Abstract
Abstract
Background
Predictions about the hospital course of the coronavirus disease 2019 (COVID-19) patients are of paramount value. This research was designed to validate 4C mortality and CT severity scores (CT-SS) as prognostication tools of mortality and detect their relations among patients with COVID-19 who are hospitalized. The identification of other potential mortality risk factors was also evaluated.
Methods
Two hundred and ninety-six confirmed COVID-19 adult cases were prospectively included. They were allocated into 3 groups according to severity; 78 in moderate group, 97 in severe group, and 121 patients in critical group. Patient demographics, clinical characteristics, co-morbidities, lines of treatment, 4C mortality score and CT severity score were assessed upon admission.
Results
The study revealed that 90% and 84.3% sensitivities were observed for 4C mortality and CT-SS respectively as predictors of mortality. Significant correlation between both scores (r = 0.6. p = 0.0001) was detected. Multivariate analysis identified 6.9-fold increased risk of mortality for the patients with 4C mortality score > 9.5 (p = 0.001). CT-SS > 12, age ≥ 60, male gender, hypertension and diabetes mellitus were also found as significant independent factors associated with increased mortality.
Conclusions
Both of 4C mortality score and CT-SS have a high sensitivity as a risk-stratification scores with a considerable correlation. In addition, they represent the most independent risk factors associated with mortality in comparison to other clinical or laboratory indices.
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献