Comparative Characterization and Risk Stratification of Asymptomatic and Presymptomatic Patients With COVID-19

Area of Science:

• Infectious Diseases
• Clinical Medicine
• Immunology

Background:

• Accurate identification of coronavirus disease 2019 (COVID-19) patient categories is crucial for effective clinical management and prognosis.
• Distinguishing between asymptomatic, presymptomatic, and symptomatic COVID-19 cases presents diagnostic challenges.

Purpose of the Study:

• To develop and validate a risk-stratification model for classifying COVID-19 patients into asymptomatic, severe presymptomatic, and non-severe presymptomatic groups upon admission.
• To investigate the correlation between CD8+ T cell exhaustion and COVID-19 progression.

Main Methods:

• A single-center case series of 2,980 hospitalized COVID-19 patients.
• Development of a two-step risk-stratification model using 10 laboratory indicators.
• Analysis of differential diagnosis models and single-cell data.

Main Results:

• A risk-stratification model demonstrated high accuracy in distinguishing between asymptomatic and presymptomatic patients (AUC = 0.89).
• The model successfully stratified presymptomatic patients into severe and non-severe groups (AUC = 0.82).
• CD8+ T cell exhaustion was identified as a factor correlating with COVID-19 progression.

Conclusions:

• A validated two-step risk-stratification model using laboratory indicators can effectively classify COVID-19 patients upon admission.
• This model aids in optimizing risk-stratified clinical management and improving patient prognosis.
• Understanding immune cell dynamics, such as CD8+ T cell exhaustion, offers insights into disease progression.