Author: Jit Sarkar; Partha Chakrabarti
Title: A Machine Learning Model Reveals Older Age and Delayed Hospitalization as Predictors of Mortality in Patients with COVID-19 Document date: 2020_3_30
ID: 0agldesf_12
Snippet: Though 48% of the non-survivors had a co-morbid disease, in multivariate analyses, independent associations of in-hospital death were found to be present with older age, high Sequential Organ Failure Assessment (SOFA) score and elevated d-dimer levels (6) . Another study has also identified older patients as a high risk group for mortality (7) . In agreement with previously published studies, our analysis also identified Age to be the most import.....
Document: Though 48% of the non-survivors had a co-morbid disease, in multivariate analyses, independent associations of in-hospital death were found to be present with older age, high Sequential Organ Failure Assessment (SOFA) score and elevated d-dimer levels (6) . Another study has also identified older patients as a high risk group for mortality (7) . In agreement with previously published studies, our analysis also identified Age to be the most important risk factor for mortality among COVID-19 patients. However, the role of delayed hospitalisation following the development of symptoms as another significant risk factor for mortality among COVID-19 patients (after Age) is being reported for the first time. The inadequacy of healthcare resources has already been reported to associate with increased mortality among COVID-19 patients (8) .
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