ObjectiveTo assess and compare the performance of triage systems for identifying high and low-urgency patients in the emergency department (ED).DesignSystematic review and meta-analysis.Data sourcesEMBASE, Medline OvidSP, Cochrane central, Web of science and CINAHL databases from 1980 to 2016 with the final update in December 2018.Eligibility criteriaStudies that evaluated an emergency medical triage system, assessed validity using any reference standard as proxy for true patient urgency and were written in English. Studies conducted in low(er) income countries, based on case scenarios or involving less than 100 patients were excluded.Review methodsReviewers identified studies, extracted data and assessed the quality of the evidence independently and in duplicate. The Quality Assessment of studies of Diagnostic Accuracy included in Systematic Reviews -2 checklist was used to assess risk of bias. Raw data were extracted to create 2×2 tables and calculate sensitivity and specificity. ED patient volume and casemix severity of illness were investigated as determinants of triage systems’ performance.ResultsSixty-six eligible studies evaluated 33 different triage systems. Comparisons were restricted to the three triage systems that had at least multiple evaluations using the same reference standard (Canadian Triage and Acuity Scale, Emergency Severity Index and Manchester Triage System). Overall, validity of each triage system to identify high and low-urgency patients was moderate to good, but performance was highly variable. In a subgroup analysis, no clear association was found between ED patient volume or casemix severity of illness and triage systems’ performance.ConclusionsEstablished triage systems show a reasonable validity for the triage of patients at the ED, but performance varies considerably. Important research questions that remain are what determinants influence triage systems’ performance and how the performance of existing triage systems can be improved.

The coronavirus disease 2019 pandemic has enormous impact on society and healthcare. Countries imposed lockdowns, which were followed by a reduction in care utilization. The aims of this study were to quantify the effects of lockdown on pediatric care in the Netherlands, to elucidate the cause of the observed reduction in pediatric emergency department (ED) visits and hospital admissions, and to summarize the literature regarding the effects of lockdown on pediatric care worldwide. ED visits and hospital admission data of 8 general hospitals in the Netherlands between January 2016 and June 2020 were summarized per diagnosis group (communicable infections, noncommunicable infections, (probable) infection-related, and noninfectious). The effects of lockdown were quantified with a linear mixed effects model. A literature review regarding the effect of lockdowns on pediatric clinical care was performed. In total, 126,198 ED visits and 47,648 admissions were registered in the study period. The estimated reduction in general pediatric care was 59% and 56% for ED visits and admissions, respectively. The largest reduction was observed for communicable infections (ED visits: 76%; admissions: 77%), whereas the reduction in noninfectious diagnoses was smaller (ED visits 36%; admissions: 37%). Similar reductions were reported worldwide, with decreases of 30–89% for ED visits and 19–73% for admissions.Conclusion: Pediatric ED utilization and hospitalization during lockdown were decreased in the Netherlands and other countries, which can largely be attributed to a decrease in communicable infectious diseases. Care utilization for other conditions was decreased as well, which may indicate that care avoidance during a pandemic is significant. What is Known:• The COVID-19 pandemic had enormous impact on society.• Countries imposed lockdowns to curb transmission rates, which were followed by a reduction in care utilization worldwide. What is New:• The Dutch lockdown caused a significant decrease in pediatric ED utilization and hospitalization, especially in ED visits and hospital admissions because of infections that were not caused by SARS-CoV-2.• Care utilization for noninfectious diagnoses was decreased as well, which may indicate that pediatric care avoidance during a pandemic is significant.

Objective To derive, cross validate, and externally validate a clinical prediction model that assesses the risks of different serious bacterial infections in children with fever at the emergency department.Design Prospective observational diagnostic study.Setting Three paediatric emergency care units: two in the Netherlands and one in the United Kingdom.Participants Children with fever, aged 1 month to 15 years, at three paediatric emergency care units: Rotterdam (n=1750) and the Hague (n=967), the Netherlands, and Coventry (n=487), United Kingdom. A prediction model was constructed using multivariable polytomous logistic regression analysis and included the predefined predictor variables age, duration of fever, tachycardia, temperature, tachypnoea, ill appearance, chest wall retractions, prolonged capillary refill time (>3 seconds), oxygen saturation <94%, and C reactive protein.Main outcome measures Pneumonia, other serious bacterial infections (SBIs, including septicaemia/meningitis, urinary tract infections, and others), and no SBIs.Results Oxygen saturation <94% and presence of tachypnoea were important predictors of pneumonia. A raised C reactive protein level predicted the presence of both pneumonia and other SBIs, whereas chest wall retractions and oxygen saturation <94% were useful to rule out the presence of other SBIs. Discriminative ability (C statistic) to predict pneumonia was 0.81 (95% confidence interval 0.73 to 0.88); for other SBIs this was even better: 0.86 (0.79 to 0.92). Risk thresholds of 10% or more were useful to identify children with serious bacterial infections; risk thresholds less than 2.5% were useful to rule out the presence of serious bacterial infections. External validation showed good discrimination for the prediction of pneumonia (0.81, 0.69 to 0.93); discriminative ability for the prediction of other SBIs was lower (0.69, 0.53 to 0.86).Conclusion A validated prediction model, including clinical signs, symptoms, and C reactive protein level, was useful for estimating the likelihood of pneumonia and other SBIs in children with fever, such as septicaemia/meningitis and urinary tract infections.

Physically and telephone-assigned NTS urgency levels were associated with majority of surrogate urgency markers. The NTS as single triage system for physical and telephone triage seems feasible.