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Abstract Objects

Prevalence of Risk Factors In Patients Tested for Covid-19 

Using data from UC CORDS Database

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Hello!

Our website is built around the UC CORDS Database from five UC medical schools. 

Our team used data from the UC CORDS Database in order to determine if the prevalence of risk factors is different between COVID-positive and COVID-negative patients. We will also use this data in order to compare the difference between sex/ethnicity and the significance of these data results.

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Click below to learn more about our project!

UC CORDS

UC Health COVID Research Data Set

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        Davis                       San Francisco                  San Diego                   Los Angeles                         Irvine

Our team was given access to UC CORDS, a weekly updated COVID-19 clinical dataset collected across five UC Medical campuses. We were able to conduct our research project by using data analytics from CORDS.

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Problem: There is a limited amount of studies that focus in-depth on how common key risk factors such as diabetes, hypertension, and obesity correlate to COVID-19 positivity and whether there are disparities between sex/gender and ethnicity.

We find this to be important because medical insight should be holistic and take into account people of various health conditions, severities, and backgrounds.

 

  1. There are millions of COVID-19 test results and EMR data that is not used for critical analysis in determining common key risk factors for COVID; very little research is done on finding common key risk factors pertaining to the patients’ backgrounds

  2. Most research show common key risk factors strictly in the context of severe COVID/mortality risks of people with pre-existing conditions and exclude mild cases of COVID

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Question:

In Patients who were tested for COVID19, is there a significant difference between levels of Hypertension, Obesity, and Diabetes? How does this change if stratified by Gender and Race?

Summary

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Criteria Used

Patients analyzed needed to:

  • Have a Unique id number

  • Be tested for COVID

  • Return a Positive or Test

Variables used

IDs, Gender, Ethnicity, COVID Positivity Status, and presence of ICD10CM Risk factors(Hypertension,Obesity, Diabetes)

Analysis Plan

-Pull relevant data for analysis from CORDS using Microsoft SQL

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-Cross tabulate Covid Positivity Status with the variables using statisical Analysis Systems (SAS)

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