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[Validation of a simplified prediction rule to identify etiology in children with pneumonia].

作者信息

López Mariela, Torres Fernando, Davenport Carolina, Rial María José, González Norma, Ferrero Fernando

机构信息

División Neumotisiología, Hospital General de Niños Pedro de Elizalde.

出版信息

Arch Argent Pediatr. 2011 Dec;109(6):499-503. doi: 10.5546/aap.2011.499.

DOI:10.5546/aap.2011.499
PMID:22231887
Abstract

INTRODUCTION

Identifying on admission those children with bacterial pneumonia could reduce inappropriate antibiotic use. The BPS (Bacterial Pneumonia Score) is a clinical prediction rule that accurately identifies children with bacterial pneumonia. Because the interpretation of chest X-ray included in this model could be considered difficult, a simplified version was developed, but this version has not yet been validated in a different population.

OBJECTIVE

To validate a simplified clinical prediction rule to identify children with an increased risk of having bacterial pneumonia.

METHODS

Children aged under 5 years, hospitalized for pneumonia (viral or bacterial) were included. On admission, axillary temperature, age, absolute neutrophil count, bands, and chest radiograph were evaluated.

RESULTS

We included 168 patients (23 with bacterial pneumonia and 145 with viral pneumonia). Those with bacterial pneumonia showed a score higher than those with viral pneumonia (5.3 ± 2.5 vs. 2.6 ± 2.02; p <0.001). A score =3 points was identified as the optimum cutoff value to predict bacterial pneumonia (aucROC= 0.79; 95% IC: 0.68-0.90), and was more frequent among patients with bacterial than viral pneumonia (19/23 vs. 42/145, p= 0.003; OR: 4.8; CI95%: 1.4-17.6), achieving 82.6% sensitivity, 50.3% specificity, 20.9% positive predictive value, 94.8% negative predictive value, 1.66 positive likelihood ratio and 0.35 negative likelihood ratio.

CONCLUSIONS

The evaluated simplified prediction rule showed a limited diagnostic accuracy on identifying children with bacterial pneumonia, being less accurate than the BPS.

摘要

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