Incorporation of biomarkers into a prediction model for paediatric radiographic pneumonia

OBJECTIVE: The aim of this study was to evaluate biomarkers to predict radiographic pneumonia among children with suspected lower respiratory tract infections (LRTI). METHODS: We performed a single-centre prospective cohort study of children 3 months to 18 years evaluated in the emergency department with signs and symptoms of LRTI. We evaluated the incorporation of four biomarkers (white blood cell count, absolute neutrophil count, C-reactive protein (CRP) and procalcitonin), in isolation and in combination, with a previously developed clinical model (which included focal decreased breath sounds, age and fever duration) for an outcome of radiographic pneumonia using multivariable logistic regression. We evaluated the improvement in performance of each model with the concordance (c-) index. RESULTS: Of 580 included children, 213 (36.7%) had radiographic pneumonia. In multivariable analysis, all biomarkers were statistically associated with radiographic pneumonia, with CRP having the greatest adjusted odds ratio of 1.79 (95% CI 1.47–2.18). As an isolated predictor, CRP at a cut-off of 3.72 mg·dL(−1) demonstrated a sensitivity of 60% and a specificity of 75%. The model incorporating CRP demonstrated improved sensitivity (70.0% versus 57.7%) and similar specificity (85.3% versus 88.3%) compared to the clinical model when using a statistically derived cutpoint. In addition, the multivariable CRP model demonstrated the greatest improvement in concordance index (0.780 to 0.812) compared with a model including only clinical variables. CONCLUSION: A model consisting of three clinical variables and CRP demonstrated improved performance for the identification of paediatric radiographic pneumonia compared with a model with clinical variables alone.