There are many factor that affect the severity of COVID-19 infections and many different ways to assess such severyity and outcomes of the infection. This project performs a characterization and outcomes analysis of COVID-19 infected individuals in CPRD (Clinical Practice Research Data Link) AURUM data. This study will include analysis of participants with diagnosed COVID-19 infection and the outcome of the infection as it relates to death, the presence and progression of certain coexisting conditions, medications, procedures as well as other clinical and social factors. Along with the stated analysis the main emphasis of the project lies in the comparability of multiple datasets as we will perform the same analysis with other datasets and compare the results and capabilities of each. To do this we will take other data such as US Medicare data, The All of Us program in the US and UK Biobank and perform the same analyses on each This will allow us to compare individuals with COVID-19 from each to see how different populations are affected by COVID-19 and how different treatments and procedures are used and what factors lead to certain outcomes. This analysis will also allow for an understanding of how populations in different countries and with different medical histories, were affected by COVID-19 and show what factors lead to potential negative outcomes such as death or severe disease.
Our primary goal is to characterize and analyze a set of COVID-19 affected individuals and related outcomes. The main motivation is to define different cohorts, analyzing the relation of multiple domains (such as condition, procedure, drug) to determine factors that affect disease progression and other outcomes and compare equivalent analyses across multiple datasets with differing population characteristics. The study population will include any individual with a COVID-19 diagnosis or positive COVID-19 viral lab test. We will review gender, age groups and clinical history, as it pertains to present and new comorbidities, medication usage and history and procedures. Analyzing these factors we will characterize their affect on outcomes such as mortality (all ause and COVID-19 related) disease progression, changes in medication usage and procedures conducted. This will be done through the combination of descriptive statistics and trend analysis as well variable linkage based on factors relating to outcomes. This analysis will use CPRD AURUM diagnosis, lab, drug and procedure data long with demographics to assess the impact of various factors in clinical backgrounds on COVID-19 outcomes as well as the development of clinical issues as caused by COVID-19. This will aid in the public health assessment of the impact of COVID-19 on overall health and the factors that contribute to certain outcomes.
COVID-19 related mortality, All-cause mortality, Comorbidity related mortality, newly developed comorbidity, COVID-19 procedure occurrence, mortality relating to previously occurring procedure for cohort of COVID-19 participants and controls, mortality relating to previously occurring treatments for cohort of COVID-19 participants and controls, changes in medication usage and dosage relating to covid-19 occurrence. Review of outcome measures as it relates to patient age, gender, time relation to COVID-19 infection as well as other cohort defining factors.
Craig Mayer - Chief Investigator - National Institutes of Health - USA
Craig Mayer - Corresponding Applicant - National Institutes of Health - USA
James Mork - Collaborator - National Institutes of Health - USA
Nick Williams - Collaborator - National Institutes of Health - USA