PEGALUS: predictivity of elderly age, arterial gas analysis, and lung ultrasound. A new prognostic score for COVID-19 patients in the emergency department—an observational prospective study

Background Periodic surges of COVID-19 patients seeking care in the hospital environment overwhelm systems reduce the availability of resources for treatment of non-COVID-19 cases (Zheng et al. in J Hosp Infect 106:325–329, 2020). Hospital flow and resource management could be greatly enhanced by differentiating patients who are likely at risk of adverse clinical outcomes from those who could safely be discharged after evaluation and managed outside of the hospital setting (Sun et al. in J Infect Dis 223:38–46, 2021). Herein, we propose a prognostic score named PEGALUS (Predictivity of Elderly age, arterial blood Gas Analysis and Lung UltraSound) that could potentially help clinicians properly and rapidly choose the appropriate allocation of COVID-19 patients admitted to the emergency department (ED). Methods This observational prospective study enrolled COVID-19 patients who were admitted to the ED of IRCCS San Raffaele Hospital (HSR). Results 230 COVID-19 patients were enrolled and 30-day follow-up data was collected. Composite outcome was death or need for oro-tracheal intubation (OTI). 50 patients (21.5%) reached the outcome during the observational period. In multivariate Cox analysis, age, PO 2 /FiO 2 ratio, p CO 2 , duration of symptoms, and lung ultrasound evaluation were significantly associated with the adverse outcome. We obtained a new scorecard (PEGALUS) according to the hazard ratio of the identified predictors. PEGALUS score performed well in predicting the composite outcome (AUC 0.866, 95% IC 0.812–0.921; p < 0.001). Kaplan–Meier showed that a PEGALUS score < 7 was associated with a good 30-day prognosis (survival rate 97.5%), compared to a PEGALUS score of 7–11 (survival rate 85.9%; p log-rank 0.009) and PEGALUS score > 11 (survival rate 49.3%; p log-rank < 0.001). Conclusions PEGALUS score performed at the admission can predict adverse outcomes in patients with COVID-19. The systematic application of this score might permit a more accurate and rapid treatment allocation in this setting.