Analysis of emergency department prediction tools in evaluating febrile young infants at risk for serious infections

Validation and comparison of the PECARN rule, Step-by-Step approach and Lab-score for predicting serious and invasive bacterial infections in young febrile infants

Introduction: Differentiating infants with serious bacterial infections (SBIs) or invasive bacterial infections (IBIs) from those without remains a challenge. We sought to compare the diagnostic performances of single biomarkers (absolute neutrophil count [ANC], C-reactive protein [CRP] and procalcitonin [PCT]) and 4 diagnostic approaches comprising Lab-score, Step-by-Step approach (original and modified) and Pediatric Emergency Care Applied Research Network (PECARN) rule. Method: This is a prospective cohort study involving infants 0–90 days of age who presented to an emergency department from July 2020 to August 2021. SBIs were defined as bacterial meningitis, bacteraemia and/or urinary tract infections. IBIs were defined as bacteraemia and/or bacterial meningitis. We evaluated the performances of Lab-score, Step-by-Step (original and modified) and PECARN rule in predicting SBIs and IBIs. Results: We analysed a total of 258 infants, among whom 86 (33.3%) had SBIs and 9 (3.5%) had IBIs. In predicting SBIs, ANC ≥4.09 had the highest sensitivity and negative predictive value (NPV), while PCT ≥1.7 had the highest specificity and positive predictive value (PPV). CRP ≥20 achieved the highest area under receiver operating characteristic curve (AUC) of 0.741 (95% confidence interval [CI] 0.672–0.810). The Step-by-Step (original) approach had the highest sensitivity (97.7%). Lab-score had the highest AUC of 0.695 (95% CI 0.621–0.768), compared to PECARN rule at 0.625 (95% CI 0.556–0.694) and Step-by-Step (original) at 0.573 (95% CI 0.502–0.644). In predicting IBIs, PCT ≥1.7 had the highest sensitivity, specificity, PPV and NPV. The Step-by-Step (original and modified) approach had the highest sensitivity of 100%. Lab-score had the highest AUC of 0.854 (95% CI 0.731–0.977) compared to PECARN rule at 0.589 (95% CI 0.420–0.758) and Step-by-Step at 0.562 (95% CI 0.392–0.732). Conclusion: CRP strongly predicted SBIs, and PCT strongly predicted IBI. The Step-by-Step approach had the highest sensitivity and NPV, while Lab-score had the highest specificity and AUC in predicting SBIs and IBIs. Keywords: Biomarkers, diagnostic approaches, febrile infants, Lab-score, PECARN rule, Step-by-Step approach

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.

Delays in Time-To-Antibiotics for Young Febrile Infants With Serious Bacterial Infections: A Prospective Single-Center Study

INTRODUCTION

Fear of missed serious bacterial infections (SBIs) results in many febrile young infants receiving antibiotics. We aimed to compare the time to antibiotics between infants with SBIs and those without.

MATERIALS AND METHODS

We recruited febrile infants ≤ 90 days old seen in the emergency department (ED) between December 2017 and April 2021. SBI was defined as (1) urinary tract infection, (2) bacteremia or (3) bacterial meningitis. We compared the total time (median with interquartile range, IQR) from ED arrival to infusion of antibiotics, divided into (i) time from triage to decision for antibiotics and (ii) time from decision for antibiotics to administration of antibiotics.

RESULTS

We analyzed 81 and 266 infants with and without SBIs. Median age of those with and without SBIs were 44 (IQR 19-72) and 29 (IQR 7-56) days, respectively (p = 0.002). All infants with SBIs and 168/266 (63.2%) infants without SBIs received antibiotics. Among 249 infants who received antibiotics, the median total time from ED arrival to infusion of antibiotics was 277.0 (IQR 236.0-385.0) mins for infants with SBIs and 304.5 (IQR 238.5-404.0) mins for those without (p = 0.561). The median time to decision for antibiotics was 156.0 (IQR 115.0-255.0) mins and 144.0 (IQR 105.5-211.0) mins, respectively (p = 0.175). Following decision for antibiotics, infants with SBIs received antibiotics much faster compared to those without [107.0 (IQR 83.0-168.0) vs. 141.0 (94.0-209.5) mins, p = 0.017].

CONCLUSION

There was no difference in total time taken to antibiotics between infants with SBIs and without SBIs. Both recognition and administration delays were observed. While all infants with SBIs were adequately treated, more than half of the infants without SBIs received unnecessary antibiotics. This highlights the challenge in managing young febrile infants at initial presentation, and demonstrates the need to examine various aspects of care to improve the overall timeliness to antibiotics.

Early prediction of serious infections in febrile infants incorporating heart rate variability in an emergency department: a pilot study

BACKGROUND

Early differentiation of febrile young infants with from those without serious infections (SIs) remains a diagnostic challenge. We sought to (1) compare vital signs and heart rate variability (HRV) parameters between febrile infants with versus without SIs, (2) assess the performance of HRV and vital signs with reference to current triage tools and (3) compare HRV and vital signs to HRV, vital signs and blood biomarkers, when predicting for the presence of SIs.

METHODS

Using a prospective observational design, we recruited patients <3 months old presenting to a tertiary paediatric ED in Singapore from December 2018 through November 2019. We obtained patient demographic characteristics, triage assessment (including the Severity Index Score (SIS)), HRV parameters (time, frequency and non-linear domains) and laboratory results. We performed multivariable logistic regression analyses to predict the presence of an SI, using area under the curve (AUC) with the corresponding 95% CI to assess predictive capability.

RESULTS

Among 203 infants with a mean age of 38.4 days (SD 27.6), 67 infants (33.0%) had an SI. There were significant differences in the time, frequency and non-linear domains of HRV parameters between infants with versus without SIs. In predicting SIs, gender, temperature and the HRV non-linear parameter Poincaré plot SD2 (AUC 0.78, 95% CI 0.71 to 0.84) performed better than SIS alone (AUC 0.61, 95% CI 0.53 to 0.68). Model performance improved with the addition of absolute neutrophil count and C reactive protein (AUC 0.82, 95% CI 0.76 to 0.89).

CONCLUSION

An exploratory prediction model incorporating HRV and biomarkers improved prediction of SIs. Further research is needed to assess if HRV can identify which young febrile infants have an SI at ED triage.

TRIAL REGISTRATION NUMBER

NCT04103151.

Infants 21-90 days presenting with a possible serious bacterial infection - are evaluation algorithms from high income countries applicable in the South African public health sector?

BACKGROUND

Young infants with a possible serious bacterial infection (SBI) are a very common presentation to emergency centres (ECs). It is often difficult to distinguish clinically between self-limiting viral infections and an SBI. Available evaluation algorithms to assist clinicians are mostly from high-income countries. Data to inform clinical practice in low- and middle-income countries are lacking.

OBJECTIVES

To determine the period prevalence of SBI and invasive bacterial infection (IBI) and describe current practice in the assessment and management of young infants aged 21-90 days presenting with a possible SBI to a Paediatric Emergency centre (PEC) in Cape Town, South Africa.

METHODS

A retrospective cross-sectional review of infants 21-90 days old presenting to the Tygerberg Hospital PED between 1 January 2016 and 31 May 2016.

RESULTS

A total of 248 infants 21-90 days were included in the study. Sixty-two patients (25%, 95% CI 20-30) had an SBI and 13 (5.2%, 95% CI 3-8) had an IBI. One hundred and sixty-five infants had a possible SBI based on WHO IMCI criteria. The sensitivity of the WHO IMCI criteria in detecting SBI was 82.3% (95% CI 70.5-90.8) and the specificity 38.7% (95% CI 31.7-46.1). More than half (51.2%) of the infants received antibiotics within the 48 h prior to presentation, of which 33.5% included intramuscular injection of Ceftriaxone. Only 20 (8.0%) patients in this age group were discharged home after initial evaluation. A significant relationship was noted between fever and the risk of SBI (p-value 0.010) and IBI (p-value 0.009). There also appeared to be a significant relationship between nutritional status and IBI (p-value 0.013).

CONCLUSION

Period prevalence of SBI and IBI was higher compared to that published in the literature. Validated evaluation algorithms to stratify risk of SBI are needed to assist clinicians in diagnosing and managing infants appropriately in low- and middle-income settings.