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Early Prediction of Severe COVID-19 in Patients by a Novel Immune-Related Predictive Model.
Sun, Caiyu; Xue, Mingshan; Yang, Min; Zhu, Lihui; Zhao, Yunxue; Lv, Xiaoting; Lin, Yueke; Ma, Dapeng; Shen, Xuecheng; Cheng, Yeping; Xuan, Haocheng; Jia, Xiaoqing; Li, Tao; Han, Lihui.
  • Sun C; Shandong 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.
  • Xue M; State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Yang M; Shandong 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.
  • Zhu L; Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
  • Zhao Y; Department of Pharmacology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Lv X; Shandong 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.
  • Lin Y; Shandong 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.
  • Ma D; Shandong 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.
  • Shen X; Shandong 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.
  • Cheng Y; Shandong 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.
  • Xuan H; Shandong 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.
  • Jia X; Department of Gastroenterology, Qilu Hospital, Shandong University, Jinan, Shandong, China.
  • Li T; Department of Infectious Diseases, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
  • Han L; Shandong 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.
mSphere ; 6(5): e0075221, 2021 10 27.
Article in English | MEDLINE | ID: covidwho-1526451
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.
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Full text: Available Collection: International databases Database: MEDLINE Document Type: Article Main subject: Severity of Illness Index / Clinical Decision Rules / COVID-19 Testing / COVID-19 Subject: Severity of Illness Index / Clinical Decision Rules / COVID-19 Testing / COVID-19 Type of study: Diagnostic study / Prognostic study / Risk factors Language: English Journal: MSphere Clinical aspect: Diagnosis / Prediction / Prognosis Year: 2021

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Full text: Available Collection: International databases Database: MEDLINE Document Type: Article Main subject: Severity of Illness Index / Clinical Decision Rules / COVID-19 Testing / COVID-19 Subject: Severity of Illness Index / Clinical Decision Rules / COVID-19 Testing / COVID-19 Type of study: Diagnostic study / Prognostic study / Risk factors Language: English Journal: MSphere Clinical aspect: Diagnosis / Prediction / Prognosis Year: 2021
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