Abstract
2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Coronavirus - COVID-19 is the subject of a report. According to news originating from Gainesville, Flo rida, by NewsRx correspondents, research stated, "Racial disparities in COVID-19 incidence and outcomes have been widely reported. Non-Hispanic Black patients e ndured worse outcomes disproportionately compared with non-Hispanic White patien ts, but the epidemiological basis for these observations was complex and multifa ceted." Our news journalists obtained a quote from the research from the University of F lorida, "This study aimed to elucidate the potential reasons behind the worse ou tcomes of COVID-19 experienced by non- Hispanic Black patients compared with non- Hispanic White patients and how these variables interact using an explainable ma chine learning approach. In this retrospective cohort study, we examined 28,943 laboratory-confirmed COVID-19 cases from the OneFlorida Research Consortium's da ta trust of health care recipients in Florida through April 28, 2021. We assesse d the prevalence of pre-existing comorbid conditions, geo-socioeconomic factors, and health outcomes in the structured electronic health records of COVID-19 cas es. The primary outcome was a composite of hospitalization, intensive care unit admission, and mortality at index admission. We developed and validated a machin e learning model using Extreme Gradient Boosting to evaluate predictors of worse outcomes of COVID-19 and rank them by importance. Compared to non-Hispanic Whit e patients, non-Hispanic Blacks patients were younger, more likely to be uninsur ed, had a higher prevalence of emergency department and inpatient visits, and we re in regions with higher area deprivation index rankings and pollutant concentr ations. Non-Hispanic Black patients had the highest burden of comorbidities and rates of the primary outcome. Age was a key predictor in all models, ranking hig hest in non-Hispanic White patients. However, for non-Hispanic Black patients, c ongestive heart failure was a primary predictor. Other variables, such as food e nvironment measures and air pollution indicators, also ranked high. By consolida ting comorbidities into the Elixhauser Comorbidity Index, this became the top pr edictor, providing a comprehensive risk measure. The study reveals that individu al and geo-socioeconomic factors significantly influence the outcomes of COVID-1 9. It also highlights varying risk profiles among different racial groups. While these findings suggest potential disparities, further causal inference and stat istical testing are needed to fully substantiate these observations."
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