Pyrexia in a young infant - is height of fever associated with serious bacterial infection?

Delayed presentation is associated with serious bacterial infections among febrile infants: A prospective cohort study

Introduction

Febrile young infants are at risk of serious bacterial infections (SBIs), which are potentially life-threatening. This study aims to investigate the association between delayed presentation and the risk of SBIs among febrile infants.

Method

We performed a prospective cohort study on febrile infants ≤90 days old presenting to a Singapore paediatric emergency department (ED) between November 2017 and July 2022. We defined delayed presentation as presentation to the ED >24 hours from fever onset. We compared the proportion of SBIs in infants who had delayed presentation compared to those without, and their clinical outcomes. We also performed a multivariable logistic regression to study if delayed presentation was independently associated with the presence of SBIs.

Results

Among 1911 febrile infants analysed, 198 infants (10%) had delayed presentation. Febrile infants with delayed presentation were more likely to have SBIs (28.8% versus [vs] 16.3%, P<0.001). A higher proportion of infants with delayed presentation required intravenous antibiotics (64.1% vs 51.9%, P=0.001). After adjusting for age, sex and severity index score, delayed presentation was independently associated with the presence of SBI (adjusted odds ratio [AOR] 1.78, 95% confidence interval 1.26-2.52, P<0.001).

Conclusion

Febrile infants with delayed presentation are at higher risk of SBI. Frontline clinicians should take this into account when assessing febrile infants.

Febrile infants risk score at triage (FIRST) for the early identification of serious bacterial infections

We aimed to derive the Febrile Infants Risk Score at Triage (FIRST) to quantify risk for serious bacterial infections (SBIs), defined as bacteremia, meningitis and urinary tract infections. We performed a prospective observational study on febrile infants < 3 months old at a tertiary hospital in Singapore between 2018 and 2021. We utilized machine learning and logistic regression to derive 2 models: FIRST, based on patient demographics, vital signs and history, and FIRST + , adding laboratory results to the same variables. SBIs were diagnosed in 224/1002 (22.4%) infants. Among 994 children with complete data, age (adjusted odds ratio [aOR] 1.01 95%CI 1.01-1.02, p < 0.001), high temperature (aOR 2.22 95%CI 1.69-2.91, p < 0.001), male sex (aOR 2.62 95%CI 1.86-3.70, p < 0.001) and fever of ≥ 2 days (aOR 1.79 95%CI 1.18-2.74, p = 0.007) were independently associated with SBIs. For FIRST + , abnormal urine leukocyte esterase (aOR 16.46 95%CI 10.00-27.11, p < 0.001) and procalcitonin (aOR 1.05 95%CI 1.01-1.09, p = 0.009) were further identified. A FIRST + threshold of ≥ 15% predicted risk had a sensitivity of 81.8% (95%CI 70.5-91.0%) and specificity of 65.6% (95%CI 57.8-72.7%). In the testing dataset, FIRST + had an area under receiver operating characteristic curve of 0.87 (95%CI 0.81-0.94). These scores can potentially guide triage and prioritization of febrile infants.

Adding heart rate n-variability (HRnV) to clinical assessment potentially improves prediction of serious bacterial infections in young febrile infants at the emergency department: a prospective observational study

Background

We aim to investigate the utility of heart rate variability (HRV) and heart rate n-variability (HRnV) in addition to vital signs and blood biomarkers, among febrile young infants at risk of serious bacterial infections (SBIs).

Methods

We performed a prospective observational study between December 2017 and November 2021 in a tertiary paediatric emergency department (ED). We included febrile infants <90 days old with a temperature ≥38 ℃. We obtained HRV and HRnV parameters via a single lead electrocardiogram. HRV measures beat-to-beat (R-R) oscillation and reflects autonomic nervous system (ANS) regulation. HRnV includes overlapping and non-overlapping R-R intervals and provides additional physiological information. We defined SBIs as meningitis, bacteraemia and urinary tract infections (UTIs). We performed area under curve (AUC) analysis to assess predictive performance.

Results

We recruited 330 and analysed 312 infants. The median age was 35.5 days (interquartile range 13.0-61.0); 74/312 infants (23.7%) had SBIs with the most common being UTIs (66/72, 91.7%); 2 infants had co-infections. No patients died and 32/312 (10.3%) received fluid resuscitation. Adding HRV and HRnV to demographics and vital signs at ED triage successively improved the AUC from 0.765 [95% confidence interval (CI): 0.705-0.825] to 0.776 (95% CI: 0.718-0.835) and 0.807 (95% CI: 0.752-0.861) respectively. The final model including demographics, vital signs, HRV, HRnV and blood biomarkers had an AUC of 0.874 (95% CI: 0.828-0.921).

Conclusions

Addition of HRV and HRnV to current assessment tools improved the prediction of SBIs among febrile infants at ED triage. We intend to validate our findings and translate them into tools for clinical care in the ED.