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The predictive value of the National Early Warning Score for mortality and independent prognostic factors in patients with coronavirus disease 2019: A retrospective cohort study
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The predictive value of the National Early Warning Score for mortality and independent prognostic factors in patients with coronavirus disease 2019: A retrospective cohort study
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The predictive value of the National Early Warning Score for mortality and independent prognostic factors in patients with coronavirus disease 2019: A retrospective cohort study
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Journal Article
The predictive value of the National Early Warning Score for mortality and independent prognostic factors in patients with coronavirus disease 2019: A retrospective cohort study
2026
Overview
Introduction
The National Early Warning Score (NEWS) was introduced in 2012 by the Royal College of Physicians in the United Kingdom. It improves the assessment accuracy in acute illness and facilitates early detection of clinical deterioration. This study aimed to evaluate the prognostic value of NEWS in predicting outcomes among patients diagnosed with coronavirus disease 2019 (COVID-19) and to analyze the clinical characteristics and risk factors associated with mortality.
Methods
This retrospective cohort study analyzed the clinical data from patients with COVID-19 admitted to the emergency resuscitation room of Beijing Luhe Hospital, Capital Medical University, between December 2022 and January 2023. Data included initial laboratory test results obtained within 1 h of admission, chest computed tomography findings, NEWS, Modified Early Warning Score (MEWS), and quick Sequential Organ Failure Assessment (qSOFA) score. Receiver operating characteristic curves were used to evaluate the predictive performance of NEWS, MEWS, and qSOFA for 30-day all-cause mortality. Patients were categorized into survivor and nonsurvivor groups. Differences in laboratory parameters and imaging features between the two groups were compared, and logistic regression was employed to identify independent risk factors for prognosis.
Results
A total of 446 patients were enrolled, including 219 survivors and 227 nonsurvivors. The area under the receiver operating characteristic curve (AUROC) for predicting mortality was 0.945 (95% confidence interval: 0.926–0.963) for NEWS, which was significantly higher than those for MEWS (0.903, 95% confidence interval: 0.877–0.929) and qSOFA (0.902, 95% confidence interval: 0.881–0.923) (p < 0.05). No significant difference was observed between the AUROCs of MEWS and qSOFA. Multivariate logistic regression analysis identified NEWS, white blood cell count, platelet count, D-dimer level, comorbidities (respiratory diseases and diabetes), and clinical classification as independent risk factors for COVID-19 prognosis (all p < 0.05). Moreover, the proportion of patients with bilateral lung involvement exceeding 50% on chest computed tomography was significantly higher in the nonsurvivor group (81.8%, p < 0.001).
Conclusion
Early application of NEWS combined with key laboratory indicators is valuable for assessing disease severity and predicting prognosis in patients with COVID-19.
