Predictive value of five early warning scores for critical novel coronavirus disease

Link to article at PubMed

Disaster Med Public Health Prep. 2020 Sep 9:1-22. doi: 10.1017/dmp.2020.324. Online ahead of print.


OBJECTIVE: A simple evaluation tool for patients with novel coronavirus disease (COVID-19) could assist the physicians to triage COVID-19 patients effectively and rapidly. This study aimed to evaluate the predictive value of five early warning scores based on the admission data of critical COVID-19 patients.

METHODS: Overall, medical records of 319 COVID-19 patients were included in the study. Demographic and clinical characteristics on admission were used for calculating the Standardized Early Warning Score (SEWS), national early warning score (NEWS), national early warning score2 (NEWS2), Hamilton early warning score (HEWS), and Modified Early Warning Score (MEWS). Data on the outcomes (survival or death) were collected for each case and extracted for overall and subgroup analysis. Receiver operating characteristic curve analyses were performed.

RESULTS: The area under the receiver operating characteristic curve for the SEWS, NEWS, NEWS2, HEWS and MEWS in predicting mortality were 0.841 (95% CI: 0.765-0.916), 0.809 (95% CI: 0.727-0.891), 0.809 (95% CI: 0.727-0.891), 0.821 (95% CI: 0.748-0.895), and 0.670 (95% CI: 0.573-0.767), respectively.

CONCLUSION: SEWS, NEWS, NEWS2 and HEWS demonstrated moderate discriminatory power and therefore, offer potential utility as prognostic tools for screening severely ill COVID-19 patients. However, MEWS is not a good prognostic predictor for COVID-19.

PMID:32900406 | DOI:10.1017/dmp.2020.324

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