Diagnosing serious infections in acutely ill children in ambulatory care (ERNIE 2 study protocol, part A): diagnostic accuracy of a clinical decision tree and added value of a point-of-care C-reactive protein test and oxygen saturation.

摘要

Acute illness is the most common presentation of children to ambulatory care. In contrast, serious infections are rare and often present at an early stage. To avoid complications or death, early recognition and adequate referral are essential. In a recent large study children were included prospectively to construct a symptom-based decision tree with a sensitivity and negative predictive value of nearly 100%. To reduce the number of false positives, point-of-care tests might be useful, providing an immediate result at bedside. The most probable candidate is C-reactive protein, as well as a pulse oximetry.This is a diagnostic accuracy study of signs, symptoms and point-of-care tests for serious infections. Acutely ill children presenting to a family physician or paediatrician will be included consecutively in Flanders, Belgium. Children testing positive on the decision tree will get a point-of-care C-reactive protein test. Children testing negative will randomly either receive a point-of-care C-reactive protein test or usual care. The outcome of interest is hospital admission more than 24 hours with a serious infection within 10 days. Aiming to include over 6500 children, we will report the diagnostic accuracy of the decision tree (+/- the point-of-care C-reactive protein test or pulse oximetry) in sensitivity, specificity, positive and negative likelihood ratios, and positive and negative predictive values. New diagnostic algorithms will be constructed through classification and regression tree and multiple logistic regression analysis.We aim to improve detection of serious infections, and present a practical tool for diagnostic triage of acutely ill children in primary care. We also aim to reduce the number of investigations and admissions in children with non-serious infections.ClinicalTrials.gov Identifier: NCT02024282.