Abstract

Early detection of viral infections, such as COVID-19 and flu, have the potential to reduce risk of morbidity, mortality, and disease transmission through earlier intervention strategies. Distinguishing patterns among vital signs, including body temperature, pulse rate, respiration rate, and blood pressure, can help to diagnose a potential respiratory virus more rapidly and accurately. The objective of this study was to utilize the University of Mississippi Medical’s extensive clinical database (EPIC) to investigate the potential association between temperature, pulse rate, blood pressure, and respiration with influenza and COVID-19. COVID-19 (March 3, 2020 to February 27, 2021) and flu (October 1, 2017 to September 30, 2018) diagnosed patients were identified from over 1 million patients (of a total population of 3 million) and 36 million encounters of Mississippi residents from the electronic health record. Data from patients with reported demographic dimensions (age, first race, and sex) and office visit dimensions (BMI, diastolic blood pressure (BP), pulse rate, respiration rate, systolic BP, and temperature) was obtained for 1,363 COVID-19 and 507 flu diagnosed patients, including day of diagnosis and additional encounter visits within 60 days before and after first unique viral disease diagnosis. Patients with COVID-19 or flu were disproportionately obese, with 93% of COVID-19 and 79% of flu patients with BMI ≥30. Most striking was that black women in 50-64 years disproportionately carried the burden of disease. For all patients at the time of infection, temperature was significantly increased for both respiratory viruses, pulse rate was significantly increased for flu, and BP was not significantly increased in either infection. We compared flu patients with no pre-existing diagnoses (n= 57) to those with essential (primary) hypertension (n= 234) and found significantly higher systolic BP at day of infection in flu only patients. Our findings show the need for more complete demographic and office visit dimension data from patients during epidemic and pandemic events.

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