Evaluation and Validation of a Model for Identifying Serious Bacterial Infections among Children Presenting to the Emergency: Evidence-based Medicine Viewpoint.

Abstract

In this diagnostic accuracy study of clinical and biomarker variables in the diagnosis of serious bacterial infections (SBIs), including pneumonia, in febrile children (age <16 y), a diagnostic model was derived by using multinomial logistic regression and internal validity. External validation of a published model was undertaken, followed by model updating and extension by the inclusion of procalcitonin and resistin. There were 1101 children studied, of whom 264 had a SBI. A diagnostic model discriminated well between pneumonia and no SBI (concordance statistic 0.84, 95% CI 0.78–0.90) and between other SBIs and no SBI (0.77, 95% CI 0.71–0.83) on internal validation. A published model discriminated well on external validation. Model updating yielded good calibration with good performance at both high-risk (positive likelihood ratios 6.46 and 5.13 for pneumonia and other SBI, respectively) and low-risk (negative likelihood ratios 0.16 and 0.13, respectively) thresholds. Extending the model with procalcitonin and resistin yielded improvements in discrimination. The authors concluded that diagnostic models discriminated well between pneumonia, other SBIs, and no SBI in febrile children in the emergency department.