A tool to distinguish viral from bacterial pneumonia

Author:

Tagarro AlfredoORCID,Moraleda Cinta,Domínguez-Rodríguez Sara,Rodríguez Mario,Dolores Martín María,Luisa Herreros María,Folgueira María Dolores,Pérez-Rivilla Alfredo,Jensen Julia,López Agustín,Berzosa Arantxa,de Santaeufemia Francisco José Sanz,Jiménez Ana Belén,Sainz TalíaORCID,Llorente Marta,Garrote Elisa,Muñoz Cristina,Sánchez Paula,Santos Mar,Illán Marta,Barrios Ana,Pacheco Mónica,Corral Raquel Ramos,Arquero Carmen,Bernardino María,Prieto Luis,Gutiérrez Lourdes,Epalza Cristina,Rojo Pablo,Oviedo Lidia,Serna-Pascual Miquel,Soto Beatriz,Guillén Sara,Molina David,Martín Elvira,Vázquez Carmen,Gerig Natalia,Calvo Cristina,Pilar Romero María,Imaz Manuel,Cañete Alfonso,Ramos José-Tomás,Galán Juan Carlos,Otheo Enrique

Abstract

ABSTRACTBackground and ObjectivesEstablishing the etiology of community-acquired pneumonia (CAP) in children at admission is challenging. As a result, most children receive antibiotics that do not need.This study aims to build and validate a diagnostic tool combining clinical, analytical and radiographical features to sequentially differentiate viral from bacterial CAP, and among bacterial CAP, typical from atypical bacteria, to improve choice of treatment.MethodsConsecutive hospitalized children between 1 month and 16 years of age with CAP were enrolled. An extensive microbiological workup was performed. A score was built with a training set of 70% patients, to first differentiate between viral and bacterial CAP and secondly, typical from atypical bacterial CAP. To select variables, a Ridge model was used. Optimal cut-off points were selected to maximize specificity setting a high sensitivity (80%). Weights of each variable were calculated with a multivariable logistic regression. The score was validated with the rest of the participants.ResultsIn total, 262 (53%) children (median age, 2 years, 52.3% male) had an etiological diagnosis.The step 1 discriminates viral from bacterial CAP. Bacterial CAPs were classified with a sensitivity=97%, a specificity=48%, and a ROC’s area under the curve (AUC)=0.81. If a CAP was classificated as bacterial, it was assessed with step 2. The step 2 differentiates typical vs. atypical bacterial CAP. Typical bacteria were classified with a sensitivity=100%, a specificity=64%, and AUC=0.90.ConclusionThis two-steps tool can facilitate the physician’s decision to prescribe antibiotics without compromising patient safety.Article summaryWe validated a clinical tool to predict the aetiology of CAP in children safely. This tool differentiates CAP into viral, atypical bacteria and typical bacteria.“What’s Known on This Subject”Establishing the aetiology of community-acquired pneumonia (CAP) in children at admission is challenging. As a result, most admitted children with CAP receive antibiotics.“What This Study Adds”We validated a clinical tool to predict the aetiology of pneumonia in children safely, differentiating among viral, atypical bacteria and typical bacteria.

Publisher

Cold Spring Harbor Laboratory

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