SUPER Score Contributes to Warning and Management in Early-Stage COVID-19

Abstract

Background

Some COVID-19 patients deteriorate to severe cases with relatively higher case-fatality rates, which increases the medical burden. This necessitates identification of patients at risk of severe disease. Early assessment plays a crucial role in identifying patients at risk of severe disease. This study is to assess the effectiveness of SUPER score as a predictor of severe COVID-19 cases.

Methods

We consecutively enrolled COVID-19 patients admitted to a comprehensive medical center in Wuhan, China, and recorded clinical characteristics and laboratory indexes. The SUPER score was calculated using parameters including oxygen saturation, urine volume, pulse, emotional state, and respiratory rate. In addition, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity of the SUPER score for the diagnosis of severe COVID-19 were calculated and compared with the National Early Warning Score 2 (NEWS2).

Results

The SUPER score at admission, with a threshold of 4, exhibited good predictive performance for early identification of severe COVID-19 cases, yielding an AUC of 0.985 (95% confidence interval [CI] 0.897–1.000), sensitivity of 1.00 (95% CI 0.715–1.000), and specificity of 0.92 (95% CI 0.775–0.982), similar to NEWS2 (AUC 0.984; 95% CI 0.895–1.000, sensitivity 0.91; 95% CI 0.587–0.998, specificity 0.97; 95% CI 0.858–0.999). Compared with patients with a SUPER score<4, patients in the high-risk group exhibited lower lymphocyte counts, interleukin-2, interleukin-4 and higher fibrinogen, C-reactive protein, aspartate aminotransferase, and lactate dehydrogenase levels.

Conclusions

In conclusion, the SUPER score demonstrated equivalent accuracy to the NEWS2 score in predicting severe COVID-19. Its application in prognostic assessment therefore offers an effective early warning system for critical management and facilitating efficient allocation of health resources.