New paper Art Biological methods and protocolspublished by Oxford University Press, shows that certain pre-existing conditions, including degenerative neurological diseases, dementia and severe disabilities, matter more than once thought when assessing who is at risk of dying from COVID-19 .
COVID-19 has changed life dramatically. In the United States, the disease can be 163 times more fatal than the seasonal flu. COVID-19 may also make patients more likely to need a ventilator or end up in intensive care.
Pre-existing conditions, or concomitant diseases, increase the likelihood of severe illness or death from COVID-19. But assessing the risk of different conditions for the severity of COVID has been difficult. Researchers have proposed several mathematical models to predict deaths from COVID-19 based on comorbidities. Healthcare facilities use these models as they aid in patient management and resource allocation.
Many diseases increase mortality because they weaken the immune system, increase the likelihood of developing infections, and cause end-organ dysfunction. One method of assessing the risk of different conditions is to group them into broad categories (such as “malignancy”) and predict outcomes for each category. Another method is to weigh the different pre-existing conditions differently and use the sum to predict the results. Researchers believe that these approaches have significant drawbacks; the real impact of a certain pre-existing condition is often not well known, similar conditions are often lumped together in prediction models, even though the outcomes of COVID-19 can be very different, and rare diseases are underrepresented.
The researchers believe the best approach is to systematically screen for all pre-existing conditions, identify which affect outcomes, and then use that to create a predicted probability of death, which is the cumulative risk associated with co-morbidities. .
Using all the diagnostic codes used by the Department of Veterans Affairs, researchers developed a new prediction model to estimate the likelihood of death from COVID-19. This is the largest study to date of patients with COVID-19 to predict mortality. Starting in 1997, researchers here used diagnoses from the time a patient first sought care up to 14 days before a positive COVID-19 test, and then compared that with the COVID results for 347,220 COVID patients treated at Veterans Affairs facilities by state for September 2021. They found that their new model, which they call PDeathDx, outperformed other conventional prediction models.
What’s more, the researchers found that some underlying diseases are much more likely to lead to death. These include degenerative neurological diseases, dementia and severe disability. Because doctors do not associate these pre-existing conditions with respiratory impairment or a weakened immune system, traditional risk assessment fails to account for the serious risk of COVID for patients with these conditions.
Heather M. Campbell et al. A new method for dealing with pre-existing conditions in the development of a multivariate prediction model for death from COVID-19, Biological methods and protocols (2022). DOI: 10.1093/biomethods/bpac017
Oxford University Press
Citation: Study Shows Different Comorbidities Impact COVID Outcomes Differently (2022, September 27) Retrieved September 27, 2022, from https://medicalxpress.com/news/2022-09-comorbidities-impacts-covid- outcomes.html
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