January 2023 in “Archives of Internal Medicine Research” This study found that both primary Covid-19 infections and exacerbations of existing health conditions influence mortality, with long-term effects being predictable from GLM models.
August 2020 in “Research Square (Research Square)” This study found that an age-adjusted Charlson comorbidity index of four or more strongly predicts mortality in South Korean COVID-19 patients, highlighting the impact of comorbidity burden and older age on disease severity.
November 2023 in “Advances and Applications in Statistics” In this retrospective study, researchers developed machine learning models to predict mortality risk among 7115 COVID-19 patients in Iran, finding that the random forests model performed best with 96% accuracy and identified factors like intubation and SpO2 as significant predictors.
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March 2021 in “Scientific Reports” This study found that, among COVID-19 patients in South Korea, hypertension, diabetes, and other comorbidities significantly increased mortality risk, with the age-adjusted Charlson comorbidity index being a strong predictor of death.
This article provides tables summarizing various medical conditions and symptoms related to COVID-19, sepsis, and cardiovascular issues, but it does not report new research findings.
