Apples to Apples: Effective Clinical Comparisons of Medications Used in Treating CoVid-19 Apples to Apples: Effective Clinical Comparisons of Medications Used in Treating CoVid-19
Location
Culp Ballroom
Start Date
4-7-2022 9:00 AM
End Date
4-7-2022 12:00 PM
Poster Number
20
Faculty Sponsor’s Department
Family Medicine
Name of Project's Faculty Sponsor
Laura Helmly
Additional Sponsors
Amanda Stoltz, Thomas Townsend, Jason Moore, Greg Clarity, John Culp, Kelsey Lloyd, Elizabeth White, Andrea Hopkins, Chris Garner
Competition Type
Competitive
Type
Poster Presentation
Project's Category
Public Health
Abstract or Artist's Statement
During the second year of the pandemic, several medicines have been invented or repurposed to treat patients with symptoms resulting from CoVid-19. As this body of research has become voluminous and burdensome, health care professionals need a statistically useful method for directly comparing medications as a means of improving medical decision making and managing expectations for patients and families regarding treatment outcomes. This project examined clinical trials underlying medications recommended by the National Institute of Health for treating CoVid-19, compared the outcomes by which each medication was measured, and calculated the number needed to treat (NNT) for each medication to compare each treatment’s efficacy. Our analysis found that most studies used hospitalization for inpatient care as the endpoint against which treatments were measured, which makes NNT a potentially meaningful metric in comparing these medications and thus improving clinical decision making.
Apples to Apples: Effective Clinical Comparisons of Medications Used in Treating CoVid-19 Apples to Apples: Effective Clinical Comparisons of Medications Used in Treating CoVid-19
Culp Ballroom
During the second year of the pandemic, several medicines have been invented or repurposed to treat patients with symptoms resulting from CoVid-19. As this body of research has become voluminous and burdensome, health care professionals need a statistically useful method for directly comparing medications as a means of improving medical decision making and managing expectations for patients and families regarding treatment outcomes. This project examined clinical trials underlying medications recommended by the National Institute of Health for treating CoVid-19, compared the outcomes by which each medication was measured, and calculated the number needed to treat (NNT) for each medication to compare each treatment’s efficacy. Our analysis found that most studies used hospitalization for inpatient care as the endpoint against which treatments were measured, which makes NNT a potentially meaningful metric in comparing these medications and thus improving clinical decision making.