ArticleAnnals of translational medicine2023
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.
Article in Annals of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 citing papers in PubMed.
- Singapore Housing Index and prevalence of serious bacterial infections among febrile infants.Frontiers in pediatrics · 2026Article
- Scoping review of clinical decision aids in the assessment and management of febrile infants under 90 days of age.BMC pediatrics · 2025Article
- Establishing normative values for short-term heart rate variability indices in healthy infants in the emergency department.Annals of translational medicine · 2025Article
- It doesn't matter what they say in the papers… It's still ROC and roll to me.Annals of translational medicine · 2023Article
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9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
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.
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