Assessing the effect of blood type on death and a novel scoring system to assess clinical course in patients with COVID-19

Coronavirus disease (COVID-19) continues to lead to worldwide morbidity and mortality. This study examined the association between blood type and clinical outcomes in patients with COVID-19 measured by a calculated morbidity score and mortality rates. The secondary aim was to investigate the relationship between patient characteristics and COVID-19 associated clinical outcomes and mortality. Logistic regression was used to determine what factors were associated with death. A total morbidity score was constructed based on overall patient's COVID-19 clinical course. This score was modeled using Quasi-Poisson regression. Bayesian variable selection was used for the logistic regression to obtain a posterior probability that blood type is important in predicting worsened clinical outcomes and death. Neither blood type nor Rh+ status was a significant moderator of death or morbidity score in regression analyses. Increased age (adjusted Odds Ratio=3.37, 95% CI=2.44–4.67), male gender (aOR=1.35, 95% CI=1.08-1.69), and number of comorbid conditions (aOR=1.28, 95% CI=1.01-1.63) were significantly associated with death. Significant factors in predicting total morbidity score were age (adjusted Multiplicative Effect=1.45; 95% CI=1.349-1.555) and gender (aME=1.17; 95% CI=1.109-1.243). The posterior probability that blood type influenced death was only 10%. There is strong evidence that blood type was not a significant predictor of clinical course or death in patients hospitalized with COVID-19. Older age and male gender led to worse clinical outcomes and higher rates of death; older age, male gender, and comorbidities predicted a worse clinical course and higher morbidity score. Race was not a significant predictor of death in our population and was associated with an increased, albeit not significant, morbidity score.