Impact of a clinical decision model for febrile children at risk for serious bacterial infections at the emergency department: a randomized controlled trial

Adoption of C-reactive protein rapid tests for the management of acute childhood infections in hospitals in the Netherlands and England: a comparative health systems analysis

BACKGROUND

The adoption of C-reactive protein point-of-care tests (CRP POCTs) in hospitals varies across Europe. We aimed to understand the factors that contribute to different levels of adoption of CRP POCTs for the management of acute childhood infections in two countries.

METHODS

Comparative qualitative analysis of the implementation of CRP POCTs in the Netherlands and England. The study was informed by the non-adoption, abandonment, spread, scale-up, and sustainability (NASSS) framework. Data were collected through document analysis and qualitative interviews with stakeholders. Documents were identified by a scoping literature review, search of websites, and through the stakeholders. Stakeholders were sampled purposively initially, and then by snowballing. Data were analysed thematically.

RESULTS

Forty-one documents resulted from the search and 46 interviews were conducted. Most hospital healthcare workers in the Netherlands were familiar with CRP POCTs as the tests were widely used and trusted in primary care. Moreover, although diagnostics were funded through similar Diagnosis Related Group reimbursement mechanisms in both countries, the actual funding for each hospital was more constrained in England. Compared to primary care, laboratory-based CRP tests were usually available in hospitals and their use was encouraged in both countries because they were cheaper. However, CRP POCTs were perceived as useful in some hospitals of the two countries in which the laboratory could not provide CRP measures 24/7 or within a short timeframe, and/or in emergency departments where expediting patient care was important.

CONCLUSIONS

CRP POCTs are more available in hospitals in the Netherlands because of the greater familiarity of Dutch healthcare workers with the tests which are widely used in primary care in their country and because there are more funding constraints in England. However, most hospitals in the Netherlands and England have not adopted CRP POCTs because the alternative CRP measurements from the hospital laboratory are available in a few hours and at a lower cost.

External validation of a multivariable prediction model for identification of pneumonia and other serious bacterial infections in febrile immunocompromised children

OBJECTIVE

To externally validate and update the Feverkids tool clinical prediction model for differentiating bacterial pneumonia and other serious bacterial infections (SBIs) from non-SBI causes of fever in immunocompromised children.

DESIGN

International, multicentre, prospective observational study embedded in PErsonalised Risk assessment in Febrile illness to Optimise Real-life Management across the European Union (PERFORM).

SETTING

Fifteen teaching hospitals in nine European countries.

PARTICIPANTS

Febrile immunocompromised children aged 0-18 years.

METHODS

The Feverkids clinical prediction model predicted the probability of bacterial pneumonia, other SBI or no SBI. Model discrimination, calibration and diagnostic performance at different risk thresholds were assessed. The model was then re-fitted and updated.

RESULTS

Of 558 episodes, 21 had bacterial pneumonia, 104 other SBI and 433 no SBI. Discrimination was 0.83 (95% CI 0.71 to 0.90) for bacterial pneumonia, with moderate calibration and 0.67 (0.61 to 0.72) for other SBIs, with poor calibration. After model re-fitting, discrimination improved to 0.88 (0.79 to 0.96) and 0.71 (0.65 to 0.76) and calibration improved. Predicted risk <1% ruled out bacterial pneumonia with sensitivity 0.95 (0.86 to 1.00) and negative likelihood ratio (LR) 0.09 (0.00 to 0.32). Predicted risk >10% ruled in bacterial pneumonia with specificity 0.91 (0.88 to 0.94) and positive LR 6.51 (3.71 to 10.3). Predicted risk <10% ruled out other SBIs with sensitivity 0.92 (0.87 to 0.97) and negative LR 0.32 (0.13 to 0.57). Predicted risk >30% ruled in other SBIs with specificity 0.89 (0.86 to 0.92) and positive LR 2.86 (1.91 to 4.25).

CONCLUSION

Discrimination and calibration were good for bacterial pneumonia but poorer for other SBIs. The rule-out thresholds have the potential to reduce unnecessary investigations and antibiotics in this high-risk group.

Clinical prediction models for serious infections in children: external validation in ambulatory care

BACKGROUND

Early distinction between mild and serious infections (SI) is challenging in children in ambulatory care. Clinical prediction models (CPMs), developed to aid physicians in clinical decision-making, require broad external validation before clinical use. We aimed to externally validate four CPMs, developed in emergency departments, in ambulatory care.

METHODS

We applied the CPMs in a prospective cohort of acutely ill children presenting to general practices, outpatient paediatric practices or emergency departments in Flanders, Belgium. For two multinomial regression models, Feverkidstool and Craig model, discriminative ability and calibration were assessed, and a model update was performed by re-estimation of coefficients with correction for overfitting. For two risk scores, the SBI score and PAWS, the diagnostic test accuracy was assessed.

RESULTS

A total of 8211 children were included, comprising 498 SI and 276 serious bacterial infections (SBI). Feverkidstool had a C-statistic of 0.80 (95% confidence interval 0.77-0.84) with good calibration for pneumonia and 0.74 (0.70-0.79) with poor calibration for other SBI. The Craig model had a C-statistic of 0.80 (0.77-0.83) for pneumonia, 0.75 (0.70-0.80) for complicated urinary tract infections and 0.63 (0.39-0.88) for bacteraemia, with poor calibration. The model update resulted in improved C-statistics for all outcomes and good overall calibration for Feverkidstool and the Craig model. SBI score and PAWS performed extremely weak with sensitivities of 0.12 (0.09-0.15) and 0.32 (0.28-0.37).

CONCLUSIONS

Feverkidstool and the Craig model show good discriminative ability for predicting SBI and a potential for early recognition of SBI, confirming good external validity in a low prevalence setting of SBI. The SBI score and PAWS showed poor diagnostic performance.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02024282. Registered on 31 December 2013.

A simple clinical decision rule may help to rule out severe bacterial infection and spare antibiotics in febrile young children

AIM

To assess the performance of a new clinical decision rule (CDR) to identify patients at a low risk of invasive bacterial infection (IBI) among febrile children and its theoretical impact on antibiotic use.

METHODS

Prospective study including consecutive children <5 years of age who presented in one French paediatric emergency department with fever without source between January and December 2016. With the collected data, we constructed a CDR based on a sequential approach based on age, clinical toxic signs, urinalysis and procalcitonin level. We evaluated its diagnostic performances to identify IBI and its potential impact on antibiotic use.

RESULTS

Among the 1061 children (IBI 11/1061, 1.0%), 693 (65.3%) were classified at low or intermediate risk of IBI, with an IBI prevalence of 0%. The sensitivity and specificity of the CDR to predict IBI were 100% and 73.9%. Negative and positive predictive value were 100% and 3.9%, respectively. Using this new CDR, the current antibiotics exposure would theoretically be reduced from 33.6% to 24.1%.

CONCLUSION

The promising interest of this clinical decision rule, using simple and accessible biological and clinical tools, needs to be confirm with an external validation study, which will allow its use in clinical practice.

Accuracy of the NICE Traffic Light system for detecting serious illness in acutely unwell children presenting to general practice: a retrospective cohort study

Background

The National Institute for Health and Care Excellence (NICE) traffic light system was created to facilitate the assessment of unwell children in primary care. To the authors’ knowledge, no studies have validated this tool in UK general practice.

Aim

To evaluate the accuracy of this system for detecting serious illness in children presenting to general practice.

Design and setting

A retrospective diagnostic accuracy study was undertaken, using a cohort of acutely unwell children aged <5 years presenting to general practice in England and Wales.

Method

The traffic light categories of 6703 children were linked with hospital data to identify admissions and diagnoses. The sensitivity and specificity of these categories were calculated against the reference standard: a hospital-diagnosed serious illness within 7 days of GP consultation, measured using International Classification of Diseases, 10th Revision codes.

Results

In total, 2116 (31.6%) children were categorised as ‘red’; 4204 (62.7%) as ‘amber’; and 383 (5.7%) as ‘green’. There were 139 (2.1%) children who were admitted to hospital within 7 days of consultation, of whom 17 (12.2%; 0.3% overall) had a serious illness. The sensitivity of the red category (versus amber and green) was 58.8% (95% confidence interval [CI] = 32.9 to 81.6) and the specificity 68.5% (95% CI = 67.4 to 69.6). The sensitivity and specificity of red and amber combined (versus green) was 100% (95% CI = 80.5 to 100) and 5.7% (95% CI = 5.2 to 6.3), respectively.

Conclusion

The NICE traffic light system did not accurately detect children admitted with a serious illness, nor those not seriously ill who could have been managed at home. This system is not suitable for use as a clinical tool in general practice. Further research is required to update or replace the system.

Integrating Clinical Signs at Presentation and Clinician's Non-analytical Reasoning in Prediction Models for Serious Bacterial Infection in Febrile Children Presenting to Emergency Department

OBJECTIVE

Development and validation of clinical prediction model (CPM) for serious bacterial infections (SBIs) in children presenting to the emergency department (ED) with febrile illness, based on clinical variables, clinician's "gut feeling," and "sense of reassurance.

MATERIALS AND METHODS

Febrile children presenting to the ED of Children's Clinical University Hospital (CCUH) between April 1, 2017 and December 31, 2018 were enrolled in a prospective observational study. Data on clinical signs and symptoms at presentation, together with clinician's "gut feeling" of something wrong and "sense of reassurance" were collected as candidate variables for CPM. Variable selection for the CPM was performed using stepwise logistic regression (forward, backward, and bidirectional); Akaike information criterion was used to limit the number of parameters and simplify the model. Bootstrapping was applied for internal validation. For external validation, the model was tested in a separate dataset of patients presenting to six regional hospitals between January 1 and March 31, 2019.

RESULTS

The derivation cohort consisted of 517; 54% (n = 279) were boys, and the median age was 58 months. SBI was diagnosed in 26.7% (n = 138). Validation cohort included 188 patients; the median age was 28 months, and 26.6% (n = 50) developed SBI. Two CPMs were created, namely, CPM1 consisting of six clinical variables and CPM2 with four clinical variables plus "gut feeling" and "sense of reassurance." The area under the curve (AUC) for receiver operating characteristics (ROC) curve of CPM1 was 0.744 (95% CI, 0.683-0.805) in the derivation cohort and 0.692 (95% CI, 0.604-0.780) in the validation cohort. AUC for CPM2 was 0.783 (0.727-0.839) and 0.752 (0.674-0.830) in derivation and validation cohorts, respectively. AUC of CPM2 in validation population was significantly higher than that of CPM1 [p = 0.037, 95% CI (-0.129; -0.004)]. A clinical evaluation score was derived from CPM2 to stratify patients in "low risk," "gray area," and "high risk" for SBI.

CONCLUSION

Both CPMs had moderate ability to predict SBI and acceptable performance in the validation cohort. Adding variables "gut feeling" and "sense of reassurance" in CPM2 improved its ability to predict SBI. More validation studies are needed for the assessment of applicability to all febrile patients presenting to ED.

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

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.

Impact of a clinical decision rule on antibiotic prescription for children with suspected lower respiratory tract infections presenting to European emergency departments: a simulation study based on routine data

BACKGROUND

Discriminating viral from bacterial lower respiratory tract infections (LRTIs) in children is challenging thus commonly resulting in antibiotic overuse. The Feverkidstool, a validated clinical decision rule including clinical symptoms and C-reactive protein, safely reduced antibiotic use in children at low/intermediate risk for bacterial LRTIs in a multicentre trial at emergency departments (EDs) in the Netherlands.

OBJECTIVES

Using routine data from an observational study, we simulated the impact of the Feverkidstool on antibiotic prescriptions compared with observed antibiotic prescriptions in children with suspected LRTIs at 12 EDs in eight European countries.

METHODS

We selected febrile children aged 1 month to 5 years with respiratory symptoms and excluded upper respiratory tract infections. Using the Feverkidstool, we calculated individual risks for bacterial LRTI retrospectively. We simulated antibiotic prescription rates under different scenarios: (1) applying effect estimates on antibiotic prescription from the trial; and (2) varying both usage (50%-100%) and compliance (70%-100%) with the Feverkidstool's advice to withhold antibiotics in children at low/intermediate risk for bacterial LRTI (≤10%).

RESULTS

Of 4938 children, 4209 (85.2%) were at low/intermediate risk for bacterial LRTI. Applying effect estimates from the trial, the Feverkidstool reduced antibiotic prescription from 33.5% to 24.1% [pooled risk difference: 9.4% (95% CI: 5.7%-13.1%)]. Simulating 50%-100% usage with 90% compliance resulted in risk differences ranging from 8.3% to 15.8%. Our simulations suggest that antibiotic prescriptions would be reduced in EDs with high baseline antibiotic prescription rates or predominantly (>85%) low/intermediate-risk children.

CONCLUSIONS

Implementation of the Feverkidstool could reduce antibiotic prescriptions in children with suspected LRTIs in European EDs.

Assessment of the impact of a new sequential approach to antimicrobial use in young febrile children in the emergency department (DIAFEVERCHILD): a French prospective multicentric controlled, open, cluster-randomised, parallel-group study protocol

INTRODUCTION

Fever is one of the most common reasons for consultation in the paediatric emergency department (ED). Because of fear of bacterial infection in parents and caregivers, clinicians often overprescribe laboratory tests and empirical antibiotic treatment. The aims of this study are to demonstrate that using a procalcitonin (PCT) rapid test-based prediction rule (1) would not be inferior to usual practice in terms of morbidity and mortality (non-inferiority objective) and (2) would result in a significant reduction in antibiotic use (superiority objective).

METHODS AND ANALYSIS

This prospective multicentric cluster-randomised study aims to include 7245 febrile children aged 6 days to 3 years with a diagnosis of fever without source in 26 participating EDs in France and Switzerland during a 24-month period. During first period, all children will receive usual care. In a second period, a point-of-care PCT-based algorithm will be used in half of the clusters. The primary endpoints collected on day 15 after ED consultation will be a composite outcome of death or intensive care unit admission for any reason, disease-specific complications, diagnosis of bacterial infection after discharge from the ED for the non-inferiority objective and proportion of children with antibiotic treatment administered for the superiority objective. The endpoints will be compared between the two groups (experimental and control) by using a mixed logistic regression model adjusted on clustering of participants within centres and period within centres.

DISCUSSION

If the algorithm is validated, a new strategy will be discussed with medical societies to safely manage fever in young children without the need for invasive procedures for microbiological testing or empirical antibiotics.

ETHICS AND DISSEMINATION

This study was submitted to an independent ethics committee on 17 May 2018 (no. 2018-A00252-53). Results will be submitted to international peer-reviewed journals and presented at international conferences.

TRIAL REGISTRATION NUMBER

NCT03607162; Pre-results.

Evaluation of a clinical decision rule to guide antibiotic prescription in children with suspected lower respiratory tract infection in The Netherlands: A stepped-wedge cluster randomised trial

BACKGROUND

Optimising the use of antibiotics is a key component of antibiotic stewardship. Respiratory tract infections (RTIs) are the most common reason for antibiotic prescription in children, even though most of these infections in children under 5 years are viral. This study aims to safely reduce antibiotic prescriptions in children under 5 years with suspected lower RTI at the emergency department (ED), by implementing a clinical decision rule.

METHODS AND FINDINGS

In a stepped-wedge cluster randomised trial, we included children aged 1-60 months presenting with fever and cough or dyspnoea to 8 EDs in The Netherlands. The EDs were of varying sizes, from diverse geographic and demographic regions, and of different hospital types (tertiary versus general). In the pre-intervention phase, children received usual care, according to the Dutch and NICE guidelines for febrile children. During the intervention phase, a validated clinical prediction model (Feverkidstool) including clinical characteristics and C-reactive protein (CRP) was implemented as a decision rule guiding antibiotic prescription. The intervention was that antibiotics were withheld in children with a low or intermediate predicted risk of bacterial pneumonia (≤10%, based on Feverkidstool). Co-primary outcomes were antibiotic prescription rate and strategy failure. Strategy failure was defined as secondary antibiotic prescriptions or hospitalisations, persistence of fever or oxygen dependency up to day 7, or complications. Hospitals were randomly allocated to 1 sequence of treatment each, using computer randomisation. The trial could not be blinded. We used multilevel logistic regression to estimate the effect of the intervention, clustered by hospital and adjusted for time period, age, sex, season, ill appearance, and fever duration; predicted risk was included in exploratory analysis. We included 999 children (61% male, median age 17 months [IQR 9 to 30]) between 1 January 2016 and 30 September 2018: 597 during the pre-intervention phase and 402 during the intervention phase. Most children (77%) were referred by a general practitioner, and half of children were hospitalised. Intention-to-treat analyses showed that overall antibiotic prescription was not reduced (30% to 25%, adjusted odds ratio [aOR] 1.07 [95% CI 0.57 to 2.01, p = 0.75]); strategy failure reduced from 23% to 16% (aOR 0.53 [95% CI 0.32 to 0.88, p = 0.01]). Exploratory analyses showed that the intervention influenced risk groups differently (p < 0.01), resulting in a reduction in antibiotic prescriptions in low/intermediate-risk children (17% to 6%; aOR 0.31 [95% CI 0.12 to 0.81, p = 0.02]) and a non-significant increase in the high-risk group (47% to 59%; aOR 2.28 [95% CI 0.84 to 6.17, p = 0.09]). Two complications occurred during the trial: 1 admission to the intensive care unit during follow-up and 1 pleural empyema at day 10 (both unrelated to the study intervention). Main limitations of the study were missing CRP values in the pre-intervention phase and a prolonged baseline period due to logistical issues, potentially affecting the power of our study.

CONCLUSIONS

In this multicentre ED study, we observed that a clinical decision rule for childhood pneumonia did not reduce overall antibiotic prescription, but that it was non-inferior to usual care. Exploratory analyses showed fewer strategy failures and that fewer antibiotics were prescribed in low/intermediate-risk children, suggesting improved targeting of antibiotics by the decision rule.

TRIAL REGISTRATION

Netherlands Trial Register NTR5326.

Can clinical prediction models assess antibiotic need in childhood pneumonia? A validation study in paediatric emergency care

Objectives

Pneumonia is the most common bacterial infection in children at the emergency department (ED). Clinical prediction models for childhood pneumonia have been developed (using chest x-ray as their reference standard), but without implementation in clinical practice. Given current insights in the diagnostic limitations of chest x-ray, this study aims to validate these prediction models for a clinical diagnosis of pneumonia, and to explore their potential to guide decisions on antibiotic treatment at the ED.

Methods

We systematically identified clinical prediction models for childhood pneumonia and assessed their quality. We evaluated the validity of these models in two populations, using a clinical reference standard (1. definite/probable bacterial, 2. bacterial syndrome, 3. unknown bacterial/viral, 4. viral syndrome, 5. definite/probable viral), measuring performance by the ordinal c-statistic (ORC). Validation populations included prospectively collected data of children aged 1 month to 5 years attending the ED of Rotterdam (2012–2013) or Coventry (2005–2006) with fever and cough or dyspnoea.

Results

We identified eight prediction models and could evaluate the validity of seven, with original good performance. In the Dutch population 22/248 (9%) had a bacterial infection, in Coventry 53/301 (17%), antibiotic prescription was 21% and 35% respectively. Three models predicted a higher risk in children with bacterial infections than in those with viral disease (ORC ≥0.55) and could identify children at low risk of bacterial infection.

Conclusions

Three clinical prediction models for childhood pneumonia could discriminate fairly well between a clinical reference standard of bacterial versus viral infection. However, they all require the measurement of biomarkers, raising questions on the exact target population when implementing these models in clinical practice. Moreover, choosing optimal thresholds to guide antibiotic prescription is challenging and requires careful consideration of potential harms and benefits.

Biomarkers for Infection in Children: Current Clinical Practice and Future Perspectives

Biomarkers have become an integral part of the clinical decision-making process of clinicians dealing with febrile children. C-reactive protein, procalcitonin and white blood cell count are probably the most studied ones. Crucial to using biomarkers is the understanding of how a test result will alter post-test probabilities and then impact on clinical decision making. Improved analytical and computational platforms have enabled the next generation of advanced biomarker discovery studies. Promising combinations of candidate biomarkers for a diverse spectrum of febrile illnesses, such as viral and bacterial infections, have been identified using proteomics, RNA gene expression and metabolomics.

Update of a clinical prediction model for serious bacterial infections in preschool children by adding a host-protein-based assay: a diagnostic study

OBJECTIVE

To determine whether updating a diagnostic prediction model by adding a combination assay (tumour necrosis factor-related apoptosis-inducing ligand, interferon γ induced protein-10 and C reactive protein (CRP)) can accurately identify children with pneumonia or other serious bacterial infections (SBIs).

DESIGN

Observational double-blind diagnostic study.

SETTING

Two hospitals in Israel and four hospitals in the Netherlands.

PATIENTS

591 children, aged 1-60 months, presenting with lower respiratory tract infections or fever without source. 96 of them had SBIs. The original Feverkidstool, a polytomous logistic regression model including clinical variables and CRP, was recalibrated and thereafter updated by using the assay.

MAIN OUTCOME MEASURES

Pneumonia, other SBIs or no SBI.

RESULTS

The recalibrated original Feverkidstool discriminated well between SBIs and viral infections, with a c-statistic for pneumonia of 0.84 (95% CI 0.77 to 0.92) and 0.82 (95% CI 0.77 to 0.86) for other SBIs. The discriminatory ability increased when CRP was replaced by the combination assay; c-statistic for pneumonia increased to 0.89 (95% CI 0.82 to 0.96) and for other SBIs to 0.91 (95% CI 0.87 to 0.94). This updated Feverkidstool improved diagnosis of SBIs mainly in children with low-moderate risk estimates of SBIs.

CONCLUSION

We improved the diagnostic accuracy of the Feverkidstool by replacing CRP with a combination assay to predict pneumonia or other SBIs in febrile children. The updated Feverkidstool has the largest potential to rule out bacterial infections and thus to decrease unnecessary antibiotic prescription in children with low-to-moderate predicted risk of SBIs.

Clinical prediction models for young febrile infants at the emergency department: an international validation study

OBJECTIVE

To assess the diagnostic value of existing clinical prediction models (CPM; ie, statistically derived) in febrile young infants at risk for serious bacterial infections.

METHODS

A systematic literature review identified eight CPMs for predicting serious bacterial infections in febrile children. We validated these CPMs on four validation cohorts of febrile children in Spain (age <3 months), France (age <3 months) and two cohorts in the Netherlands (age 1-3 months and >3-12 months). We evaluated the performance of the CPMs by sensitivity/specificity, area under the receiver operating characteristic curve (AUC) and calibration studies.

RESULTS

The original cohorts in which the prediction rules were developed (derivation cohorts) ranged from 381 to 15 781 children, with a prevalence of serious bacterial infections varying from 0.8% to 27% and spanned an age range of 0-16 years. All CPMs originally performed moderately to very well (AUC 0.60-0.93). The four validation cohorts included 159-2204 febrile children, with a median age range of 1.8 (1.2-2.4) months for the three cohorts <3 months and 8.4 (6.0-9.6) months for the cohort >3-12 months of age. The prevalence of serious bacterial infections varied between 15.1% and 17.2% in the three cohorts <3 months and was 9.8% for the cohort >3-12 months of age. Although discriminative values varied greatly, best performance was observed for four CPMs including clinical signs and symptoms, urine dipstick analyses and laboratory markers with AUC ranging from 0.68 to 0.94 in the three cohorts <3 months (ranges sensitivity: 0.48-0.94 and specificity: 0.71-0.97). For the >3-12 months' cohort AUC ranges from 0.80 to 0.89 (ranges sensitivity: 0.70-0.82 and specificity: 0.78-0.90). In general, the specificities exceeded sensitivities in our cohorts, in contrast to derivation cohorts with high sensitivities, although this effect was stronger in infants <3 months than in infants >3-12 months.

CONCLUSION

We identified four CPMs, including clinical signs and symptoms, urine dipstick analysis and laboratory markers, which can aid clinicians in identifying serious bacterial infections. We suggest clinicians should use CPMs as an adjunctive clinical tool when assessing the risk of serious bacterial infections in febrile young infants.

Antibiotic Use in Febrile Children Presenting to the Emergency Department: A Systematic Review

Introduction: While fever is the main complaint among pediatric emergency services and high antibiotic prescription are observed, only a few studies have been published addressing this subject. Therefore this systematic review aims to summarize antibiotic prescriptions in febrile children at the ED and assess its determinants. Methods: We extracted studies published from 2000 to 2017 on antibiotic use in febrile children at the ED from different databases. Author, year, and country of publishing, study design, inclusion criteria, primary outcome, age, and number of children included in the study was extracted. To compare the risk-of-bias all articles were assessed using the MINORS criteria. For the final quality assessment we additionally used the sample size and the primary outcome. Results: We included 26 studies reporting on antibiotic prescription and 28 intervention studies on the effect on antibiotic prescription. In all 54 studies antibiotic prescriptions in the ED varied from 15 to 90.5%, pending on study populations and diagnosis. Respiratory tract infections were mostly studied. Pediatric emergency physicians prescribed significantly less antibiotics then general emergency physicians. Most frequent reported interventions to reduce antibiotics are delayed antibiotic prescription in acute otitis media, viral testing and guidelines. Conclusion: Evidence on antibiotic prescriptions in children with fever presenting to the ED remains inconclusive. Delayed antibiotic prescription in acute otitis media and guidelines for fever and respiratory infections can effectively reduce antibiotic prescription in the ED. The large heterogeneity of type of studies and included populations limits strict conclusions, such a gap in knowledge on the determining factors that influence antibiotic prescription in febrile children presenting to the ED remains.

Review of implementation strategies to change healthcare provider behaviour in the emergency department

OBJECTIVES

Advances in emergency medicine research can be slow to make their way into clinical care, and implementing a new evidence-based intervention can be challenging in the emergency department. The Canadian Association of Emergency Physicians (CAEP) Knowledge Translation Symposium working group set out to produce recommendations for best practice in the implementation of a new science in Canadian emergency departments.

METHODS

A systematic review of implementation strategies to change health care provider behaviour in the emergency department was conducted simultaneously with a national survey of emergency physician experience. We summarized our findings into a list of draft recommendations that were presented at the national CAEP Conference 2017 and further refined based on feedback through social media strategies.

RESULTS

We produced 10 recommendations for implementing new evidence-based interventions in the emergency department, which cover identifying a practice gap, evaluating the evidence, planning the intervention strategy, monitoring, providing feedback during implementation, and desired qualities of future implementation research.

CONCLUSIONS

We present recommendations to guide future emergency department implementation initiatives. There is a need for robust and well-designed implementation research to guide future emergency department implementation initiatives.

Characteristics of revisits of children at risk for serious infections in pediatric emergency care

In this study, we aimed to identify characteristics of (unscheduled) revisits and its optimal time frame after Emergency Department (ED) discharge. Children with fever, dyspnea, or vomiting/diarrhea (1 month-16 years) who attended the ED of Erasmus MC-Sophia, Rotterdam (2010-2013), the Netherlands, were prospectively included. Three days after ED discharge, we applied standardized telephonic questionnaires on disease course and revisits. Multivariable logistic regression analysis was used to identify independent characteristics of revisits. Young age, parental concern, and alarming signs and symptoms (chest wall retractions, ill appearance, clinical signs of dehydration, and tachypnea) were associated with revisits (n = 527) in children at risk for serious infections discharged from the ED (n = 1765). Children revisited the ED within a median of 2 days (IQR 1.0-3.0), but this was proven to be shorter in children with vomiting/diarrhea (1.0 day (IQR 1.0-2.0)) compared to children with fever or dyspnea (2.0 (IQR 1.0-3.0)).

CONCLUSION

Young age, parental concern, and alarming signs and symptoms (chest wall retractions, ill appearance, clinical signs of dehydration, and tachypnea) were associated with emergency health care revisits in children with fever, dyspnea, and vomiting/diarrhea. These characteristics could help to define targeted review of children during post-discharge period. We observed a disease specific and differential timing of control revisits after ED discharge. What is Known • Fever, dyspnea, and vomiting/diarrhea are major causes of emergency care attendance in children. • As uncertainty remains on uneventful recovery, patients at risk need to be identified on order to improve safety netting after discharge from the ED. What is New • In children with fever, dyspnea, and vomiting/diarrhea, young age, parental concern and chest wall retractions, ill appearance, clinical signs of dehydration, and tachypnea help to define targeted review of children during the post-discharge period. • A revisit after ED discharge is disease-specific and seems to be shorter for children with vomiting/diarrhea than others.

Fever in Children: Pearls and Pitfalls

Fever in children is a common concern for parents and one of the most frequent presenting complaints in emergency department visits, often involving non-pediatric emergency physicians. Although the incidence of serious infections has decreased after the introduction of conjugate vaccines, fever remains a major cause of laboratory investigation and hospital admissions. Furthermore, antipyretics are the most common medications administered to children. We review the epidemiology and measurement of fever, the meaning of fever and associated clinical signs in children of different ages and under special conditions, including fever in children with cognitive impairment, recurrent fevers, and fever of unknown origin. While the majority of febrile children have mild, self-resolving viral illness, a minority may be at risk of life-threatening infections. Clinical assessment differs markedly from adult patients. Hands-off evaluation is paramount for a correct evaluation of breathing, circulation and level of interaction. Laboratory markers and clinical prediction rules provide limited help in identifying children at risk for serious infections; however, clinical examination, prudent utilization of laboratory tests, and post-discharge guidance ("safety netting") remain the cornerstone of safe management of febrile children.

Predicting Risk of Serious Bacterial Infections in Febrile Children in the Emergency Department

BACKGROUND

Improving the diagnosis of serious bacterial infections (SBIs) in the children's emergency department is a clinical priority. Early recognition reduces morbidity and mortality, and supporting clinicians in ruling out SBIs may limit unnecessary admissions and antibiotic use.

METHODS

A prospective, diagnostic accuracy study of clinical and biomarker variables in the diagnosis of SBIs (pneumonia or other SBI) in febrile children <16 years old. A diagnostic model was derived by using multinomial logistic regression and internally validated. External validation of a published model was undertaken, followed by model updating and extension by the inclusion of procalcitonin and resistin.

RESULTS

There were 1101 children studied, of whom 264 had an SBI. A diagnostic model discriminated well between pneumonia and no SBI (concordance statistic 0.84, 95% confidence interval 0.78-0.90) and between other SBIs and no SBI (0.77, 95% confidence interval 0.71-0.83) on internal validation. A published model discriminated well on external validation. Model updating yielded good calibration with good performance at both high-risk (positive likelihood ratios: 6.46 and 5.13 for pneumonia and other SBI, respectively) and low-risk (negative likelihood ratios: 0.16 and 0.13, respectively) thresholds. Extending the model with procalcitonin and resistin yielded improvements in discrimination.

CONCLUSIONS

Diagnostic models discriminated well between pneumonia, other SBIs, and no SBI in febrile children in the emergency department. Improvements in the classification of nonevents have the potential to reduce unnecessary hospital admissions and improve antibiotic prescribing. The benefits of this improved risk prediction should be further evaluated in robust impact studies.

Pediatric Patients Discharged from the Emergency Department with Abnormal Vital Signs

INTRODUCTION

Children often present to the emergency department (ED) with minor conditions such as fever and have persistently abnormal vital signs. We hypothesized that a significant portion of children discharged from the ED would have abnormal vital signs and that those discharged with abnormal vital signs would experience very few adverse events.

METHODS

We performed a retrospective chart review encompassing a 44-month period of all pediatric patients (aged two months to 17 years) who were discharged from the ED with an abnormal pulse rate, respiratory rate, temperature, or oxygen saturation. We used a local quality assurance database to identify pre-defined adverse events after discharge in this population. Our primary aim was to determine the proportion of children discharged with abnormal vital signs and the frequency and nature of adverse events. Additionally, we performed a sub-analysis comparing the rate of adverse events in children discharged with normal vs. abnormal vital signs, as well as a standardized review of the nature of each adverse event.

RESULTS

Of 33,185 children discharged during the study period, 5,540 (17%) of these patients had at least one abnormal vital sign. There were 24/5,540 (0.43%) adverse events in the children with at least one abnormal vital sign vs. 47/27,645 (0.17%) adverse events in the children with normal vital signs [relative risk = 2.5 (95% confidence interval, 1.6 to 2.4)].However, upon review of each adverse event we found only one case that was related to the index visit, was potentially preventable by a 23-hour hospital observation, and caused permanent disability.

CONCLUSION

In our study population, 17% of the children were discharged with at least one abnormal vital sign, and there were very few adverse (0.43%) events associated with this practice. Heart rate was the most common abnormal vital sign leading to an adverse event. Severe adverse events that were potentially related to the abnormal vital sign(s) were exceedingly rare. Additional research is needed in broader populations to better determine the rate of adverse events and possible methods of avoiding them.

Systematic review of the effects of care provided with and without diagnostic clinical prediction rules

BACKGROUND

Diagnostic clinical prediction rules (CPRs) are worthwhile if they improve patient outcomes or provide benefits such as reduced resource use, without harming patients. We conducted a systematic review to assess the effects of diagnostic CPRs on patient and process of care outcomes.

METHODS

We searched electronic databases and a trial registry and performed citation and reference checks, for randomised trials comparing a diagnostic strategy with and without a CPR. Included studies were assessed for risk of bias and similar studies meta-analysed.

RESULTS

Twenty-seven studies evaluating diagnostic CPRs for 14 conditions were included. A clinical management decision was the primary outcome in the majority of studies. Most studies were judged to be at high or uncertain risk of bias on ≥3 of 6 domains. Details of study interventions and implementation were infrequently reported.For suspected Group A Streptococcus throat infection, diagnostic CPRs reduced symptoms (1 study) and antibiotic prescriptions (5 studies, RR 0.86, 95% CI 0.75 to 0.99). For suspected cardiac chest pain, diagnostic strategies incorporating a CPR improved early discharge rates (1 study), decreased objective cardiac testing (1 study) and decreased hospitalisations (1 study). For ankle injuries, Ottawa Ankle Rules reduced radiography when used with clinical examination (1 study) but had no effect on length of stay as a triage test (1 study). For suspected acute appendicitis, CPRs had no effect on rates of perforated appendix (1 study) or the number of non-therapeutic operations (5 studies, RR 0.68, 95% CI 0.43 to 1.08). For suspected pneumonia, CPRs reduced antibiotic prescribing without unfavourable outcomes (3 studies). For children with possible serious bacterial infection, diagnostic CPRs did not improve process of care outcomes (3 studies).

CONCLUSION

There are few randomised trials of diagnostic CPRs, and patient outcomes are infrequently reported. Diagnostic CPRs had a positive effect on process outcomes in some clinical conditions; however, many studies were at unclear or high risk of bias and the results may be context specific. Future studies should seek to detail how the CPR might alter the diagnostic pathway, report effects on both patient and process outcomes, and improve reporting of the study interventions and implementation.

TRIAL REGISTRATION

The protocol for this review was not registered with PROSPERO, the international prospective register of systematic review protocols. The review was conceived and protocol prepared prior to the launch of PROSPERO in February 2011.

Predictors of fever-related admissions to a paediatric assessment unit, ward and reattendances in a South London emergency department: the CABIN 2 study

OBJECTIVE

To explore the risk factors for ward and paediatric assessment unit (PAU) admissions from the emergency department (ED).

DESIGN

Prospective observational study.

SETTING AND PATIENTS

Febrile children attending a large tertiary care ED during the winter of 2014-2015.

MAIN OUTCOME MEASURES

Ward and PAU admissions, National Institute for Health and Care Excellence (NICE) guidelines classification, reattendance to the ED within 28 days and antibiotic use.

RESULTS

A total of 1097 children attending the children's ED with fever were analysed. Risk factors for PAU admission were tachycardia (RR=1.1, 95% CI (1 to 1.1)), ill-appearance (RR=2.2, 95% CI (1.2 to 4.2)), abnormal chest findings (RR=2.1, 95% CI (1.2 to 4.3)), categorised as NICE amber (RR 1.7 95% CI (1.2 to 2.5)). There was a 30% discordance between NICE categorisation at triage and statistical internal validation. Predictors of ward admission were a systemic (RR=6.9, 95% CI (2.4 to 19.8)) or gastrointestinal illness (RR=3.8, 95% (1.4 to 10.4)) and categorised as NICE Red (RR=5.9, 95% CI (2.2 to 15.3)). Only 51 children had probable bacterial pneumonia (4.6%), 52 children had a proven urinary tract infection (4.2%), with just 2 (0.2%) positive blood cultures out of 485 (44%) children who received an antibiotic. 15% of all children reattended by 28 days and were more likely to have been categorised as Amber and had investigations on initial visit.

CONCLUSIONS

Risk factors for PAU and ward admissions are different in this setting with high reattendance rates and very low proportion of confirmed/probable serious bacterial infections. Future studies need to focus on reducing avoidable admissions and antibiotic treatment.

Supporting decisions to increase the safe discharge of children with febrile illness from the emergency department: a systematic review and meta-analysis

BACKGROUND

Despite fewer serious infections presenting to the children's emergency department (ED), hospital admissions of children with febrile illness have increased. We review evidence for the use of decision rules to increase the safe discharge of these children from the ED.

METHODS

A systematic review of prospective studies of decision rules for the discharge of children with febrile illness, and prediction rules for the diagnosis of serious infections in children presenting to ED. We reviewed the MEDLINE database, Cochrane Library and hand searched the bibliographies of related studies. The search was limited to the English language.

RESULTS

Thirty-three studies were identified. Fourteen reported low-risk criteria to rule out serious bacterial infection (SBI) in infants less than 3 months of age. In this group, clinical tools such as the Rochester and Philadelphia criteria support the safe discharge of low-risk infants without empirical antibiotics. Seventeen studies reported prediction rules in older children, though only four included children over 3 years. Two impact studies based upon multivariable prediction models failed to demonstrate any impact on rates of discharge from ED.

CONCLUSIONS

The use of clinical prediction models can improve discrimination between serious and self-limiting infections in children. The application of low-risk thresholds may help to rule out serious infections and discharge children from the ED without empirical antibiotics. A growing evidence base for prediction rules has so far failed to translate into validated rules to aid decision-making. Future work should evaluate decision rules in well designed impact studies, focusing on the need for hospital admission and antibiotic therapy.