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Early Prediction of Severe COVID-19 in Patients by a Novel Immune-Related Predictive Model
Caiyu Sun1, Mingshan Xue2, Min Yang1
1Shandong Provincial Key Laboratory of Infection and Immunology, Shandong Provincial Clinical Research Center for Immune Diseases and Gout, Department of Immunology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Insights
A new NEAR model combining neutrophil, eosinophil, and IgA levels effectively predicts severe COVID-19. This tool aids clinicians in early identification and better patient management for coronavirus disease 2019.
Area of Science:
- Immunology
- Infectious Diseases
- Biostatistics
Background:
- COVID-19 progression involves dynamic immune and inflammatory responses.
- These responses correlate with disease severity and patient outcomes.
- Predicting severe COVID-19 is crucial for timely clinical intervention.
Purpose of the Study:
- To develop a predictive model for severe COVID-19 using immune and inflammatory markers.
- To identify key indicators capable of discriminating between severe and non-severe cases.
- To validate the predictive performance and clinical utility of the developed model.
Main Methods:
- Collected demographic and immune-inflammatory data from COVID-19 patients.
- Utilized logistic regression to identify independent predictors of severe disease.
- Constructed the Neutrophil, Eosinophil, and IgA (NEAR) ratio model.
- Validated the model using ROC curves, cross-validation, and external datasets.
Main Results:
- Identified neutrophils, eosinophils, and IgA as key predictors.
- Developed the NEAR model: NEU [10^9/L] - 150×EOS [10^9/L] + 3×IgA [g/L].
- NEAR model achieved an AUC of 0.961 with 100% sensitivity and 88.89% specificity at a threshold of 9.
- Model demonstrated high accuracy in predicting severe COVID-19.
Conclusions:
- The NEAR model is an effective and powerful tool for predicting COVID-19 severity.
- This predictive index can significantly aid clinicians in making informed treatment decisions.
- Eosinophils and IgA are identified as novel prognostic markers for COVID-19 severity.
Abstract:
During the progression of coronavirus disease 2019 (COVID-19), immune response and inflammation reactions are dynamic events that develop rapidly and are associated with the severity of disease. Here, we aimed to develop a predictive model based on the immune and inflammatory response to discriminate patients with severe COVID-19. COVID-19 patients were enrolled, and their demographic and immune inflammatory reaction indicators were collected and analyzed. Logistic regression analysis was performed to identify the independent predictors, which were further used to construct a predictive model. The predictive performance of the model was evaluated by receiver operating characteristic curve, and optimal diagnostic threshold was calculated; these were further validated by 5-fold cross-validation and external validation. We screened three key indicators, including neutrophils, eosinophils, and IgA, for predicting severe COVID-19 and obtained a combined neutrophil, eosinophil, and IgA ratio (NEAR) model (NEU [109/liter] - 150×EOS [109/liter] + 3×IgA [g/liter]). NEAR achieved an area under the curve (AUC) of 0.961, and when a threshold of 9 was applied, the sensitivity and specificity of the predicting model were 100% and 88.89%, respectively. Thus, NEAR is an effective index for predicting the severity of COVID-19 and can be used as a powerful tool for clinicians to make better clinical decisions. IMPORTANCE The immune inflammatory response changes rapidly with the progression of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and is responsible for clearance of the virus and further recovery from the infection. However, the intensified immune and inflammatory response in the development of the disease may lead to more serious and fatal consequences, which indicates that immune indicators have the potential to predict serious cases. Here, we identified both eosinophils and serum IgA as prognostic markers of COVID-19, which sheds light on new research directions and is worthy of further research in the scientific research field as well as clinical application. In this study, the combination of NEU count, EOS count, and IgA level was included in a new predictive model of the severity of COVID-19, which can be used as a powerful tool for better clinical decision-making.
