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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 betwe...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9906196/ https://www.ncbi.nlm.nih.gov/pubmed/36760240 http://dx.doi.org/10.21037/atm-22-3303 |
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author | Chong, Shu-Ling Niu, Chenglin Piragasam, Rupini Koh, Zhi Xiong Guo, Dagang Lee, Jan Hau Ong, Gene Yong-Kwang Ong, Marcus Eng Hock Liu, Nan |
author_facet | Chong, Shu-Ling Niu, Chenglin Piragasam, Rupini Koh, Zhi Xiong Guo, Dagang Lee, Jan Hau Ong, Gene Yong-Kwang Ong, Marcus Eng Hock Liu, Nan |
author_sort | Chong, Shu-Ling |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9906196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-99061962023-02-08 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 Chong, Shu-Ling Niu, Chenglin Piragasam, Rupini Koh, Zhi Xiong Guo, Dagang Lee, Jan Hau Ong, Gene Yong-Kwang Ong, Marcus Eng Hock Liu, Nan Ann Transl Med Original Article 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. AME Publishing Company 2022-12-16 2023-01-15 /pmc/articles/PMC9906196/ /pubmed/36760240 http://dx.doi.org/10.21037/atm-22-3303 Text en 2023 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Chong, Shu-Ling Niu, Chenglin Piragasam, Rupini Koh, Zhi Xiong Guo, Dagang Lee, Jan Hau Ong, Gene Yong-Kwang Ong, Marcus Eng Hock Liu, Nan 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9906196/ https://www.ncbi.nlm.nih.gov/pubmed/36760240 http://dx.doi.org/10.21037/atm-22-3303 |
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