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.

Comparison of Illumina versus Nanopore 16S rRNA Gene Sequencing of the Human Nasal Microbiota.

Illumina and nanopore sequencing technologies are powerful tools that can be used to determine the bacterial composition of complex microbial communities. In this study, we compared nasal microbiota results at genus level using both Illumina and nanopore 16S rRNA gene sequencing. We also monitored the progression of nanopore sequencing in the accurate identification of species, using pure, single species cultures, and evaluated the performance of the nanopore EPI2ME 16S data analysis pipeline. Fifty-nine nasal swabs were sequenced using Illumina MiSeq and Oxford Nanopore 16S rRNA gene sequencing technologies. In addition, five pure cultures of relevant bacterial species were sequenced with the nanopore sequencing technology. The Illumina MiSeq sequence data were processed using bioinformatics modules present in the Mothur software package. Albacore and Guppy base calling, a workflow in nanopore EPI2ME (Oxford Nanopore Technologies-ONT, Oxford, UK) and an in-house developed bioinformatics script were used to analyze the nanopore data. At genus level, similar bacterial diversity profiles were found, and five main and established genera were identified by both platforms. However, probably due to mismatching of the nanopore sequence primers, the nanopore sequencing platform identified Corynebacterium in much lower abundance compared to Illumina sequencing. Further, when using default settings in the EPI2ME workflow, almost all sequence reads that seem to belong to the bacterial genus Dolosigranulum and a considerable part to the genus Haemophilus were only identified at family level. Nanopore sequencing of single species cultures demonstrated at least 88% accurate identification of the species at genus and species level for 4/5 strains tested, including improvements in accurate sequence read identification when the basecaller Guppy and Albacore, and when flowcell versions R9.4 (Oxford Nanopore Technologies-ONT, Oxford, UK) and R9.2 (Oxford Nanopore Technologies-ONT, Oxford, UK) were compared. In conclusion, the current study shows that the nanopore sequencing platform is comparable with the Illumina platform in detection bacterial genera of the nasal microbiota, but the nanopore platform does have problems in detecting bacteria within the genus Corynebacterium. Although advances are being made, thorough validation of the nanopore platform is still recommendable.

Expert panel diagnosis demonstrated high reproducibility as reference standard in infectious diseases.

OBJECTIVE: If a gold standard is lacking in a diagnostic test accuracy study, expert diagnosis is frequently used as reference standard. However, interobserver and intraobserver agreements are imperfect. The aim of this study was to quantify the reproducibility of a panel diagnosis for pediatric infectious diseases. STUDY DESIGN AND SETTING: Pediatricians from six countries adjudicated a diagnosis (i.e., bacterial infection, viral infection, or indeterminate) for febrile children. Diagnosis was reached when the majority of panel members came to the same diagnosis, leaving others inconclusive. We evaluated intraobserver and intrapanel agreement with 6 weeks and 3 years' time intervals. We calculated the proportion of inconclusive diagnosis for a three-, five-, and seven-expert panel. RESULTS: For both time intervals (i.e., 6 weeks and 3 years), intrapanel agreement was higher (kappa 0.88, 95%CI: 0.81-0.94 and 0.80, 95%CI: NA) compared to intraobserver agreement (kappa 0.77, 95%CI: 0.71-0.83 and 0.65, 95%CI: 0.52-0.78). After expanding the three-expert panel to five or seven experts, the proportion of inconclusive diagnoses (11%) remained the same. CONCLUSION: A panel consisting of three experts provides more reproducible diagnoses than an individual expert in children with lower respiratory tract infection or fever without source. Increasing the size of a panel beyond three experts has no major advantage for diagnosis reproducibility.

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.

A host-protein based assay to differentiate between bacterial and viral infections in preschool children (OPPORTUNITY): a double-blind, multicentre, validation study.

BACKGROUND: A physician is frequently unable to distinguish bacterial from viral infections. ImmunoXpert is a novel assay combining three proteins: tumour necrosis factor-related apoptosis-inducing ligand (TRAIL), interferon gamma induced protein-10 (IP-10), and C-reactive protein (CRP). We aimed to externally validate the diagnostic accuracy of this assay in differentiating between bacterial and viral infections and to compare this test with commonly used biomarkers. METHODS: In this prospective, double-blind, international, multicentre study, we recruited children aged 2-60 months with lower respiratory tract infection or clinical presentation of fever without source at four hospitals in the Netherlands and two hospitals in Israel. A panel of three experienced paediatricians adjudicated a reference standard diagnosis for all patients (ie, bacterial or viral infection) using all available clinical and laboratory information, including a 28-day follow-up assessment. The panel was masked to the assay results. We identified majority diagnosis when two of three panel members agreed on a diagnosis and unanimous diagnosis when all three panel members agreed on the diagnosis. We calculated the diagnostic performance (ie, sensitivity, specificity, positive predictive value, and negative predictive value) of the index test in differentiating between bacterial (index test positive) and viral (index test negative) infection by comparing the test classification with the reference standard outcome. FINDINGS: Between Oct 16, 2013 and March 1, 2015, we recruited 777 children, of whom 577 (mean age 21 months, 56% male) were assessed. The majority of the panel diagnosed 71 cases as bacterial infections and 435 as viral infections. In another 71 patients there was an inconclusive panel diagnosis. The assay distinguished bacterial from viral infections with a sensitivity of 86·7% (95% CI 75·8-93·1), a specificity of 91·1% (87·9-93·6), a positive predictive value of 60·5% (49·9-70·1), and a negative predictive value of 97·8% (95·6-98·9). In the more clear cases with unanimous panel diagnosis (n=354), sensitivity was 87·8% (74·5-94·7), specificity 93·0% (89·6-95·3), positive predictive value 62·1% (49·2-73·4), and negative predictive value 98·3% (96·1-99·3). INTERPRETATION: This external validation study shows the diagnostic value of a three-host protein-based assay to differentiate between bacterial and viral infections in children with lower respiratory tract infection or fever without source. This diagnostic based on CRP, TRAIL, and IP-10 has the potential to reduce antibiotic misuse in young children. FUNDING: MeMed Diagnostics.

[Increased risk of type II diabetes mellitus and cardiovascular disease after gestational diabetes mellitus: a systematic review]. / Verhoogd risico op diabetes mellitus type 2 en hart- en vaatziekten na diabetes gravidarum: een systematische review.

OBJECTIVE: To determine the long-term risk of developing type II diabetes (T2D) and cardiovascular disease (CVD) for women with a history of gestational diabetes mellitus. DESIGN: Systematic review and meta-analysis. METHOD: Two search strategies were used in PubMed and Embase to determine the long-term risks of developing T2D and CVD after a pregnancy complicated by gestational diabetes mellitus. After critical appraisal of the papers found, 11 papers were included, involving a total of 328,423 patients. Absolute and relative risks (RRs) were calculated. RESULTS: Eight studies (n=276,829) reported on the long-term risk of T2D and 4 (n=141,048) on the long-term risk of CVD. Follow-up ranged from 3.5 to 11.5 years for T2D and from 1.2 to 74.0 years for CVD. Women with gestational diabetes had a risk of T2D varying between 9.5% and 37.0% and a risk of CVD of between 0.28% and 15.5%. Women with gestational diabetes were at increased risk of T2D (weighted RR: 13.2; 95% CI: 8.5-20.7) and CVD (weighted RR: 2.0; 95% CI: 1.1-3.7) compared to women without gestational diabetes. CONCLUSION: Women with prior gestational diabetes mellitus have a significantly increased risk of developing T2D and CVD. It is very important that gestational diabetes is recognised as a cardiovascular risk factor in daily practice. It would be desirable to screen this group of women for the presence of hyperglycaemia and other cardiovascular risk factors. Further research is required to be able to specify the long-term risk of T2D and CVD and to demonstrate whether such screening is cost-effective.