Comparative Characterization and Risk Stratification of Asymptomatic and
Presymptomatic Patients with COVID-19
Abstract
The identification of asymptomatic, non-severe presymptomatic, and
severe presymptomatic coronavirus disease (COVID-19) in patients may
help optimize risk-stratified clinical management and improve prognosis.
This single-center case series from Wuhan Huoshenshan Hospital, China,
included 2,980 patients with COVID-19 who were hospitalized between
February 4, 2020 and April 10, 2020. Patients were diagnosed as
asymptomatic (n=39), presymptomatic (n=34), and symptomatic (n=2,907)
upon admission. This study provided an overview of asymptomatic,
presymptomatic, and symptomatic COVID-19 patients, including detection,
demographics, clinical characteristics, and outcomes. Upon admission,
there was no significant difference in clinical symptoms and CT image
between asymptomatic and presymptomatic patients for diagnosis
reference. The mean area under the receiver operating characteristic
curve (AUC) of the differential diagnosis model to discriminate
presymptomatic patients from asymptomatic patients was 0.89 (95% CI,
0.81-0.98). The severe and non-severe presymptomatic patients can be
further stratified (AUC = 0.82). The two-step risk-stratification model
based on 10 laboratory indicators on admission can facilitate early
identification of asymptomatic patients with COVID-19 and predict
illness severity for appropriate clinical management. Moreover,
single-cell data analyses revealed that the CD8+T cell exhaustion
contributed to the progression of COVID-19.