AUTHOR=Yin Zhengrong , Zhou Mei , Xu Juanjuan , Wang Kai , Hao Xingjie , Tan Xueyun , Li Hui , Wang Fen , Dai Chengguqiu , Ma Guanzhou , Wang Zhihui , Duan Limin , Jin Yang 

TITLE=Predictive Risk Factors at Admission and a “Burning Point” During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19

JOURNAL=Frontiers in Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.816314

DOI=10.3389/fmed.2022.816314

ISSN=2296-858X

ABSTRACT=Background: We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for COVID-19 patients.
Methods: We evaluated COVID-19 patients admitted to Wuhan West Union Hospital between January 12 and February 25, 2020. Patients’ data were collected and the illness severity were assessed.
Results: Among 1150 enrolled patients, 296 (25.7%) developed into critical illness. A baseline nomogram model consist of seven variables including age (odds ratio [OR], 1.028; 95% confidence interval [CI], 1.004-1.052), SOFA score (OR, 4.367; 95% CI, 3.230-5.903), NLR (OR, 1.094; 95% CI, 1.024-1.168), D-dimer (OR, 1.476; 95% CI, 1.107-1.968), LDH (OR, 1.004; 95% CI, 1.001-1.006), INR (OR, 1.027; 95% CI, 0.999-1.055) and pneumonia area interpreted from CT images (medium vs. small [OR, 4.358; 95% CI, 2.188-8.678]; and large vs. small [OR, 9.567; 95% CI, 3.982-22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an AUC of 0.960 (95% CI, 0.941-0.972) in the training set and an AUC of 0.958 (95% CI, 0.936-0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2; increase per day [I/d], +0.49), NLR (value, 10.61; I/d, +2.07), CRP (value, 46.9 mg/L; I/d, +4.95), glucose (value, 7.83 mmol/L; I/d, +0.2), D-dimer (value, 6.08 μg/L; I/d, +0.28), LDH (value, 461 U/L; I/d, +13.95), and BUN (value, 6.51 mmol/L; I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset (CIO) during hospitalization.
Conclusion: The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for COVID-19 patients.