Clinical correlation of influenza and respiratory syncytial virus load measured by digital PCR

Hijano, Diego R.; Brazelton de Cardenas, Jessica; Maron, Gabriela; Garner, Cherilyn D.; Ferrolino, Jose A.; Dallas, Ronald H.; Gu, Zhengming; Hayden, Randall T.

Descriptive statistical analyses are presented as proportions for categorical data and mean ± standard deviation for continuous data. Statistical analysis was performed using the chi-squared test or Fisher's exact test, as appropriate, for categorical data, and Student's t-test for continuous variables. To account for difference in the number of samples per patient, a mixed linear regression model was used to determine association between viral load and clinical characteristics [Presence of symptoms, Number of symptoms and individual symptoms: Fever, Cough and Nasal Congestion) (Figs 1 and 2), Lymphocyte count (Fig 3) , Presence/ absence of co-infections, and Number of additional viruses (S2 Fig)] , with the random variable being the patient identifier. A similar mixed linear regression model approach was used to determine association between lymphocyte count and presence of symptoms. Logistic regression using initial viral load upon clinical presentation was used to assess the correlation between viral load and clinical complications in univariate and multivariate analysis. Paired ttests was used to compare samples before and after treatment. A P-value < 0.05 was considered statistically significant.