Abstract

Influenza A is the most common viral pathogen isolated from pediatric clinics during influenza seasons. Some young patients with influenza manifest rapid progression with high fever and severe sequelae, such as pneumonia and meningitis. Therefore, early diagnosis and prompt treatment are highly important. Specific diagnostic tests currently include antigen detection, antibody detection, nucleic acid test and virus isolation. Rapid antigen testing is the most commonly adopted method in the outpatient setting, but false negative results are frequently observed, which causes delayed treatment and severe outcome. Routine blood test is the most commonly used detection for the outpatients. Incorporating specific blood cell counts into rapid antigen test may overcome some technical issues and enable accurate early diagnosis. We enrolled 537 children with influenza-like symptoms like fever or respiratory symptoms from pediatric outpatients and 110 children without infectious diseases for control. Routine blood tests detected by a routine analyzer and influenza A virus antigen detection were performed in the patients. Significant blood routine parameters between groups were examined by statistical tests. Parameters in routine blood test were assessed by the receiver operating characteristic curve to find the screening indicators of influenza A. Multivariate logistic regression were used to establish the optimal combinations of blood routine parameters in our screening model. Two subgroups were set according to age: ≤6 years old group and >6 years old group. In each group, patients were further divided into three subgroups: the influenza A-positive-result group (A+ group) (n=259), influenza A-negative-result group (A- group) (n=277) and healthy control group (H group) (n=110). Most routine blood parameters showed significant differences among the three subgroups in each age group. Notably, lymphocyte (LYM) number, platelet (PLT) number, lymphocyte-to-monocyte ratio (LMR) and LYM multiplied by PLT (LYM*PLT) exhibited extremely significant differences. Using A- group as a reference based on the area under the curve (AUC), both age groups had a similar trend. For A- group, the optimal cutoff value of LYM*PLT was 221.6, the AUC, the sensitivity and specificity were 0.6830, 55.71% and 76.92% in the ≤6 years old group. Meanwhile, the cutoff value of LYM*PLT was 196.7, and the AUC, the sensitivity and specificity were 0.6448, 53.97% and 70.81%, respectively in the >6 years old group. Screening model based on multivariate logistic regression model revealed that LYM*PLT was the optimal parameter combinations in ≤6 years old group (AUC =0.7202), while LYM and PLT were the optimal parameter combinations in >6 years old group (AUC =0.6760). Several blood routine parameters in children with influenza A demonstrate differential levels in both age subgroups. The LYM*PLT exhibits the potential screening value of influenza infection.

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