Background: This study aims to compare the epidemiological, clinical and laboratory characteristics between patients with coronavirus disease (COVID-19) and influenza A (H1N1), and to develop a differentiating model and a simple scoring system.
Methods: We retrospectively analyzed the data from patients with COVID-19 and H1N1. The logistic regression model based on clinical and laboratory characteristics was constructed to distinguish COVID-19 from H1N1. Scores were assigned to each of independent discrimination factors based on their odds ratios. The performance of the prediction model and scoring system was assessed.
Results: A total of 236 patients were recruited, including 20 COVID-19 patients and 216 H1N1 patients. Logistic regression revealed that age >34 years, temperature ≤37.5 °C, no sputum or myalgia, lymphocyte ratio ≥20% and creatine kinase-myocardial band isoenzyme (CK-MB) >9.7 U/L were independent differentiating factors for COVID-19. The area under curves (AUCs) of the prediction model and scoring system in differentiating COVID-19 from H1N1 were 0.988 and 0.962, respectively.
Conclusions: There are certain differences in clinical and laboratory features between patients with COVID-19 and H1N1. The simple scoring system may be a useful tool for the early identification of COVID-19 patients from H1N1 patients.
Keywords: Clinical characteristics; Coronavirus disease; Influenza A.
Copyright: © World Journal of Emergency Medicine.