Genetic clustering and parentage analysis of Western Balkan grapevines (Vitis vinifera L.)

A total of 90 grapevine samples collected in five countries of the Western Balkan region were evaluated for trueness-to-type and kinship relations based on comparative analysis with 1,130 grapevine genotypes held at the INRA "Domaine de Vassal" French Grape Germplasm Repository, using 14 microsatellite markers. In the context of the comparative analysis, twenty-four synonyms/counterparts and the putative parents for twelve Balkan accessions were identified. We discovered five pairs of homonyms, subsequently confirming the identity or parentage of three of them. Some of the examined accessions were identified either on the basis of the genotypes found in the literature, or through parentage relationships revealed in this study. For the remaining fifty accessions we were unable to establish either their pedigree or to identify them on the basis of SSR profiles available elsewhere. Finally, the Balkan genotypes that were not well classified by synonymy or parentage analysis were further studied with a Principal Coordinate Analysis to reveal genetic clustering within larger datasets of genotypes. The graphical display of the individual and group distances showed that about forty accessions (85 %) are structured within a group of Balkan and Eastern Europe genotypes and only a minor proportion resulted in admixed population assignment

Guideline adherence in febrile children below 3 months visiting European Emergency Departments: an observational multicenter study

Febrile children below 3 months have a higher risk of serious bacterial infections, which often leads to extensive diagnostics and treatment. There is practice variation in management due to differences in guidelines and their usage and adherence. We aimed to assess whether management in febrile children below 3 months attending European Emergency Departments (EDs) was according to the guidelines for fever. This study is part of the MOFICHE study, which is an observational multicenter study including routine data of febrile children (0-18 years) attending twelve EDs in eight European countries. In febrile children below 3 months (excluding bronchiolitis), we analyzed actual management compared to the guidelines for fever. Ten EDs applied the (adapted) NICE guideline, and two EDs applied local guidelines. Management included diagnostic tests, antibiotic treatment, and admission. We included 913 children with a median age of 1.7 months (IQR 1.0-2.3). Management per ED varied as follows: use of diagnostic tests 14-83%, antibiotic treatment 23-54%, admission 34-86%. Adherence to the guideline was 43% (374/868) for blood cultures, 29% (144/491) for lumbar punctures, 55% (270/492) for antibiotic prescriptions, and 67% (573/859) for admission. Full adherence to these four management components occurred in 15% (132/868, range 0-38%), partial adherence occurred in 56% (484/868, range 35-77%). CONCLUSION: There is large practice variation in management. The guideline adherence was limited, but highest for admission which implies a cautious approach. Future studies should focus on guideline revision including new biomarkers in order to optimize management in young febrile children. WHAT IS KNOWN: • Febrile children below 3 months have a higher risk of serious bacterial infections, which often leads to extensive diagnostics and treatment. • There is practice variation in management of young febrile children due to differences in guidelines and their usage and adherence. WHAT IS NEW: • Full guideline adherence is limited, whereas partial guideline adherence is moderate in febrile children below 3 months across Europe. • Guideline revision including new biomarkers is needed to improve management in young febrile children

AWaRe-ness of antimicrobial stewardship challenges in pediatric emergency care: results from the PERFORM study assessing consistency and appropriateness of antibiotic prescribing across Europe

Objectives Optimization of antimicrobial stewardship (AMS) is key to tackling antimicrobial resistance (AMR), which is exacerbated by over-prescription of antibiotics in pediatric Emergency Departments (EDs). We described patterns of empiric antibiotic use in European EDs, and characterized appropriateness and consistency of prescribing. Methods Between August 2016 and December 2019 febrile children attending the ED in nine European countries with suspected infection were recruited into the PERFORM (Personalised Risk assessment in Febrile illness to Optimise Real-life Management) study. Empiric systemic antibiotic use was determined in view of assigned final ‘bacterial’ or ‘viral’ phenotype. Antibiotics were classified according to WHO AWaRe. Results Of 2130 febrile episodes (excluding children with non-bacterial/non-viral phenotypes), 1549 (72.7%) were assigned a ‘bacterial’ and 581 (27.3%) a ‘viral’ phenotype. A total of 1318/1549 (85.1%) episodes with a ‘bacterial’ and 269/581 (46.3%) with a ‘viral’ phenotype received empiric systemic antibiotics (first two days of admission). Of those, the majority (87.8% in ‘bacterial’ and 87.0% in ‘viral’ group) received parenteral antibiotics. The top three antibiotics prescribed were third-generation cephalosporins, penicillins and penicillin/beta-lactamase inhibitor combinations. Of those treated with empiric systemic antibiotics in the ‘viral’ group 216/269 (80.3%) received ≥ one Watch antibiotic. Conclusions Differentiating bacterial from viral etiology in febrile illness on initial ED presentation remains challenging, resulting in a substantial over-prescription of antibiotics. A significant proportion of patients with a ‘viral’ phenotype received systemic antibiotics, predominantly classified as WHO Watch. Rapid and accurate point-of-care tests in the ED differentiating between bacterial and viral etiology, could significantly improve AMS

A multi-platform approach to identify a blood-based host protein signature for distinguishing between bacterial and viral infections in febrile children (PERFORM): a multi-cohort machine learning study

BACKGROUND: Differentiating between self-resolving viral infections and bacterial infections in children who are febrile is a common challenge, causing difficulties in identifying which individuals require antibiotics. Studying the host response to infection can provide useful insights and can lead to the identification of biomarkers of infection with diagnostic potential. This study aimed to identify host protein biomarkers for future development into an accurate, rapid point-of-care test that can distinguish between bacterial and viral infections, by recruiting children presenting to health-care settings with fever or a history of fever in the previous 72 h. METHODS: In this multi-cohort machine learning study, patient data were taken from EUCLIDS, the Swiss Pediatric Sepsis study, the GENDRES study, and the PERFORM study, which were all based in Europe. We generated three high-dimensional proteomic datasets (SomaScan and two via liquid chromatography tandem mass spectrometry, referred to as MS-A and MS-B) using targeted and untargeted platforms (SomaScan and liquid chromatography mass spectrometry). Protein biomarkers were then shortlisted using differential abundance analysis, feature selection using forward selection-partial least squares (FS-PLS; 100 iterations), along with a literature search. Identified proteins were tested with Luminex and ELISA and iterative FS-PLS was done again (25 iterations) on the Luminex results alone, and the Luminex and ELISA results together. A sparse protein signature for distinguishing between bacterial and viral infections was identified from the selected proteins. The performance of this signature was finally tested using Luminex assays and by calculating disease risk scores. FINDINGS: 376 children provided serum or plasma samples for use in the discovery of protein biomarkers. 79 serum samples were collected for the generation of the SomaScan dataset, 147 plasma samples for the MS-A dataset, and 150 plasma samples for the MS-B dataset. Differential abundance analysis, and the first round of feature selection using FS-PLS identified 35 protein biomarker candidates, of which 13 had commercial ELISA or Luminex tests available. 16 proteins with ELISA or Luminex tests available were identified by literature review. Further evaluation via Luminex and ELISA and the second round of feature selection using FS-PLS revealed a six-protein signature: three of the included proteins are elevated in bacterial infections (SELE, NGAL, and IFN-γ), and three are elevated in viral infections (IL18, NCAM1, and LG3BP). Performance testing of the signature using Luminex assays revealed area under the receiver operating characteristic curve values between 89·4% and 93·6%. INTERPRETATION: This study has led to the identification of a protein signature that could be ultimately developed into a blood-based point-of-care diagnostic test for rapidly diagnosing bacterial and viral infections in febrile children. Such a test has the potential to greatly improve care of children who are febrile, ensuring that the correct individuals receive antibiotics. FUNDING: European Union's Horizon 2020 research and innovation programme, the European Union's Seventh Framework Programme (EUCLIDS), Imperial Biomedical Research Centre of the National Institute for Health Research, the Wellcome Trust and Medical Research Foundation, Instituto de Salud Carlos III, Consorcio Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Grupos de Refeencia Competitiva, Swiss State Secretariat for Education, Research and Innovation

Variation in hospital admission in febrile children evaluated at the Emergency Department (ED) in Europe : PERFORM, a multicentre prospective observational study

Funding Information: This project was funded by the European Union?s Horizon 2020 research and innovation programme to ML (Grant No. 668303), the NIHR Newcastle Biomedical Research Centre at Newcastle Hospitals NHS foundation trust to ME, and the National Institute for Health Research to RGN (CL-2018-21-007). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2021 Borensztajn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.OBJECTIVES: Hospitalisation is frequently used as a marker of disease severity in observational Emergency Department (ED) studies. The comparison of ED admission rates is complex in potentially being influenced by the characteristics of the region, ED, physician and patient. We aimed to study variation in ED admission rates of febrile children, to assess whether variation could be explained by disease severity and to identify patient groups with large variation, in order to use this to reduce unnecessary health care utilization that is often due to practice variation. DESIGN: MOFICHE (Management and Outcome of Fever in children in Europe, part of the PERFORM study, www.perform2020.org), is a prospective cohort study using routinely collected data on febrile children regarding patient characteristics (age, referral, vital signs and clinical alarming signs), diagnostic tests, therapy, diagnosis and hospital admission. SETTING AND PARTICIPANTS: Data were collected on febrile children aged 0-18 years presenting to 12 European EDs (2017-2018). MAIN OUTCOME MEASURES: We compared admission rates between EDs by using standardised admission rates after adjusting for patient characteristics and initiated tests at the ED, where standardised rates >1 demonstrate higher admission rates than expected and rates <1 indicate lower rates than expected based on the ED patient population. RESULTS: We included 38,120 children. Of those, 9.695 (25.4%) were admitted to a general ward (range EDs 5.1-54.5%). Adjusted standardised admission rates ranged between 0.6 and 1.5. The largest variation was seen in short admission rates (0.1-5.0), PICU admission rates (0.2-2.2), upper respiratory tract infections (0.4-1.7) and fever without focus (0.5-2.7). Variation was small in sepsis/meningitis (0.9-1.1). CONCLUSIONS: Large variation exists in admission rates of febrile children evaluated at European EDs, however, this variation is largely reduced after correcting for patient characteristics and therefore overall admission rates seem to adequately reflect disease severity or a potential for a severe disease course. However, for certain patient groups variation remains high even after adjusting for patient characteristics.publishersversionPeer reviewe

A NICE combination for predicting hospitalisation at the Emergency Department : a European multicentre observational study of febrile children

Funding Information: DB, UB, EC, JD, ME, MF, NH, BK, FMT, HM, EL, ML, MP, IRC, FS, MT, CV, SY, DZ and WZ report grants from the European Union. Horizon 2020 research and innovation programme during the study conduct. FS reports a grant from the Slovenian Research Agency outside the submitted work. Funding Information: MP reports a grant from Pfizer and financial support from Pfizer and Sanofi outside the submitted work. MF reports a grant from CSL Behring outside the submitted work. RN reports a grant from the National Institute for Health Research during the study conduct. ME reports financial support from the National Institute for Health Research Biomedical Research Centre based at Newcastle Hospitals NHS Foundation Trust and Newcastle University ng the study conduct. MT is a member of the Advisory Board of MSD and Pfizer, a member of the National Committee on Immunization Practices and a member of the national Scientific Advisory Group for the management of the pandemic. Publisher Copyright: © 2021 The Author(s)Background: Prolonged Emergency Department (ED) stay causes crowding and negatively impacts quality of care. We developed and validated a prediction model for early identification of febrile children with a high risk of hospitalisation in order to improve ED flow. Methods: The MOFICHE study prospectively collected data on febrile children (0–18 years) presenting to 12 European EDs. A prediction models was constructed using multivariable logistic regression and included patient characteristics available at triage. We determined the discriminative values of the model by calculating the area under the receiver operating curve (AUC). Findings: Of 38,424 paediatric encounters, 9,735 children were admitted to the ward and 157 to the PICU. The prediction model, combining patient characteristics and NICE alarming, yielded an AUC of 0.84 (95%CI 0.83-0.84). The model performed well for a rule-in threshold of 75% (specificity 99.0% (95%CI 98.9-99.1%, positive likelihood ratio 15.1 (95%CI 13.4-17.1), positive predictive value 0.84 (95%CI 0.82-0.86)) and a rule-out threshold of 7.5% (sensitivity 95.4% (95%CI 95.0-95.8), negative likelihood ratio 0.15 (95%CI 0.14-0.16), negative predictive value 0.95 (95%CI 0.95-9.96)). Validation in a separate dataset showed an excellent AUC of 0.91 (95%CI 0.90- 0.93). The model performed well for identifying children needing PICU admission (AUC 0.95, 95%CI 0.93-0.97). A digital calculator was developed to facilitate clinical use. Interpretation: Patient characteristics and NICE alarming signs available at triage can be used to identify febrile children at high risk for hospitalisation and can be used to improve ED flow. Funding: European Union, NIHR, NHS.publishersversionPeer reviewe

Diagnosis of multisystem inflammatory syndrome in children by a whole-blood transcriptional signature

BACKGROUND: To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease (KD), bacterial infections, and viral infections. METHODS: Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020 and April 2021 were prospectively recruited. Whole-blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C (n = 38) to those from children with KD (n = 136), definite bacterial (DB; n = 188) and viral infections (DV; n = 138). Genes significantly differentially expressed (SDE) between MIS-C and comparator groups were identified. Feature selection was used to identify genes that optimally distinguish MIS-C from other diseases, which were subsequently translated into RT-qPCR assays and evaluated in an independent validation set comprising MIS-C (n = 37), KD (n = 19), DB (n = 56), DV (n = 43), and COVID-19 (n = 39). RESULTS: In the discovery set, 5696 genes were SDE between MIS-C and combined comparator disease groups. Five genes were identified as potential MIS-C diagnostic biomarkers (HSPBAP1, VPS37C, TGFB1, MX2, and TRBV11-2), achieving an AUC of 96.8% (95% CI: 94.6%-98.9%) in the discovery set, and were translated into RT-qPCR assays. The RT-qPCR 5-gene signature achieved an AUC of 93.2% (95% CI: 88.3%-97.7%) in the independent validation set when distinguishing MIS-C from KD, DB, and DV. CONCLUSIONS: MIS-C can be distinguished from KD, DB, and DV groups using a 5-gene blood RNA expression signature. The small number of genes in the signature and good performance in both discovery and validation sets should enable the development of a diagnostic test for MIS-C