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?:abstract
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Identifying factors associated with severe COVID-19 is a priority to guide clinical care and resource use in this pandemic. This cohort comprised 13954 in-patients with confirmed COVID-19. Study outcomes were death and intensive care unit admission (ICUA). Multivariable logistic regression estimated odd ratios adjusted for 37 covariates (comorbidities, demographic, and others). Gradient boosted decision tree (GBDT) classification generated Shapley values evaluating the impact of covariates for each patient. Deaths due to COVID-19 were associated with immunosuppression due to disease (Odds Ratio 1.39, 95%CI [1.10-1.76]), type-2 diabetes (1.31, [1.17-1.46]), chronic respiratory disease (1.19, [1.05-1.35]), obesity (1.16, [1.01-1.33], age (1.56/10-year increment, [1.52-1.61]), and male sex (1.54, [1.42-1.68]). Associations with ICUA differed in direction (e.g., age, chronic respiratory disease) and in scale, e.g., obesity (3.37, [2.90-3.92]) for some factors. Ethnicity was strongly but variably associated with both outcomes, for example Irish ethnicity is negatively with death but not ICUA. GBDTs had similar performance (ROC-AUC, ICUA 0.83, death 0.68 for GBDT; 0.80 and 0.68 for logistic regression). Shapley explanations overall were consistent with odds ratios. Chronic heart disease, hypertension, other comorbidities, and some ethnicities had Shapley impacts on death ranging from positive to negative among different patients, although consistently associated with ICUA for all. Immunosuppressive disease, type-2 diabetes, and chronic liver and respiratory diseases had positive impacts on death with either positive or negative on ICUA. Very different association of some factors, e.g., obesity, with death and ICUA may guide review of practice. Shapley explanation identified varying effects among patients emphasising the importance of individual patient assessment.
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