Novel COVID Model to Help Early Diagnosis of COVID-19 and Prediction of Disease Severity: A Multicenter Study

Autor: Muhammad Mostafa Abdel Ghaffar, Hend Ibrahim Shousha, Mohamed Omran, Ahmed Heiba, Ahmad ElAskary, Samah Abdel Hafez, Ahmed Abdel Azeem Wahdan, Dalia Omran
Rok vydání: 2021
Zdroj: Microbiology & Infectious Diseases. 5
ISSN: 2639-9458
Popis: Early identification of patients with coronavirus disease-2019 (COVID-19) particularly those who develop critical illness is of great importance and aids in delivering proper treatment and optimizing the use of resources. This work aimed to develop a clinical score at hospital admission for COVID-19 diagnosis and predicting severe disease. This is a multicenter case-control study including 2793 PCR-confirmed consecutive COVID-19 patients and 251 patients without COVID-19 presented to 6 hospitals affiliated to the General Organization for Teaching Hospitals, Egypt (1st-May-2020 to 31st-July-2020). There was no difference among groups regarding age and gender distribution. Patients with COVID-19 had significantly higher white blood cell count, platelet count, ALT, AST, total serum bilirubin, serum creatinine, CRP, Ferritin, D-dimer, and fibrinogen and lower serum albumin and more prolonged INR. ALT, ferritin, D-dimer, and Fibrinogen were significantly higher and oxygen saturation was significantly lower, in patients with severe COVID-19. Multivariate regression analysis revealed Oxygen saturation, ferritin, D-dimer and CRP are the independent factors associated with severity. We developed a novel COVID model which enabled the correct diagnosis of COVID-19 at cutoff point (0.1) with an AUC=0.99, (P-value
Databáze: OpenAIRE