Performance of Crisis Standards of Care Guidelines in a Cohort of Critically Ill COVID-19 Patients in the United States.

Many US states published crisis standards of care (CSC) guidelines for allocating scarce critical care resources during the COVID-19 pandemic. However, the performance of these guidelines in maximizing population benefit has not been well tested. In 2,272 adults with COVID-19 requiring ICU admission drawn from the STOP-COVID multicenter cohort, we tested three approaches to CSC algorithms: SOFA scores grouped into ranges, SOFA score ranges plus comorbidities, and a hypothetical approach using raw SOFA scores not grouped into ranges. We found that area under receiver operating characteristic (AUROC) curves for all three algorithms demonstrate only modest discrimination for 28-day mortality. Adding comorbidity scoring modestly improves algorithm performance over SOFA scores alone. The algorithm incorporating comorbidities has modestly worse predictive performance for Black compared to White patients. CSC algorithms should be empirically examined to refine approaches to the allocation of scarce resources during pandemics and to avoid potential exacerbation of racial inequities.