A Novel Prediction Model of COVID-19 Progression: A Retrospective Cohort Study

Estimating the risk of disease progression is of utmost importance for planning appropriate setting of care and treatment for patients with coronavirus disease 2019 (COVID-19). This study aimed to develop and validate a novel prediction model of COVID-19 progression.

In total, 814 patients in the training set were included to develop a novel scoring system; and 420 patients in the validation set were included to validate the model.

A prediction score, called ACCCDL, was developed on the basis of six risk factors associated with COVID-19 progression: age, comorbidity, CD4⁺ T cell count, C-reactive protein (CRP), D-dimer, and lactate dehydrogenase (LDH). For predicting COVID-19 progression, the ACCCDL score yielded a significantly higher area under the receiver operating characteristic curve (AUROC) compared with the CALL score, CoLACD score, PH-COVID-19 score, neutrophil-lymphocyte ratio, and lymphocyte-monocyte ratio both in the training set (0.92, 0.84, 0.83, 0.83, 0.76, and 0.65, respectively) and in the validation set (0.97, 0.83, 0.83, 0.78, 0.74, and 0.60, respectively). Over 99% of patients with the ACCCDL score < 12 points will not progress to severe cases, and over 30% of patients with the ACCCDL score > 20 points will progress to severe cases.

The ACCCDL score could stratify patients with at risk of COVID-19 progression, and was useful in regulating the large flow of patients with COVID-19 between primary health care and tertiary centers.