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Comparative Characterization and Risk Stratification of Asymptomatic and Presymptomatic Patients With COVID-19.
Lei Shi1, Rong Ding2,3, Tingting Zhang2,3
1Affiliated First People's Hospital of Kunshan, Gusu College of Nanjing Medical University, Suzhou, China.
Frontiers in Immunology
|July 26, 2021
Summary
A new risk-stratification model effectively distinguishes asymptomatic, severe presymptomatic, and non-severe presymptomatic coronavirus disease 2019 (COVID-19) patients using laboratory indicators. This aids in optimizing clinical management and prognosis for 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.
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