Objective To assess the value of the Emergency Department-Pediatric Early Warning Score (ED-PEWS) for triage of children with comorbidity.Design Secondary analysis of a prospective cohort.Setting... Show moreObjective To assess the value of the Emergency Department-Pediatric Early Warning Score (ED-PEWS) for triage of children with comorbidity.Design Secondary analysis of a prospective cohort.Setting and patients 53 829 consecutive ED visits of children <16 years in three European hospitals (Netherlands, UK and Austria) participating in the TrIAGE (Triage Improvements Across General Emergency departments) project in different periods (2012-2015).Intervention ED-PEWS, a score consisting of age and six physiological parameters.Main outcome measure A three-category reference standard as proxy for true patient urgency. We assessed discrimination and calibration of the ED-PEWS for children with comorbidity (complex and non-complex) and without comorbidity. In addition, we evaluated the value of adding the ED-PEWS to the routinely used Manchester Triage System (MTS).Results 5053 (9%) children had underlying non-complex morbidity and 5537 (10%) had complex comorbidity. The c-statistic for identification of high-urgency patients was 0.86 (95% prediction interval 0.84-0.88) for children without comorbidity, 0.87 (0.82-0.92) for non-complex and 0.86 (0.84-0.88) for complex comorbidity. For high and intermediate urgency, the c-statistic was 0.63 (0.62-0.63), 0.63 (0.61-0.65) and 0.63 (0.55-0.73) respectively. Sensitivity was slightly higher for children with comorbidity (0.73-0.75 vs 0.70) at the cost of a lower specificity (0.86-0.87 vs 0.92). Calibration was largely similar. Adding the ED-PEWS to the MTS for children with comorbidity improved performance, except in the setting with few high-urgency patients.Conclusions The ED-PEWS has a similar performance in children with and without comorbidity. Adding the ED-PEWS to the MTS for children with comorbidity improves triage, except in the setting with few high-urgency patients. Show less
Background To develop a clinical prediction model to identify children at risk for revisits with serious illness to the emergency department. Methods and findings A secondary analysis of a... Show moreBackground To develop a clinical prediction model to identify children at risk for revisits with serious illness to the emergency department. Methods and findings A secondary analysis of a prospective multicentre observational study in five European EDs (the TRIAGE study), including consecutive children aged <16 years who were discharged following their initial ED visit ('index' visit), in 2012-2015. Standardised data on patient characteristics, Manchester Triage System urgency classification, vital signs, clinical interventions and procedures were collected. The outcome measure was serious illness defined as hospital admission or PICU admission or death in ED after an unplanned revisit within 7 days of the index visit. Prediction models were developed using multivariable logistic regression using characteristics of the index visit to predict the likelihood of a revisit with a serious illness. The clinical model included day and time of presentation, season, age, gender, presenting problem, triage urgency, and vital signs. An extended model added laboratory investigations, imaging, and intravenous medications. Cross validation between the five sites was performed, and discrimination and calibration were assessed using random effects models. A digital calculator was constructed for clinical implementation. 7,891 children out of 98,561 children had a revisit to the ED (8.0%), of whom 1,026 children (1.0%) returned to the ED with a serious illness. Rates of revisits with serious illness varied between the hospitals (range 0.7-2.2%). The clinical model had a summary Area under the operating curve (AUC) of 0.70 (95% CI 0.65-0.74) and summary calibration slope of 0.83 (95% CI 0.67-0.99). 4,433 children (5%) had a risk of > = 3%, which was useful for ruling in a revisit with serious illness, with positive likelihood ratio 4.41 (95% CI 3.87-5.01) and specificity 0.96 (95% CI 0.95-0.96). 37,546 (39%) had a risk <0.5%, which was useful for ruling out a revisit with serious illness (negative likelihood ratio 0.30 (95% CI 0.25-0.35), sensitivity 0.88 (95% CI 0.86-0.90)). The extended model had an improved summary AUC of 0.71 (95% CI 0.68-0.75) and summary calibration slope of 0.84 (95% CI 0.71-0.97). As study limitations, variables on ethnicity and social deprivation could not be included, and only return visits to the original hospital and not to those of surrounding hospitals were recorded. Conclusion We developed a prediction model and a digital calculator which can aid physicians identifying those children at highest and lowest risks for developing a serious illness after initial discharge from the ED, allowing for more targeted safety netting advice and follow-up. Show less
Objective Our aim was to describe variability in resource use and hospitalization in children presenting with shortness of breath to different European Emergency Departments (EDs) and to explore... Show moreObjective Our aim was to describe variability in resource use and hospitalization in children presenting with shortness of breath to different European Emergency Departments (EDs) and to explore possible explanations for variability.Design The TrIAGE project, a prospective observational study based on electronic health record data.Patients and setting Consecutive paediatric emergency department visits for shortness of breath in five European hospitals in four countries (Austria, Netherlands, Portugal, United Kingdom) during a study period of 9-36 months (2012-2014).Main outcome measures We assessed diversity between EDs regarding resource use (diagnostic tests, therapy) and hospital admission using multivariable logistic regression analyses adjusting for potential confounding variables.Results In total, 13,552 children were included. Of those, 7,379 were categorized as immediate/very urgent, ranging from 13-80% in the participating hospitals. Laboratory tests and X-rays were performed in 8-33% of the cases and 21-61% was treated with inhalation medication. Admission rates varied between 8-47% and PICU admission rates varied between 0.1-9%. Patient characteristics and markers of disease severity (age, sex, comorbidity, urgency, vital signs) could explain part of the observed variability in resource use and hospitalization. However, after adjusting for these characteristics, we still observed substantial variability between settings.Conclusion European EDs differ substantially regarding the resource use and hospitalization in children with shortness of breath, even when adjusting for patient characteristics. Possible explanations for this variability might be unmeasured patient characteristics such as underlying disease, differences in guideline use and adherence or different local practice patterns. Show less
eTRANSAFE is a research project funded within the Innovative Medicines Initiative (IMI), which aims at developing integrated databases and computational tools (the eTRANSAFE ToxHub) that support... Show moreeTRANSAFE is a research project funded within the Innovative Medicines Initiative (IMI), which aims at developing integrated databases and computational tools (the eTRANSAFE ToxHub) that support the translational safety assessment of new drugs by using legacy data provided by the pharmaceutical companies that participate in the project. The project objectives include the development of databases containing preclinical and clinical data, computational systems for translational analysis including tools for data query, analysis and visualization, as well as computational models to explain and predict drug safety events. Show less
Background Paediatric Early Warning Scores (PEWSs) are being used increasingly in hospital wards to identify children at risk of clinical deterioration, but few scores exist that were designed for... Show moreBackground Paediatric Early Warning Scores (PEWSs) are being used increasingly in hospital wards to identify children at risk of clinical deterioration, but few scores exist that were designed for use in emergency care settings. To improve the prioritisation of children in the emergency department (ED), we developed and validated an ED-PEWS.Methods The TrIAGE project is a prospective European observational study based on electronic health record data collected between Jan 1, 2012, and Nov 1, 2015, from five diverse EDs in four European countries (Netherlands, the UK, Austria, and Portugal). This study included data from all consecutive ED visits of children under age 16 years. The main outcome measure was a three-category reference standard (high, intermediate, low urgency) that was developed as part of the TrIAGE project as a proxy for true patient urgency. The ED-PEWS was developed based on an ordinal logistic regression model, with cross-validation by setting. After completing the study, we fully externally validated the ED-PEWS in an independent cohort of febrile children from a different ED (Greece).Findings Of 119 209 children, 2007 (1.7%) were of high urgency and 29 127 (24.4%) of intermediate urgency, according to our reference standard. We developed an ED-PEWS consisting of age and the predictors heart rate, respiratory rate, oxygen saturation, consciousness, capillary refill time, and work of breathing. The ED-PEWS showed a cross-validated c-statistic of 0.86 (95% prediction interval 0.82-0.90) for high-urgency patients and 0.67 (0.61-0.73) for highurgency or intermediate-urgency patients. A cutoff of score of at least 15 was useful for identifying high-urgency patients with a specificity of 0.90 (95% CI 0.87-0.92) while a cutoff score of less than 6 was useful for identifying low-urgency patients with a sensitivity of 0.83 (0.81-0.85).Interpretation The proposed ED-PEWS can assist in identifying high-urgency and low-urgency patients in the ED, and improves prioritisation compared with existing PEWSs. Show less
Wilkinson, M.D.; Dumontier, M.; Aalbersberg, I.J.; Appleton, G.; Axton, M.; Baak, A.; ... ; Mons, B. 2019
Collaborative efforts of physicians and basic scientists are often necessary in the investigation of complex disorders. Difficulties can arise, however, when large amounts of information need to... Show moreCollaborative efforts of physicians and basic scientists are often necessary in the investigation of complex disorders. Difficulties can arise, however, when large amounts of information need to reviewed. Advanced information retrieval can be beneficial in combining and reviewing data obtained from the various scientific fields. In this paper, a team of investigators with varying backgrounds has applied advanced information retrieval methods, in the form of text mining and entity relationship tools, to review the current literature, with the intention to generate new insights into the molecular mechanisms underlying a complex disorder. As an example of such a disorder the Complex Regional Pain Syndrome (CRPS) was chosen. CRPS is a painful and debilitating syndrome with a complex etiology that is still unraveled for a considerable part, resulting in suboptimal diagnosis and treatment.\nA text mining based approach combined with a simple network analysis identified Nuclear Factor kappa B (NFkappaB) as a possible central mediator in both the initiation and progression of CRPS.\nThe result shows the added value of a multidisciplinary approach combined with information retrieval in hypothesis discovery in biomedical research. The new hypothesis, which was derived in silico, provides a framework for further mechanistic studies into the underlying molecular mechanisms of CRPS and requires evaluation in clinical and epidemiological studies. Show less
