A high-throughput informatics technique developed at Vanderbilt University Medical Center that reveals associations between genetic variations and medical conditions in the electronic health record (EHR) also can identify new “post-COVID” diagnoses, according to a report in the Journal of the American Medical Informatics Association.
Eric Kerchberger, MD, Josh Peterson, MD, MPH, and Wei-Qi Wei, MD, PhD, used a phenome-wide association study (PheWAS) technique to assess new diagnoses occurring among survivors of acute COVID-19 at VUMC.
Pulling EHR data from 186,105 adults tested for SARS-CoV-2 at VUMC between March 2020 and November 2021, the authors found COVID-19 survivors had an increased risk for more than 40 new diagnoses, including multiple respiratory, cardiovascular, neurological, and pregnancy complications.
Given the scale of the COVID-19 pandemic, these findings could have profound long-term implications for public health, the researchers concluded.
This study also demonstrates how high-throughput informatics approaches like PheWAS could help researchers study the consequences of other acute medical conditions and help policymakers plan for future pandemics.
The research was supported by the National Institutes of Health grants LM007450, HL157755, HG011166, and GM139891, the American Thoracic Society, and the Francis Family Foundation.
