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Utility of early warning scores to predict mortality in COVID-19 patients: A retrospective observational study
Nidhi Kaeley1, Prakash Mahala1, Ankita Kabi1
1Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.
Insights
Early warning scores (EWS) effectively predict mortality in COVID-19 patients. These scores aid in early severity assessment for better patient outcomes.
Area of Science:
- Critical Care Medicine
- Infectious Diseases
- Public Health
Background:
- COVID-19 presents with varying severity, posing a global health challenge.
- While less fatal than SARS-CoV, COVID-19 mortality is higher in older adults and those with comorbidities.
- Early identification of high-risk patients is crucial for effective management.
Purpose of the Study:
- To evaluate the predictive utility of various Early Warning Scores (EWS) for mortality in COVID-19 patients.
- To compare the effectiveness of different EWS in assessing disease severity.
- To determine if EWS can aid in early risk stratification for COVID-19 patients.
Main Methods:
- Retrospective study conducted at a tertiary care institute.
- Collected demographic and clinical data from moderate-to-severe COVID-19 patients.
- Calculated 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).
Main Results:
- REMS and WPS demonstrated the highest predictive accuracy for mortality (AUC = 0.892).
- NEWS showed good predictive value (AUC = 0.813), followed by MEWS (AUC = 0.770) and RAPS (AUC = 0.755).
- All evaluated EWS showed significant predictive capability for mortality in COVID-19 patients.
Conclusions:
- Early Warning Scores (EWS) are valuable tools for the early assessment of severity in COVID-19 patients.
- Triage EWS can reliably predict mortality risk in individuals with COVID-19.
- Implementing EWS at triage can improve patient management and outcomes.
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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