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

Biomarkers for the Discrimination of Acute Kawasaki Disease From Infections in Childhood

Funding Information: We would like to thank all the patients and their relatives as well as the treatment teams for their participation in this study. We also thank Dr. Mischa Keizer for his help in developing the MRP8/14 ELISA. We would like to thank the EUCLIDS Consortium, PERFORM Consortium, and the Genetic Determinants of Kawasaki Disease Study group (UK). Funding. This work was partially supported by the European Seventh Framework Program for Research and Technological Development (FP7) under EUCLIDS grant agreement no. 279185; from the European Union's Horizon 2020 research and innovation program under grant agreement no. 668303; by STINAFO and anonymous donor; and by Sanquin Blood Supply Product and Process Development Cellular Products Fund (PPOC 1957). Publisher Copyright: © Copyright © 2020 Zandstra, van de Geer, Tanck, van Stijn-Bringas Dimitriades, Aarts, Dietz, van Bruggen, Schweintzger, Zenz, Emonts, Zavadska, Pokorn, Usuf, Moll, Schlapbach, Carrol, Paulus, Tsolia, Fink, Yeung, Shimizu, Tremoulet, Galassini, Wright, Martinón-Torres, Herberg, Burns, Levin, Kuijpers, EUCLIDS Consortium, PERFORM Consortium and UK Kawasaki Disease Genetics Study Network. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Kawasaki disease (KD) is a vasculitis of early childhood mimicking several infectious diseases. Differentiation between KD and infectious diseases is essential as KD's most important complication—the development of coronary artery aneurysms (CAA)—can be largely avoided by timely treatment with intravenous immunoglobulins (IVIG). Currently, KD diagnosis is only based on clinical criteria. The aim of this study was to evaluate whether routine C-reactive protein (CRP) and additional inflammatory parameters myeloid-related protein 8/14 (MRP8/14 or S100A8/9) and human neutrophil-derived elastase (HNE) could distinguish KD from infectious diseases. Methods and Results: The cross-sectional study included KD patients and children with proven infections as well as febrile controls. Patients were recruited between July 2006 and December 2018 in Europe and USA. MRP8/14, CRP, and HNE were assessed for their discriminatory ability by multiple logistic regression analysis with backward selection and receiver operator characteristic (ROC) curves. In the discovery cohort, the combination of MRP8/14+CRP discriminated KD patients (n = 48) from patients with infection (n = 105), with area under the ROC curve (AUC) of 0.88. The HNE values did not improve discrimination. The first validation cohort confirmed the predictive value of MRP8/14+CRP to discriminate acute KD patients (n = 26) from those with infections (n = 150), with an AUC of 0.78. The second validation cohort of acute KD patients (n = 25) and febrile controls (n = 50) showed an AUC of 0.72, which improved to 0.84 when HNE was included. Conclusion: When used in combination, the plasma markers MRP8/14, CRP, and HNE may assist in the discrimination of KD from both proven and suspected infection.publishersversionPeer reviewe

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

Febrile illness in high-risk children: a prospective, international observational study.

To assess and describe the aetiology and management of febrile illness in children with primary or acquired immunodeficiency at high risk of serious bacterial infection, as seen in emergency departments in tertiary hospitals. Prospective data on demographics, presenting features, investigations, microbiology, management, and outcome of patients within the 'Biomarker Validation in HR patients' database in PERFORM, were analysed. Immunocompromised children (< 18 years old) presented to fifteen European hospitals in nine countries, and one Gambian hospital, with fever or suspected infection and clinical indication for blood investigations. Febrile episodes were assigned clinical phenotypes using the validated PERFORM algorithm. Logistic regression was used to assess the effect size of predictive features of proven/presumed bacterial or viral infection. A total of 599 episodes in 482 children were analysed. Seventy-eight episodes (13.0%) were definite bacterial, 67 episodes probable bacterial (11.2%), and 29 bacterial syndrome (4.8%). Fifty-five were definite viral (9.2%), 49 probable viral (8.2%), and 23 viral syndrome (3.8%). One hundred ninety were unknown bacterial or viral infections (31.7%), and 108 had inflammatory or other non-infectious causes of fever (18.1%). Predictive features of proven/presumed bacterial infection were ill appearance (OR 3.1 (95% CI 2.1-4.6)) and HIV (OR 10.4 (95% CI 2.0-54.4)). Ill appearance reduced the odds of having a proven/presumed viral infection (OR 0.5 (95% CI 0.3-0.9)). A total of 82.1% had new empirical antibiotics started on admission (N = 492); 94.3% proven/presumed bacterial (N = 164), 66.1% proven/presumed viral (N = 84), and 93.2% unknown bacterial or viral infections (N = 177). Mortality was 1.9% (N = 11) and 87.1% made full recovery (N = 522).   Conclusion: The aetiology of febrile illness in immunocompromised children is diverse. In one-third of cases, no cause for the fever will be identified. Justification for standard intravenous antibiotic treatment for every febrile immunocompromised child is debatable, yet effective. Better clinical decision-making tools and new biomarkers are needed for this population. What is Known: • Immunosuppressed children are at high risk for morbidity and mortality of serious bacterial and viral infection, but often present with fever as only clinical symptom. • Current diagnostic measures in this group are not specific to rule out bacterial infection, and positivity rates of microbiological cultures are low. What is New: • Febrile illness and infectious complications remain a significant cause of mortality and morbidity in HR children, yet management is effective. • The aetiology of febrile illness in immunocompromised children is diverse, and development of pathways for early discharge or cessation of intravenous antibiotics is debatable, and requires better clinical decision-making tools and biomarkers

Emergency medical services utilisation among febrile children attending emergency departments across Europe:an observational multicentre study

Children constitute 6–10% of all patients attending the emergency department (ED) by emergency medical services (EMS). However, discordant EMS use in children occurs in 37–61% with fever as an important risk factor. We aimed to describe EMS utilisation among febrile children attending European EDs. This study is part of an observational multicentre study assessing management and outcome in febrile children up to 18 years (MOFICHE) attending twelve EDs in eight European countries. Discordant EMS use was defined as the absence of markers of urgency including intermediate/high triage urgency, advanced diagnostics, treatment, and admission in children transferred by EMS. Multivariable logistic regression analyses were performed for the association between (1) EMS use and markers of urgency, and (2) patient characteristics and discordant EMS use after adjusting all analyses for the covariates age, gender, visiting hours, presenting symptoms, and ED setting. A total of 5464 (15%, range 0.1–42%) children attended the ED by EMS. Markers of urgency were more frequently present in the EMS group compared with the non-EMS group. Discordant EMS use occurred in 1601 children (29%, range 1–59%). Age and gender were not associated with discordant EMS use, whereas neurological symptoms were associated with less discordant EMS use (aOR 0.2, 95%CI 0.1–0.2), and attendance out of office hours was associated with more discordant EMS use (aOR 1.6, 95%CI 1.4–1.9). Settings with higher percentage of self-referrals to the ED had more discordant EMS use (p &lt; 0.05). Conclusion: There is large practice variation in EMS use in febrile children attending European EDs. Markers of urgency were more frequently present in children in the EMS group. However, discordant EMS use occurred in 29%. Further research is needed on non-medical factors influencing discordant EMS use in febrile children across Europe, so that pre-emptive strategies can be implemented. What is Known: •Children constitute around 6–10% of all patients attending the emergency department by emergency medical services. •Discordant EMS use occurs in 37–61% of all children, with fever as most common presenting symptom for discordant EMS use in children. What is New: •There is large practice variation in EMS use among febrile children across Europe with discordance EMS use occurring in 29% (range 1–59%), which was associated with attendance during out of office hours and with settings with higher percentage of self-referrals to the ED. •Future research is needed focusing on non-medical factors (socioeconomic status, parental preferences and past experience, healthcare systems, referral pathways, out of hours services provision) that influence discordant EMS use in febrile children across Europe.</p

A new scoring system derived from base excess and platelet count at presentation predicts mortality in paediatric meningococcal sepsis

Introduction: The aim of this study was to derive a novel prognostic score for mortality in paediatric meningococcal sepsis (MS) based on readily available laboratory markers.Methods: A multicentre retrospective cohort study for the consortium set and a single centre retrospective study for replication set. The consortium set were 1,073 children (age 1 week to 17.9 years) referred over a 15-year period (1996 to 2011), who had an admission diagnosis of MS, referred to paediatric intensive care units (PICUs) in six different European centres. The consortium set was split into a development set and validation set to derive the score. The replication set were 134 children with MS (age 2 weeks to 16 years) referred over a 4-year period (2007 to 2011) to PICUs via the Children's Acute Transport Service (CATS), London.Results: A total of 85/1,073 (7.9%) children in the consortium set died. A total of 16/134 (11.9%) children in the replication set died. Children dying in the consortium set had significantly lower base excess, C-reactive protein (CRP), platelet and white cell count, more deranged coagulation and higher lactate than survivors. Paediatric risk of mortality (PRISM) score, Glasgow meningococcal septicaemia prognosis score (GMSPS) and Rotterdam score were also higher. Using the consortium set, a new scoring system using base excess and platelet count at presentation, termed the BEP score, was mathematically developed and validated. BEP predicted mortality with high sensitivity and specificity scores (area under the curve (AUC) in the validation set = 0.8

Chronic pain in primary care. German figures from 1991 and 2006

<p>Abstract</p> <p>Background</p> <p>Until now only limited research has been done on the prevalence of chronic pain in primary care. The aim of this investigation was to study the health care utilisation of patients suffering from pain. How many patients visit an outpatient clinic because of the symptom of pain? These data were compared with data from a similar study in 1991, to investigate whether improvements had been achieved.</p> <p>Methods</p> <p>A total of 1201 consecutive patients visiting outpatient clinics were surveyed in six practices in the western part of Germany on randomly selected days by means of questionnaires. Topics were the point prevalence of pain and the period prevalence of chronic pain, its characteristics and its impact on daily life, as well as data on previous therapies for pain. A retrospective comparison was made with the data from a similar study with same design surveying 900 patients that took place in five practices during 1991.</p> <p>Results</p> <p>In 2006, pain was the main reason for consulting a doctor in 42.5% of all patients (1991: 50.3%). Of all respondents, 62% suffered from pain on the particular day of the consultation, and 40% reported that they had been suffering from pain for more than six months (1991: 36.4%). As many as 88.3% of patients with chronic pain reported a negative impact on their daily life due to this pain (1991: 68%), and 88.1% reported impairment of their working life because of chronic pain (1991: 59.1%).</p> <p>Conclusion</p> <p>Pain, and chronic pain in particular, is a central problem in primary care. Over the last 15 years, the number of patients suffering from chronic pain has not decreased. In nearly half of all cases, pain is still the reason for health care utilisation in outpatient clinics. Pain represents a major primary health care problem with enormous impact on public health. Improvements can only be achieved by improving the quality of health care at the primary care level.</p

A Novel Framework for Phenotyping Children With Suspected or Confirmed Infection for Future Biomarker Studies

Copyright © 2021 Nijman, Oostenbrink, Moll, Casals-Pascual, von Both, Cunnington, De, Eleftheriou, Emonts, Fink, van der Flier, de Groot, Kaforou, Kohlmaier, Kuijpers, Lim, Maconochie, Paulus, Martinon-Torres, Pokorn, Romaine, Calle, Schlapbach, Smit, Tsolia, Usuf, Wright, Yeung, Zavadska, Zenz, Levin, Herberg, Carrol and the PERFORM consortium (Personalized Risk assessment in febrile children to optimize Real-life Management across the European Union).Background: The limited diagnostic accuracy of biomarkers in children at risk of a serious bacterial infection (SBI) might be due to the imperfect reference standard of SBI. We aimed to evaluate the diagnostic performance of a new classification algorithm for biomarker discovery in children at risk of SBI. Methods: We used data from five previously published, prospective observational biomarker discovery studies, which included patients aged 0– <16 years: the Alder Hey emergency department (n = 1,120), Alder Hey pediatric intensive care unit (n = 355), Erasmus emergency department (n = 1,993), Maasstad emergency department (n = 714) and St. Mary's hospital (n = 200) cohorts. Biomarkers including procalcitonin (PCT) (4 cohorts), neutrophil gelatinase-associated lipocalin-2 (NGAL) (3 cohorts) and resistin (2 cohorts) were compared for their ability to classify patients according to current standards (dichotomous classification of SBI vs. non-SBI), vs. a proposed PERFORM classification algorithm that assign patients to one of eleven categories. These categories were based on clinical phenotype, test outcomes and C-reactive protein level and accounted for the uncertainty of final diagnosis in many febrile children. The success of the biomarkers was measured by the Area under the receiver operating Curves (AUCs) when they were used individually or in combination. Results: Using the new PERFORM classification system, patients with clinically confident bacterial diagnosis (“definite bacterial” category) had significantly higher levels of PCT, NGAL and resistin compared with those with a clinically confident viral diagnosis (“definite viral” category). Patients with diagnostic uncertainty had biomarker concentrations that varied across the spectrum. AUCs were higher for classification of “definite bacterial” vs. “definite viral” following the PERFORM algorithm than using the “SBI” vs. “non-SBI” classification; summary AUC for PCT was 0.77 (95% CI 0.72–0.82) vs. 0.70 (95% CI 0.65–0.75); for NGAL this was 0.80 (95% CI 0.69–0.91) vs. 0.70 (95% CI 0.58–0.81); for resistin this was 0.68 (95% CI 0.61–0.75) vs. 0.64 (0.58–0.69) The three biomarkers combined had summary AUC of 0.83 (0.77–0.89) for “definite bacterial” vs. “definite viral” infections and 0.71 (0.67–0.74) for “SBI” vs. “non-SBI.” Conclusion: Biomarkers of bacterial infection were strongly associated with the diagnostic categories using the PERFORM classification system in five independent cohorts. Our proposed algorithm provides a novel framework for phenotyping children with suspected or confirmed infection for future biomarker studies.publishersversionPeer reviewe