Performance of prediction rules and guidelines in detecting serious bacterial infections among Tanzanian febrile children.

Details

Serval ID
serval:BIB_10DA5CCB0ADB
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Performance of prediction rules and guidelines in detecting serious bacterial infections among Tanzanian febrile children.
Journal
BMC infectious diseases
Author(s)
Keitel K., Kilowoko M., Kyungu E., Genton B., D'Acremont V.
ISSN
1471-2334 (Electronic)
ISSN-L
1471-2334
Publication state
Published
Issued date
03/09/2019
Peer-reviewed
Oui
Volume
19
Number
1
Pages
769
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
Health-workers in developing countries rely on clinical algorithms, such as the Integrated Management of Childhood Illnesses (IMCI), for the management of patients, including diagnosis of serious bacterial infections (SBI). The diagnostic accuracy of IMCI in detecting children with SBI is unknown. Prediction rules and guidelines for SBI from well-resourced countries at outpatient level may help to improve current guidelines; however, their diagnostic performance has not been evaluated in resource-limited countries, where clinical conditions, access to care, and diagnostic capacity differ. The aim of this study was to estimate the diagnostic accuracy of existing prediction rules and clinical guidelines in identifying children with SBI in a cohort of febrile children attending outpatient health facilities in Tanzania.
Structured literature review to identify available prediction rules and guidelines aimed at detecting SBI and retrospective, external validation on a dataset containing 1005 febrile Tanzanian children with acute infections. The reference standard, SBI, was established based on rigorous clinical and microbiological criteria.
Four prediction rules and five guidelines, including IMCI, could be validated. All examined rules and guidelines had insufficient diagnostic accuracy for ruling-in or ruling-out SBI with positive and negative likelihood ratios ranging from 1.04-1.87 to 0.47-0.92, respectively. IMCI had a sensitivity of 36.7% (95% CI 29.4-44.6%) at a specificity of 70.3% (67.1-73.4%). Rules that use a combination of clinical and laboratory testing had better performance compared to rules and guidelines using only clinical and or laboratory elements.
Currently applied guidelines for managing children with febrile illness have insufficient diagnostic accuracy in detecting children with SBI. Revised clinical algorithms including simple point-of-care tests with improved accuracy for detecting SBI targeting in tropical resource-poor settings are needed. They should undergo careful external validation against clinical outcome before implementation, given the inherent limitations of gold standards for SBI.
Keywords
Childhood infections, Clinical prediction rules, Diagnostic accuracy, External validation, IMCI, Serious bacterial infections
Pubmed
Open Access
Yes
Create date
13/09/2019 17:17
Last modification date
10/01/2020 6:26
Usage data