The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections.

BACKGROUND: The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI. RESULTS: Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the 'bacterial' patients and 82% of the 'viral' patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus). CONCLUSIONS: We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections.

Antibiotic misuse in respiratory tract infections in children and adults-a prospective, multicentre study (TAILORED Treatment).

Respiratory tract infections (RTI) are more commonly caused by viral pathogens in children than in adults. Surprisingly, little is known about antibiotic use in children as compared to adults with RTI. This prospective study aimed to determine antibiotic misuse in children and adults with RTI, using an expert panel reference standard, in order to prioritise the target age population for antibiotic stewardship interventions. We recruited children and adults who presented at the emergency department or were hospitalised with clinical presentation of RTI in The Netherlands and Israel. A panel of three experienced physicians adjudicated a reference standard diagnosis (i.e. bacterial or viral infection) for all the patients using all available clinical and laboratory information, including a 28-day follow-up assessment. The cohort included 284 children and 232 adults with RTI (median age, 1.3 years and 64.5 years, respectively). The proportion of viral infections was larger in children than in adults (209(74%) versus 89(38%), p < 0.001). In case of viral RTI, antibiotics were prescribed (i.e. overuse) less frequently in children than in adults (77/209 (37%) versus 74/89 (83%), p < 0.001). One (1%) child and three (2%) adults with bacterial infection were not treated with antibiotics (i.e. underuse); all were mild cases. This international, prospective study confirms major antibiotic overuse in patients with RTI. Viral infection is more common in children, but antibiotic overuse is more frequent in adults with viral RTI. Together, these findings support the need for effective interventions to decrease antibiotic overuse in RTI patients of all ages.

Antibiotic Overuse in Children with Respiratory Syncytial Virus Lower Respiratory Tract Infection.

BACKGROUND: Respiratory syncytial virus (RSV) is the most common cause of lower respiratory tract infections (LRTI) during the first year of life. Antibiotic treatment is recommended in cases suspected of bacterial coinfection. The aim of this prospective study was to estimate the incidence of bacterial coinfections and the amount of antibiotic overuse in children infected with RSV using expert panel diagnosis. METHODS: Children 1 month of age and over with LRTI or fever without source were prospectively recruited in hospitals in the Netherlands and Israel. Children with confirmed RSV infection by Polymerase Chain Reaction (PCR) on nasal swabs were evaluated by an expert panel as reference standard diagnosis. Three experienced pediatricians distinguished bacterial coinfection from simple viral infection using all available clinical information, including all microbiologic evaluations and a 28-day follow-up evaluation. RESULTS: A total of 188 children (24% of all 784 recruited patients) were positive for RSV. From these, 92 (49%) were treated with antibiotics. All 27 children (29%) with bacterial coinfection were treated with antibiotics. Fifty-seven patients (62%) were treated with antibiotics without a diagnosis of bacterial coinfection. In 8 of the 92 (9%), the expert panel could not distinguish simple viral infection from bacterial coinfection. CONCLUSION: This is the first prospective international multicenter RSV study using an expert panel as reference standard to identify children with and without bacterial coinfection. All cases of bacterial coinfections are treated, whereas as many as one-third of all children with RSV LRTI are treated unnecessarily with antibiotics.