National Early Warning Score 2 to Predict ICU Admission of COVID-19 Patients in Bangladeshi Cohort
DOI:
https://doi.org/10.3329/ewmcj.v12i1.77180Keywords:
COVID-19, National Early Warning Score 2 NEWS2, ICU, and BangladeshAbstract
Objective: To assess the predictive accuracy of the National Early Warning Score 2 (NEWS 2) for early prediction of clinical deterioration (ICU admission) of COVID-19- infected patients in Bangladesh. Methods: Data from 244 patients with COVID-19 infection admitted from July 2021- September 2021, to the Aichi Hospital Ltd, Bangladesh, were retrospectively reviewed. Consecutive adult patients with laboratory-confirmed COVID-19 initially admitted to non- ICU wards were included. Categorical and quantitative variables were expressed as numbers (percentages) and median (interquartile range, IQR). We evaluated the predictive performance of NEWS2 to predict ICU admission by comparing the area under the receiver operating characteristics curve (AUROC) at thresholds 5 and 7 and assessed its association with ICU admission by performing multivariate logistic analyses. STATA conducted all the statistical analyses. Results: Among the included 218 patients, 68 patients were transferred to ICU. The AUROC was 0.96 (Standard error 0.01, 95% confidence interval 0.93-0.98), revealing that NEWS2 at hospital admission was a good predictor of ICU admission. A NEWS2 threshold of 5 had higher sensitivity than a threshold of 7 (72.06% and 29.41%). A point of 7 also had high specificity (99.33% and 63.33%) and a high positive predictive value than a threshold of 5 (95.24% vs. 47.12%). The NEWS2 entries 5 and 7 were related to ICU admission found in multivariate logistic regression analysis. Conclusion: Our results suggest that NEWS2 at hospital admission is a good predictor for ICU admission of COVID-19 patients in Bangladesh. Screening patients at admission with this tool may identify patients at risk of clinical deterioration and help in better management.
EWMCJ Vol. 12, No. 1&2, January-July 2024: 60-65
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Copyright (c) 2024 Md Jahidul Islam
This work is licensed under a Creative Commons Attribution 4.0 International License.