Diagnostic models predicting paediatric viral acute respiratory infections: a systematic review

Abstract

ObjectivesTo systematically review and evaluate diagnostic models used to predict viral acute respiratory infections (ARIs) in children.DesignSystematic review.Data sourcesPubMed and Embase were searched from 1 January 1975 to 3 February 2022.Eligibility criteriaWe included diagnostic models predicting viral ARIs in children (<18 years) who sought medical attention from a healthcare setting and were written in English. Prediction model studies specific to SARS-CoV-2, COVID-19 or multisystem inflammatory syndrome in children were excluded.Data extraction and synthesisStudy screening, data extraction and quality assessment were performed by two independent reviewers. Study characteristics, including population, methods and results, were extracted and evaluated for bias and applicability using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and PROBAST (Prediction model Risk Of Bias Assessment Tool).ResultsOf 7049 unique studies screened, 196 underwent full text review and 18 were included. The most common outcome was viral-specific influenza (n=7; 58%). Internal validation was performed in 8 studies (44%), 10 studies (56%) reported discrimination measures, 4 studies (22%) reported calibration measures and none performed external validation. According to PROBAST, a high risk of bias was identified in the analytic aspects in all studies. However, the existing studies had minimal bias concerns related to the study populations, inclusion and modelling of predictors, and outcome ascertainment.ConclusionsDiagnostic prediction can aid clinicians in aetiological diagnoses of viral ARIs. External validation should be performed on rigorously internally validated models with populations intended for model application.PROSPERO registration numberCRD42022308917.

Multiplex PCR and Antibiotic Use in Children with Community-Acquired Pneumonia

“…Our study highlights the need for antimicrobial stewardship strategies for children with CAP, as well as diagnostic tests to improve antibiotic prescription. It is important to have guidelines and tools that help clinicians distinguish viral from bacterial pneumonia [3] and to make appropriate treatment decisions, thereby helping to reduce unnecessary antibiotic therapy for viral infections. Active antimicrobial stewardship could be another important approach.…”

“…However, there is significant overlap, and clinical algorithms cannot clearly discern the cause of CAP [2], which leads to substantial variations in its management. Various diagnostic models have been developed to predict the viral aetiology of paediatric respiratory infections, but most have focused on specific viruses, mainly influenza, and are not yet ready for clinical application [3]. Moreover, the identification of viruses within the upper respiratory tract does not confirm their causal relationship with CAP, nor does it exclude the presence of a bacterial pathogen, given the frequent occurrence of mixed viral-bacterial infections in paediatric cases [2,4].…”