Performance of Diagnostic Model for Differentiating Between COVID-19 and Influenza: A 2-Center Retrospective Study

Abstract

Background COVID-19 and influenza share many similarities, such as mode of transmission and clinical symptoms. Failure to distinguish the 2 diseases may increase the risk of transmission. A fast and convenient differential diagnosis between COVID-19 and influenza has significant clinical value, especially for low- and middle-income countries with a shortage of nucleic acid detection kits. We aimed to establish a diagnostic model to differentiate COVID-19 and influenza based on clinical data. Material/Methods A total of 493 patients were enrolled in the study, including 282 with COVID-19 and 211 with influenza. All data were collected and reviewed retrospectively. The clinical and laboratory characteristics of all patients were analyzed and compared. We then randomly divided all patients into development sets and validation sets to establish a diagnostic model using multivariate logistic regression analysis. Finally, we validated the diagnostic model using the validation set. Results We preliminarily established a diagnostic model for differentiating COVID-19 from influenza that consisted of 5 variables: age, dry cough, fever, white cell count, and D-dimer. The model showed good performance for differential diagnosis. Conclusions This initial model including clinical features and laboratory indices effectively differentiated COVID-19 from influenza. Patients with a high score were at a high risk of having COVID-19, while patients with a low score were at a high risk of having influenza. This model could help clinicians quickly identify and isolate cases in the absence of nucleic acid tests, especially during the cocirculation of COVID-19 and influenza. Owing to the study’s retrospective nature, further prospective study is needed to validate the accuracy of the model.

Sensitivity and Specificity of Patient-Reported Clinical Manifestations to Diagnose COVID-19 in Adults from a National Database in Chile: A Cross-Sectional Study

“…Data from other studies have shown better diagnostic estimators for several of the clinical features that were included in this study, either in isolation or when integrated within multivariable models [ 21 , 22 , 23 ]. Estimators of precision well over 85% and ROC AUCs of 0.85–0.91 have been previously reported in the literature, findings that contrast with the more conservative AUC of roughly 0.75 that was found in both our simplified and full multivariable model [ 24 , 25 , 26 ]. It is likely that methodological differences explain these contrasts in accuracy, such as the retrospective nature of the aforementioned studies and the inclusion of non-clinical variables within models, such as computer tomography scans or laboratory data; in addition, the non-use of protective means may increase the predictive properties of the model.…”

D-dimer, CRP, PCT, and IL-6 Levels at Admission to ICU Can Predict In-Hospital Mortality in Patients with COVID-19 Pneumonia

“…Currently, the best-compared variance of mentioned parameters is between patients with COVID-19 and patients with influenza. Therefore, significantly higher CRP values on hospital admission were detected in influenza-positive subjects after comparing those groups of patients [ 44 ]. In their study, Kuang et al have evinced the higher incidence of influenza patients detected on admission with CRP value above 10 mg/dl and PCT value above 0.5 ng/mL, compared to COVID-19 patients [ 45 ].…”

Using logistic regression to develop a diagnostic model for COVID-19

“…[ 25 26 ] Therefore, developing an accurate diagnostic model that can effectively predict COVID-19 presence (diagnosis) with important prognostic determinants is indeed vital. [ 1 2 ] This study proposed an understandable, intuitive, and yet accurate prediction model using logistic regression based on the most important predictors.…”

“…It is thought that SARS-CoV-2 has animal origins that slipped from animal species into the human population. [ 1 2 ] The World Health Organization later on February 11, 2020 announced coronavirus disease 2019 “COVID-19” as the name of this new disease. [ 3 4 ] COVID-19 is a highly contagious viral infectious disease and continues to spreading aggressively around the whole world.…”