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Comparison of national early warning score 2 and quick sepsis-related organ failure assessment score in predicting severe coronavirus disease 2019: A validation study
1Department of Chest Diseases, University of Health Sciences, Tepecik Training and Research Hospital, İzmir, Türkiye
2Department of Chest Diseases, İzmir Bakırçay University, Ciğli Training and Research Hospital, İzmir, Türkiye
3Department of Chest Diseases, Dr. Suat Seren Chest Disease and Thoracic Surgery Training and Research Hospital, İzmir, Türkiye
Eurasian Journal of Pulmonology 185-192 DOI: 10.14744/ejp.2022.6002
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BACKGROUND AND AIM: Coronavirus disease 2019 (COVID-19) has imposed a heavy burden on the intensive care unit and health care systems worldwide. Therefore, early detection of high-risk patients in terms of poor prognosis is crucial. We aimed to compare the diagnostic yield of the two most reliable scoring systems (National Early Warning Score 2 [NEWS 2] and quick Sepsis-related Organ Failure Assessment [qSOFA]) when repeatedly performed during the COVID-19 course.

METHODS: The data of 403 COVID-19 patients admitted to our hospital between March 1, 2020, and November 30, 2020, were retrospectively reviewed. The demographic, comorbidity, and clinical data of the patients were recorded in the evaluation. NEWS2 and qSOFA score were retrospectively calculated at the time of admission, 24th hour, and 48th hour. We compared the effectiveness of qSOFA and NEWS2 for predicting the prognosis of COVID-19.

RESULTS: The mean NEWS2 at the time of admission, 24th hour, and 48th hour was significantly higher in patients with poor outcomes than in patients with good outcomes. The 48th-hour NEWS2 was found to be the most successful score in predicting the poor outcome (AUC: 0.854; 95% CI: 0.81–0.88; p<0.001). NEWS2 at 0th, 24th, and 48th hours were found to be superior to qSOFA scores at the same time points.

CONCLUSIONS: NEWS2 was superior to qSOFA in determining the need for intensive care support and/or mortality. A high NEWS2 at the 48th hour seems to be more valuable to predict worse outcomes.