PT  - JOURNAL ARTICLE
AU  - Sriram Ramgopal
AU  - Lilliam Ambroggio
AU  - Douglas Lorenz
AU  - Samir S. Shah
AU  - Richard M. Ruddy
AU  - Todd A. Florin
TI  - Incorporation of biomarkers into a prediction model for paediatric radiographic pneumonia
AID  - 10.1183/23120541.00339-2022
DP  - 2022 Jan 01
TA  - ERJ Open Research
PG  - 00339-2022
4099  - http://openres.ersjournals.com/content/early/2022/10/13/23120541.00339-2022.short
4100  - http://openres.ersjournals.com/content/early/2022/10/13/23120541.00339-2022.full
AB  - Objective To evaluate biomarkers to predict radiographic pneumonia among children with suspected lower respiratory tract infections (LRTI).Methods We performed a single-center 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 (WBC), absolute neutrophil count (ANC), 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 cutoff 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 c-index (0.780 to 0.812) compared with a model including only clinical variables.Conclusion A model consisting of 3 clinical variables and CRP demonstrated improved performance for the identification of radiographic pneumonia compared with a model with clinical variables alone.FootnotesThis manuscript has recently been accepted for publication in the ERJ Open Research. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJOR online. Please open or download the PDF to view this article.Conflicts of Interest: The authors have nothing to disclose.