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A tool to distinguish viral from bacterial pneumonia

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

medRxiv (Cold Spring Harbor Laboratory)(2021)

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摘要
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.
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bacterial pneumonia
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