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ORIGINAL ARTICLE
Year : 2021  |  Volume : 11  |  Issue : 3  |  Page : 161-166

Utility of early warning scores to predict mortality in COVID-19 patients: A retrospective observational study


1 Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
2 Department of Microbiology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India

Correspondence Address:
Dr. Prakash Mahala
Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijciis.ijciis_64_21

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Background: Coronavirus disease 2019 (COVID19) has evolved as a global pandemic. The patients with COVID-19 infection can present as mild, moderate, and severe disease forms. The reported mortality of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection is around 6.6%, which is lower than that of SARS-CoV and (middle east respiratory syndrome CoV). However, the fatality rate of COVID-19 infection is higher in the geriatric age group and in patients with multiple co-morbidities. The study aimed to evaluate the utility of early warning scores (EWS) to predict mortality in patients with moderate to severe COVID-19 infection. Methods: This retrospective study was carried out in a tertiary care institute of Uttarakhand. Demographic and clinical data of the admitted patients with moderate-to-severe COVID-19 infection were collected from the hospital record section and utilized to calculate the EWS-National early warning score (NEWS), modified early warning score (MEWS), Rapid Acute Physiology Score (RAPS), rapid emergency medicine score (REMS), and worthing physiological scoring system (WPS). Results: The area under the curve for NEWS, MEWS, RAPS, REMS, and WPS was 0.813 (95% confidence interval [CI]; 0.769–0.858), 0.770 (95% CI; 0.717–0.822), 0.755 (95% CI; 0.705–0.805), 0.892 (95% CI; 0.859–0.924), and 0.892 (95% CI; 0.86–0.924), respectively. Conclusion: The EWS at triage can be used for early assessment of severity as well as predict mortality in patients with COVID-19 patients.


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