Urine Metabolites of Suspected Community-Acquired Pneumonia

Lilliam Ambroggio, Todd A Florin, Kayla Williamson, Grace Bosma, Brandie D Wagner, Larisa Yeomans, Jae Hyun Kim, Heidi Sucharew, Maurizio Macaluso, Richard M Ruddy, Kathleen A Stringer, Samir S Shah
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Abstract

Background Accurate diagnosis of community-acquired pneumonia (CAP) can be challenging. Clinical findings are non-specific, and interpretations of chest radiographs have poor inter-rater reliability. Pilot studies demonstrate the potential for metabolomics to identify metabolite concentrations that differentiate children with CAP from those without. The objective of this study was to expand these findings in a large cohort of children with CAP compared with controls. Methods Urine was collected from children, 3 months to 12 years old, with emergency department visits for suspected CAP and community-based controls. Nuclear magnetic resonance spectrometry was used to identify and quantify metabolites. A random forest approach developed three models discriminating cases from community-based controls based on: 1) clinical signs and symptoms; 2) metabolites, and 3) the combination of both. The area under the receiver operating characteristic curve (AUC) was computed for each model. Results Included were 253 cases and 122 controls. The metabolite-only model had similar discriminatory ability as the combination model (AUC: 0.97 and 0.99, respectively). The discriminating metabolites in the metabolite-only model were 2-aminobutyrate, fumarate, hypoxanthine, acetone, leucine, quinolinate, valine, O-acetylcarnitine, citrate and trigonelline. In the combined model, discriminatory clinical factors included receipt of corticosteroids, fever, cough, rapid breathing, decreased oral intake, difficulty breathing, receipt of albuterol, abnormal sleepiness, vomiting and wheezing, and included five additional metabolites compared to the metabolite only model (4-hydroxybenzoate, isoleucine, carnitine, 2-hydroxyisovalerate, betaine, succinate). Conclusions Urine metabolite concentrations can accurately discriminate healthy children from children with suspected CAP. Metabolites associated with CAP may overcome limitations of prior diagnostic approaches.
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