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

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.

FeBRILe3: Safety Evaluation of Febrile Infant Guidelines Through Prospective Bayesian Monitoring

OBJECTIVES

Despite evidence supporting earlier discharge of well-appearing febrile infants at low risk of serious bacterial infection (SBI), admissions for ≥48 hours remain common. Prospective safety monitoring may support broader guideline implementation.

METHODS

A sequential Bayesian safety monitoring framework was used to evaluate a new hospital guideline recommending early discharge of low-risk infants. Hospital readmissions within 7 days of discharge were regularly assessed against safety thresholds, derived from historic rates and expert opinion, and specified a priori (8 per 100 infants). Infants aged under 3 months admitted to 2 Western Australian metropolitan hospitals for management of fever without source were enrolled (August 2019-December 2021), to a prespecified maximum 500 enrolments.

RESULTS

Readmission rates remained below the prespecified threshold at all scheduled analyses. Median corrected age was 34 days, and 14% met low-risk criteria (n = 71). SBI was diagnosed in 159 infants (32%), including urinary tract infection (n = 140) and bacteraemia (n = 18). Discharge occurred before 48 hours for 192 infants (38%), including 52% deemed low-risk. At study completion, 1 of 37 low-risk infants discharged before 48 hours had been readmitted (3%), for issues unrelated to SBI diagnosis. In total, 20 readmissions were identified (4 per 100 infants; 95% credible interval 3, 6), with >0.99 posterior probability of being below the prespecified noninferiority threshold, indicating acceptable safety.

CONCLUSIONS

A Bayesian monitoring approach supported safe early discharge for many infants, without increased risk of readmission. This framework may be used to embed safety evaluations within future guideline implementation programs to further reduce low-value care.

Performance Evaluation of Host Biomarker Combinations for the Diagnosis of Serious Bacterial Infection in Young Febrile Children: A Double-Blind, Multicentre, Observational Study

The diagnosis of serious bacterial infection (SBI) in young febrile children remains challenging. This prospective, multicentre, observational study aimed to identify new protein marker combinations that can differentiate a bacterial infection from a viral infection in 983 children, aged 7 days–36 months, presenting with a suspected SBI at three French paediatric emergency departments. The blood levels of seven protein markers (CRP, PCT, IL-6, NGAL, MxA, TRAIL, IP-10) were measured at enrolment. The patients received the standard of care, blinded to the biomarker results. An independent adjudication committee assigned a bacterial vs. viral infection diagnosis based on clinical data, blinded to the biomarker results. Computational modelling was applied to the blood levels of the biomarkers using independent training and validation cohorts. Model performances (area under the curve (AUC), positive and negative likelihood ratios (LR+ and LR–)) were calculated and compared to those of the routine biomarkers CRP and PCT. The targeted performance for added value over CRP or PCT was LR+ ≥ 5.67 and LR− ≤ 0.5. Out of 652 analysed patients, several marker combinations outperformed CRP and PCT, although none achieved the targeted performance criteria in the 7 days–36 months population. The models seemed to perform better in younger (7–91 day-old) patients, with the CRP/MxA/TRAIL combination performing best (AUC 0.895, LR+ 10.46, LR− 0.16). Although computational modelling using combinations of bacterial- and viral-induced host-protein markers is promising, further optimisation is necessary to improve SBI diagnosis in young febrile children.

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

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.

Cost Analysis of Emergency Department Criteria for Evaluation of Febrile Infants Ages 29 to 90 Days

OBJECTIVE

To compare the medical costs associated with risk stratification criteria used to evaluate febrile infants 29-90 days of age.

STUDY DESIGN

A cost analysis study was conducted evaluating the Boston, Rochester, Philadelphia, Step-by-Step, and PECARN criteria. The percentage of infants considered low risk and rates of missed infections were obtained from published literature. Emergency department costs were estimated from the Centers for Medicare and Medicaid Services. The Health Care Cost and Utilization Project databases were used to estimate the number of infants ages 29-90 days presenting with fever annually and costs for admissions related to missed infections. A probabilistic Markov model with a Dirichlet prior was used to estimate the transition probability distributions for each outcome, and a gamma distribution was used to model costs. A Markov simulation estimated the distribution of expected annual costs per infant and total annual costs.

RESULTS

For low-risk infants, the mean cost per infant for the criteria were Rochester: $1050 (IQR $1004-$1092), Philadelphia: $1416 (IQR, $1365-$1465), Boston: $1460 (IQR, $1411-$1506), Step-by-Step $942 (IQR, $899-$981), and PECARN $1004 (IQR, $956-$1050). An estimated 18 522 febrile 1- to 3-month-old infants present annually and estimated total mean costs for their care by criteria were: Rochester, $127.3 million (IQR, $126.1-$128.5); Philadelphia, $129.9 million (IQR, $128.7-$131.1); Boston, $128.7 million (IQR, $127.5-$129.9); Step-by-Step, $ 126.6 million (IQR, $125.4-$127.8); and PECARN, $125.8 million (IQR, $124.6-$127).

CONCLUSIONS

The Rochester, Step-by-step, and PECARN criteria are the least costly when evaluating infants 29-90 days of age with a fever.

Cost Study of a Cluster Randomized Trial on a Clinical Decision Rule Guiding Antibiotic Treatment in Children With Suspected Lower Respiratory Tract Infections in the Emergency Department

BACKGROUND

Children with fever and respiratory symptoms represent a large patient group at the emergency department (ED). A decision rule-based treatment strategy improved targeting of antibiotics in these children in a recent clinical trial. This study aims to evaluate the impact of the decision rule on healthcare and societal costs, and to describe costs of children with suspected lower respiratory tract infections (RTIs) in the ED in general.

METHODS

In a stepped-wedge, cluster randomized trial, we collected cost data of children 1 month to 5 years of age with fever and cough/dyspnea in 8 EDs in The Netherlands (2016-2018). We calculated medical costs and societal costs per patient, during usual care (n = 597), and when antibiotic prescription was guided by the decision rule (n = 402). We calculated cost-of-illness of this patient group and estimated their annual costs at national level.

RESULTS

The cost-of-illness of children under 5 years with suspected lower RTIs in the ED was on average &OV0556;2130 per patient. At population level this is &OV0556;15 million per year in The Netherlands (&OV0556;1.7 million/100,000 children under 5). Mean costs per patient in usual care (&OV0556;2300) were reduced to &OV0556;1870 in the intervention phase (P = 0.01). Main cost drivers were hospitalization and lost parental workdays.

CONCLUSIONS

Implementation of a decision rule-based treatment strategy in children with suspected lower RTI was cost-saving, due to a reduction in hospitalization and parental absenteeism. Given the high frequency of this disease in children, the decision rule has the potential to result in a considerable cost reduction at population level.

FeBRILe3 Project: protocol for a prospective pragmatic, multisite observational study and safety evaluation assessing Fever, Blood cultures and Readiness for discharge in Infants Less than 3 months old

INTRODUCTION

The purpose of this observational study is to assess the safety and impact of the introduction of a clinical practice guideline (CPG) recommending early discharge of infants with fever without source who are at low risk of serious bacterial infection (SBI). We hypothesise that implementation of this guideline will be associated with a rate of unplanned readmission to hospital (within 7 days of discharge) which is similar (ie, non-inferior) to that observed under previous standard practice.

METHODS AND ANALYSIS

This observational study is a prospective pragmatic, multisite safety assessment and impact project. It will evaluate the safety of a CPG which allows febrile infants fulfilling low-risk criteria to be discharged early from hospital if their blood cultures demonstrate no growth at 24 hours (compared with previous minimum 48 hours admission). This guideline has been implemented at two Western Australian metropolitan hospitals. Infants aged <3 months (chronological or corrected for premature birth before 37 weeks gestation) presenting with fever without source will be included. The primary outcome is readmission to hospital due to clinical deterioration/caregiver concern within 7 days of discharge, identified through review of electronic admission details and study-specific caregiver surveys. Secondary outcomes include rates of SBI, hospital lengths of stay compared with previous practice, clinician guideline adherence and caregiver satisfaction with the discharge process. Analysis will be within a sequential Bayesian safety monitoring framework, which incorporates new information and updates the evidence for guideline safety relative to previous practice (historical control) at prespecified interim analyses. Demographic and clinical information will be summarised.

ETHICS AND DISSEMINATION

Ethics approval and waiver of consent for data collection has been granted by the Child and Adolescent Health Service Human Research Ethics Committee (RGS0000001415). Caregivers will have the option to opt out of survey follow-up. Results will be disseminated via peer-reviewed publication.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry (ACTRN12619001010189).

Performance of the Modified Boston and Philadelphia Criteria for Invasive Bacterial Infections

BACKGROUND

The ability of the decades-old Boston and Philadelphia criteria to accurately identify infants at low risk for serious bacterial infections has not been recently reevaluated.

METHODS

We assembled a multicenter cohort of infants 29 to 60 days of age who had cerebrospinal fluid (CSF) and blood cultures obtained. We report the performance of the modified Boston criteria (peripheral white blood cell count [WBC] ≥20 000 cells per mm³, CSF WBC ≥10 cells per mm³, and urinalysis with >10 WBC per high-power field or positive urine dip result) and modified Philadelphia criteria (peripheral WBC ≥15 000 cells per mm³, CSF WBC ≥8 cells per mm³, positive CSF Gram-stain result, and urinalysis with >10 WBC per high-power field or positive urine dip result) for the identification of invasive bacterial infections (IBIs). We defined IBI as bacterial meningitis (growth of pathogenic bacteria from CSF culture) or bacteremia (growth from blood culture).

RESULTS

We applied the modified Boston criteria to 8344 infants and the modified Philadelphia criteria to 8131 infants. The modified Boston criteria identified 133 of the 212 infants with IBI (sensitivity 62.7% [95% confidence interval (CI) 55.9% to 69.3%] and specificity 59.2% [95% CI 58.1% to 60.2%]), and the modified Philadelphia criteria identified 157 of the 219 infants with IBI (sensitivity 71.7% [95% CI 65.2% to 77.6%] and specificity 46.1% [95% CI 45.0% to 47.2%]). The modified Boston and Philadelphia criteria misclassified 17 of 53 (32.1%) and 13 of 56 (23.3%) infants with bacterial meningitis, respectively.

CONCLUSIONS

The modified Boston and Philadelphia criteria misclassified a substantial number of infants 29 to 60 days old with IBI, including those with bacterial meningitis.

Comparing febrile children presenting on and off antibiotics to the emergency department: a retrospective cohort study

Background

It is not yet known how antibiotics may affect Serious Bacterial Infections (SBI). Our aim is to describe the presentation, management, and serious bacterial infections (SBI) of febrile children on or off antibiotics.

Methods

Retrospective, cohort study of febrile Emergency Department patients, 0–36 months of age, at a single institution, between 2009and 2012.

Results

Seven hundred fifty-three patients were included: 584 in the No-Antibiotics group and 169 (22%) in the Antibiotics group. Age and abnormal lung sounds were predictors for being on antibiotics (OR 2.00 [95% CI 1.23–3.25] and OR 1.04 [95% CI 1.02–1.06] respectively) while female gender, and lower temperatures were negative predictors (OR 0.68 [95%0.47–0.98] and OR 0.47 [95% CI 0.32–0.67] respectively). Antibiotics were prescribed by a physician 89% of the time; the most common one being Amoxicillin/Clavulanic Acid (39%). The antibiotic group got more blood tests (57% vs 45%) and Chest X-Rays (37% vs 25%). Overall, the percent of SBIs (and pneumonias) was statistically the same in both groups (6.5% in the No-antibiotic group VS 3.6%).

Conclusions

Children presenting on antibiotics and off antibiotics were significantly different in their presentation and management, although the overall percentages of SBI were similar in each group. Further investigations into this subgroup of febrile children are needed.

Risk of invasive bacterial infections by week of age in infants: prospective national surveillance, England, 2010-2017

OBJECTIVE

To estimate the incidence of laboratory-confirmed, invasive bacterial infections (IBIs) by week of age in infants over a 7-year period.

DESIGN

Analysis of prospective national surveillance data for England.

SETTING

National Health Service hospitals in England.

PATIENTS

Infants aged <1 year who were hospitalised with IBI.

MAIN OUTCOME MEASURES

IBI incidence by week of age, incidence rate ratio (IRR) at 8, 12 and 16 weeks compared with the first week of life, and the main pathogens responsible for IBI.

RESULTS

There were 22 075 IBI episodes between 2010/2011 and 2016/2017. The lowest annual cases were in 2011/2012 (n=2 799; incidence, 412/100 000 population), increasing year-on-year to 3 698 cases in 2016/2017 (incidence, 552/100 000 population). The incidence was highest in the first week of life and then declined rapidly. In 2016/2017, compared with the first week of life, weekly IBI incidence was 92% lower at 8 weeks (IRR 0.08; 95% CI 0.06 to 0.10) and 96% lower at 16 weeks of age (IRR 0.04; 95% CI 0.03 to 0.06). In 2016/2017, Escherichia coli was the most prevalent pathogen responsible for IBI (n=592, 16.0%), followed by group B Streptococci (n=493, 13.3%), Staphylococcus aureus (n=400, 10.8%) and Enterococci (n=304, 8.2%). The other pathogens were individually responsible for <5% of total cases. There were differences in age distribution of the pathogens with increasing age.

CONCLUSION

IBI incidence declines rapidly after the first week of life, such that infants have a very low risk of IBI by the time they are eligible for their routine immunisations from 8 weeks of age.

Validation of Risk Stratification Criteria to Identify Febrile Neonates at Low Risk of Serious Bacterial Infection

Our objective was to evaluate the accuracy of risk stratification criteria for febrile neonates in the emergency department. This was a retrospective study of febrile neonates ≤56 days of age. Patients were low risk for serious bacterial infection (SBI) if all test results were within normal ranges. Three hundred thirty-eight patients were enrolled with a mean age of 32 (±14) days, and 78 (23%) had SBI: 26 (8%) with bacteremia, 48 (14%) with urinary tract infection, 3 (1%) with meningitis, and 11 (3%) with pneumonia. Risk stratification criteria identified 47 (14%) as low risk, 2 of whom had SBI (both with Group B Streptococcus bacteremia). The sensitivity was 97.4% (95% confidence interval = 91.0% to 99.7%), and the negative predictive value was 95.7% (95% confidence interval = 84.8% to 98.9%). The risk stratification criteria have high sensitivity and high negative predictive value for identifying infants at low risk for SBI. Care must be taken to assure reliable follow-up.

Procalcitonin and C-reactive protein may help to detect invasive bacterial infections in children who have fever without source

AIM

This study evaluated the epidemiology and performance of biomarkers for identifying bacterial infections in children who presented with fever without source.

METHODS

We conducted a prospective cohort study in the paediatric department at the University Hospital of Nantes, France, in 2016. Children older than six days and younger than five years of age were included.

RESULTS

A total of 1060 children (52.2% male) with fever without source were admitted, and the median age was 17 months (interquartile range: 6.6-24.3 months). Severe bacterial infections were diagnosed in 127 (11.9%) children and invasive bacterial infections in 11 (1.0%) children: four (0.3%) with bacterial meningitis and seven (0.6%) with bacteraemia. A further 114 (10.7%) had urinary tract infections. We explored the area under the receiver-operating characteristic curves for identifying invasive bacterial infections. The curves for procalcitonin and C-reactive protein assays were better than those for the absolute neutrophil counts and the white blood cell counts.

CONCLUSION

This study found that there was a low prevalence of invasive bacterial infections in children who presented with fever without source. It also showed that procalcitonin and C-reactive protein may help to detect invasive bacterial infections in children who have fever without source.

Validation of the Feverkidstool and procalcitonin for detecting serious bacterial infections in febrile children

BackgroundTo validate the Feverkidstool, a prediction model consisting of clinical signs and symptoms and C-reactive protein (CRP) to identify serious bacterial infections (SBIs) in febrile children, and to determine the incremental diagnostic value of procalcitonin.MethodsThis prospective observational study that was carried out at two Dutch emergency departments included children with fever, aged 1 month to 16 years. The prediction models were developed with polytomous logistic regression differentiating "pneumonia" and "other SBIs" from "non-SBIs" using standardized, routinely collected data on clinical signs and symptoms, CRP, and procalcitonin.ResultsA total of 1,085 children were included with a median age of 1.6 years (interquartile range 0.8-3.4); 73 children (7%) had pneumonia and 98 children (9%) had other SBIs. The Feverkidstool showed good discriminative ability in this new population. After adding procalcitonin to the Feverkidstool, c-statistic for "pneumonia" increased from 0.85 (95% confidence interval (CI) 0.76-0.94) to 0.86 (0.77-0.94) and for "other SBI" from 0.81 (0.73-0.90) to 0.83 (0.75- 0.91). A model with clinical features and procalcitonin performed similar to the Feverkidstool.ConclusionThis study confirms the external validity of the Feverkidstool, with CRP and procalcitonin being equally valuable for predicting SBI in our population of febrile children. Our findings do not support routine dual use of CRP and procalcitonin.

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.

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.