Objectives: To evaluate the accuracy of a new COVID-19 prognostic score based on lung ultrasound (LUS) and previously validated variables in predicting critical illness. Methods: We conducted a single-center retrospective cohort development and internal validation study of the COVID-19 Worsening Score (COWS), based on a combination of the previously validated COVID-GRAM score (GRAM) variables and LUS. Adult COVID-19 patients admitted to the emergency department (ED) were enrolled. Ten variables previously identified by GRAM, days from symptom onset, LUS findings, and peripheral oxygen saturation/fraction of inspired oxygen (P/F) ratio were analyzed. LUS score as a single predictor was assessed. We evaluated GRAM model's performance, the impact of adding LUS, and then developed a new model based on the most predictive variables. Results: Among 274 COVID-19 patients enrolled, 174 developed critical illness. The GRAM score identified 51 patients at high risk of developing critical illness and 132 at low risk. LUS score over 15 (range 0 to 36) was associated with a higher risk ratio of critical illness (RR, 2.05; 95% confidence interval [CI], 1.52-2.77; area under the curve [AUC], 0.63; 95% CI 0.676-0.634). The newly developed COVID-19 Worsening Score relies on five variables to classify high- and low-risk patients with an overall accuracy of 80% and negative predictive value of 93% (95% CI, 87%-98%). Patients scoring more than 0.183 on COWS showed a RR of developing critical illness of 8.07 (95% CI, 4.97-11.1). Conclusions: COWS accurately identify patients who are unlikely to need intensive care unit (ICU) admission, preserving resources for the remaining high-risk patients.

The COVID‐19 Worsening Score (COWS)—a predictive bedside tool for critical illness

Boero, Enrico
First
;
Berchialla, Paola;Charrier, Lorena;Cravino, Marta Maria;Gollini, Paola;Puppo, Mattia;Fornelli, Giorgia;Labarile, Giulia;Aprà, Franco;
2021-01-01

Abstract

Objectives: To evaluate the accuracy of a new COVID-19 prognostic score based on lung ultrasound (LUS) and previously validated variables in predicting critical illness. Methods: We conducted a single-center retrospective cohort development and internal validation study of the COVID-19 Worsening Score (COWS), based on a combination of the previously validated COVID-GRAM score (GRAM) variables and LUS. Adult COVID-19 patients admitted to the emergency department (ED) were enrolled. Ten variables previously identified by GRAM, days from symptom onset, LUS findings, and peripheral oxygen saturation/fraction of inspired oxygen (P/F) ratio were analyzed. LUS score as a single predictor was assessed. We evaluated GRAM model's performance, the impact of adding LUS, and then developed a new model based on the most predictive variables. Results: Among 274 COVID-19 patients enrolled, 174 developed critical illness. The GRAM score identified 51 patients at high risk of developing critical illness and 132 at low risk. LUS score over 15 (range 0 to 36) was associated with a higher risk ratio of critical illness (RR, 2.05; 95% confidence interval [CI], 1.52-2.77; area under the curve [AUC], 0.63; 95% CI 0.676-0.634). The newly developed COVID-19 Worsening Score relies on five variables to classify high- and low-risk patients with an overall accuracy of 80% and negative predictive value of 93% (95% CI, 87%-98%). Patients scoring more than 0.183 on COWS showed a RR of developing critical illness of 8.07 (95% CI, 4.97-11.1). Conclusions: COWS accurately identify patients who are unlikely to need intensive care unit (ICU) admission, preserving resources for the remaining high-risk patients.
2021
1
10
COVID-19, critical care, intensive care, lung sonography, lung ultrasound, prognostic score
Boero, Enrico; Rovida, Serena; Schreiber, Annia; Berchialla, Paola; Charrier, Lorena; Cravino, Marta Maria; Converso, Marcella; Gollini, Paola; Puppo, Mattia; Gravina, Angela; Fornelli, Giorgia; Labarile, Giulia; Sciacca, Santi; Bove, Tiziana; Karakitsos, Dimitrios; Aprà, Franco; Blaivas, Michael; Vetrugno, Luigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1769068
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