Predicting severe COVID-19 in the Emergency Department

Area of Science:

• Critical Care Medicine
• Infectious Diseases
• Emergency Medicine

Background:

• COVID-19 poses a significant threat, potentially leading to severe illness and overwhelming healthcare systems.
• Accurate prediction of severe COVID-19 cases is crucial for effective resource allocation and patient management.
• Existing sepsis and pneumonia scoring systems' utility in predicting severe COVID-19 requires evaluation.

Purpose of the Study:

• To compare the predictive accuracy of commonly used clinical scoring systems for severe COVID-19.
• To assess the performance of qSOFA, SIRS, NEWS2, CURB-65, and PSI in identifying patients at high risk for severe COVID-19.
• To determine the most effective screening tool for severe COVID-19 in the emergency department setting.

Main Methods:

• A prospective, observational study was conducted in a single center in Oslo, Norway.
• Patients were evaluated upon admission using qSOFA, SIRS, NEWS2, CURB-65, PSI, and P/F-ratio.
• Area Under the Receiver Operating Characteristics Curve (AUROC), sensitivity, and specificity were calculated to assess predictive performance. Severe disease was defined as death or ICU admission within 14 days.

Main Results:

• Out of 175 participants, 38 developed severe COVID-19, including 13 deaths and 29 ICU admissions.
• NEWS2 showed the highest AUROC (0.80), outperforming SIRS and qSOFA (both 0.70).
• NEWS2 with a cutoff of 5 points achieved 82% sensitivity and 60% specificity for predicting severe disease.

Conclusions:

• NEWS2 demonstrated superior predictive accuracy for severe COVID-19 compared to SIRS and qSOFA.
• NEWS2's performance was comparable to CURB-65 and PSI in predicting severe COVID-19.
• NEWS2 is a valuable screening tool for assessing COVID-19 patients upon hospital admission.