst clinical outcomes.
They said these patients had the highest level of comorbidies related to heart and kidney dysfunction.
As per the study, 173 patients, or 16.9 per cent presented with ‘phenotype III,’ or the ‘favorable phenotype,’ which the scientists said was associated with the best clinical outcomes.
While this group had the lowest complication rate and mortality, the scientists said these patients had the highest rate of respiratory comorbidities as well as a 10 per cent greater risk of hospital readmission compared to the other phenotypes.
Overall, they said phenotypes I and II were associated with 7.30-fold and 2.57-fold increases in hazard of death relative to phenotype III.
Based on the results, the scientists said such phenotype-specific medical care could improve Covid-19 outcomes.
However, they believe further studies are needed to determine the utility of these findings in clinical practice.
“Patients do not suffer from Covid-19 in a uniform matter. By identifying similarly affected groups, we not only improve our understanding of the disease process, but this enables us to precisely target future interventions to the highest risk patients,” the scientists stated.