Abstract
Objective
Early triage of patients with coronavirus disease 2019 (COVID-19) is pivotal in managing the disease. However, studies on the clinical risk score system of the risk factors for the development of severe disease are limited. Hence, we conducted a clinical risk score system for severe illness, which might optimize appropriate treatment strategies.
Methods
We conducted a retrospective, single-center study at the JinYinTan Hospital from January 24, 2020 to March 31, 2020. We evaluated the demographic, clinical, and laboratory data and performed a 10-fold cross-validation to split the data into a training set and validation set. We then screened the prognostic factors for severe illness using the least absolute shrinkage and selection operator (LASSO) and logistic regression, and finally conducted a risk score to estimate the probability of severe illness in the training set. Data from the validation set were used to validate the score.
Results
A total of 295 patients were included. From 49 potential risk factors, 3 variables were measured as the risk score: neutrophil to lymphocyte ratio (OR, 1.27; 95% CI, 1.15–1.39), albumin (OR, 0.76; 95% CI, 0.70–0.83), and chest computed tomography abnormalities (OR, 2.01; 95% CI, 1.41–2.86) and the AUC of the validation cohort was 0.822 (95% CI, 0.7667–0.8776).
Conclusion
This report may help define the potential of developing severe illness in patients with COVID-19 at an early stage, which might be related to the neutrophil to lymphocyte ratio, albumin, and chest computed tomography abnormalities.
Key words: COVID-19, Risk factors, Severe illness, Nomogram
Biographies
Biographical notes of the first authors: XIONG Yi Bai, male, born in 1991, MD, majoring in cancer and infectious diseases
TIAN Ya Xin, female, born in 1993, MD, majoring in applied economics
MA Yan, female, born in 1980, MD, majoring in epidemiology, prevention and control of infectious disease.
Footnotes
This work was supported by National Science and Technology Major Project [2018ZX10101001-005] and China Academy of Chinese Medical Sciences Project [No. 2020YFC0841500].
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