A risk score to predict admission to the intensive care unit in patients with Covid-19: the ABC-GOALS score

Objective. To develop a score to predict the need for intensive care unit (ICU) admission in Covid-19. Materials and methods. We assessed patients admitted to a Covid-19 center in Mexico. Patients were segregated into a group that required ICU admission, and a group that never required ICU admission. By logistic regression, we derived predictive models including clinical, laboratory, and imaging findings.The ABC-GOALS was constructed and compared to other scores. Results. We included 329 and 240 patients in the development and validation cohorts, respectively. Onehundred-fifteen patients from each cohort required ICU admission. The clinical (ABC-GOALS c), clinical+laboratory (ABC-GOALS cl), clinical+laboratory+image (ABC-GOALSclx) models area under the curve were 0.79 (95%CI=0.74-0.83) and 0.77 (95% CI=0.71-0.83), 0.86 (95%CI=0.82-0.90) and 0.87 (95%CI=0.83-0.92), 0.88 (95%CI=0.84-0.92) and 0.86 (95%CI=0.81-0.90), in the development and validation cohorts, respectively. The ABC-GOALS cl and ABC-GOALS clx outperformed other Covid-19 and pneumonia predictive scores. Conclusion. ABC-GOALS is a tool to timely predict the need for admission to ICU in Covid-19.