The aim of this study is to construct a clinical distinction model to help determine the type of influenza by analyzing the clinical characteristics and hematological indicators of influenza patients during the influenza season. Demographic characteristics and clinical data of 726 influenza patients aged 7 years and older from September 2018 to July 2019 were collected, and logistic regression analysis was used to analyze the impact of different clinical manifestations and hematological examination indicators on the determination of the value of the flu type. The common clinical manifestations of influenza patients were fever (99.2%), pharyngeal congestion (97.1%), cough (80.4%), sore throat (57.2%), muscle aches (48.8%), and runny nose (45.2%). Those with onset of illness were 19-49 years of age (OR= 0.335, 95% CI: 0.196-0.573), nasal congestion (OR= 0.566, 95% CI: 0.349-0.919), and fever for more than 3 days (OR= 0.368, 95% CI: 0.214-0.632) tend to diagnosed as influenza B, while those with symptoms of cough (OR=2.119, 95% CI: 1.322-3.389), headache (OR=1.834, 95% CI: 1.157-2.908), muscle pain (OR=1.811, 95% CI: 1.139-2.880), and blood CPR>8mg/L (OR=2.315, 95%CI: 1.501-3.589) and the percentage of neutrophils >70% (OR=2.361, 95%CI: 1.171-4.759) are prone to have influenza A. Combining clinical manifestations and laboratory findings, we plotted a nomogram by lasso regression. The distinction model was discriminated using a C-index（0.765,95% CI 0.716-0.819) and an AUC value (0.772,95% CI 0.696-0.848), showing good prognostic accuracy and clinical applicability. This distinction model can distinguish well between the types of influenza,which can provide assistance in early treatment and prognosis of influenza.

The aim of this study is to construct a clinical distinction model to help determine the type of influenza by analyzing the clinical characteristics and hematological indicators of influenza patients during the influenza season. Demographic characteristics and clinical data of 726 influenza patients aged 7 years and older from September 2018 to July 2019 were collected, and logistic regression analysis was used to analyze the impact of different clinical manifestations and hematological examination indicators on the determination of the value of the flu type. The common clinical manifestations of influenza patients were fever (99.2%), pharyngeal congestion (97.1%), cough (80.4%), sore throat (57.2%), muscle aches (48.8%), and runny nose (45.2%). Those with onset of illness were 19-49 years of age (OR= 0.335, 95% CI: 0.196-0.573), nasal congestion (OR= 0.566, 95% CI: 0.349-0.919), and fever for more than 3 days (OR= 0.368, 95% CI: 0.214-0.632) tend to diagnosed as influenza B, while those with symptoms of cough (OR=2.119, 95% CI: 1.322-3.389), headache (OR=1.834, 95% CI: 1.157-2.908), muscle pain (OR=1.811, 95% CI: 1.139-2.880), and blood CPR>8mg/L (OR=2.315, 95%CI: 1.501-3.589) and the percentage of neutrophils >70% (OR=2.361, 95%CI: 1.171-4.759) are prone to have influenza A. Combining clinical manifestations and laboratory findings, we plotted a nomogram by lasso regression. The distinction model was discriminated using a C-index（0.765,95% CI 0.716-0.819) and an AUC value (0.772,95% CI 0.696-0.848), showing good prognostic accuracy and clinical applicability. This distinction model can distinguish well between the types of influenza,which can provide assistance in early treatment and prognosis of influenza.