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Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients

BACKGROUND: Triage trauma scores are utilised to determine patient disposition, interventions and prognostication in the care of trauma patients. Heart rate variability (HRV) and heart rate complexity (HRC) reflect the autonomic nervous system and are derived from electrocardiogram (ECG) analysis. I...

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Autores principales: Kumar, Aravin, Liu, Nan, Koh, Zhi Xiong, Chiang, Jayne Jie Yi, Soh, Yuda, Wong, Ting Hway, Ho, Andrew Fu Wah, Tagami, Takashi, Fook-Chong, Stephanie, Ong, Marcus Eng Hock
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471773/
https://www.ncbi.nlm.nih.gov/pubmed/31019983
http://dx.doi.org/10.1186/s41038-019-0147-2
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author Kumar, Aravin
Liu, Nan
Koh, Zhi Xiong
Chiang, Jayne Jie Yi
Soh, Yuda
Wong, Ting Hway
Ho, Andrew Fu Wah
Tagami, Takashi
Fook-Chong, Stephanie
Ong, Marcus Eng Hock
author_facet Kumar, Aravin
Liu, Nan
Koh, Zhi Xiong
Chiang, Jayne Jie Yi
Soh, Yuda
Wong, Ting Hway
Ho, Andrew Fu Wah
Tagami, Takashi
Fook-Chong, Stephanie
Ong, Marcus Eng Hock
author_sort Kumar, Aravin
collection PubMed
description BACKGROUND: Triage trauma scores are utilised to determine patient disposition, interventions and prognostication in the care of trauma patients. Heart rate variability (HRV) and heart rate complexity (HRC) reflect the autonomic nervous system and are derived from electrocardiogram (ECG) analysis. In this study, we aimed to develop a model incorporating HRV and HRC, to predict the need for life-saving interventions (LSI) in trauma patients, within 24 h of emergency department presentation. METHODS: We included adult trauma patients (≥ 18 years of age) presenting at the emergency department of Singapore General Hospital between October 2014 and October 2015. We excluded patients who had non-sinus rhythms and larger proportions of artefacts and/or ectopics in ECG analysis. We obtained patient demographics, laboratory results, vital signs and outcomes from electronic health records. We conducted univariate and multivariate analyses for predictive model building. RESULTS: Two hundred and twenty-five patients met inclusion criteria, in which 49 patients required LSIs. The LSI group had a higher proportion of deaths (10, 20.41% vs 1, 0.57%, p < 0.001). In the LSI group, the mean of detrended fluctuation analysis (DFA)-α1 (1.24 vs 1.12, p = 0.045) and the median of DFA-α2 (1.09 vs 1.00, p = 0.027) were significantly higher. Multivariate stepwise logistic regression analysis determined that a lower Glasgow Coma Scale, a higher DFA-α1 and higher DFA-α2 were independent predictors of requiring LSIs. The area under the curve (AUC) for our model (0.75, 95% confidence interval, 0.66–0.83) was higher than other scoring systems and selected vital signs. CONCLUSIONS: An HRV/HRC model outperforms other triage trauma scores and selected vital signs in predicting the need for LSIs but needs to be validated in larger patient populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41038-019-0147-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-64717732019-04-24 Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients Kumar, Aravin Liu, Nan Koh, Zhi Xiong Chiang, Jayne Jie Yi Soh, Yuda Wong, Ting Hway Ho, Andrew Fu Wah Tagami, Takashi Fook-Chong, Stephanie Ong, Marcus Eng Hock Burns Trauma Research Article BACKGROUND: Triage trauma scores are utilised to determine patient disposition, interventions and prognostication in the care of trauma patients. Heart rate variability (HRV) and heart rate complexity (HRC) reflect the autonomic nervous system and are derived from electrocardiogram (ECG) analysis. In this study, we aimed to develop a model incorporating HRV and HRC, to predict the need for life-saving interventions (LSI) in trauma patients, within 24 h of emergency department presentation. METHODS: We included adult trauma patients (≥ 18 years of age) presenting at the emergency department of Singapore General Hospital between October 2014 and October 2015. We excluded patients who had non-sinus rhythms and larger proportions of artefacts and/or ectopics in ECG analysis. We obtained patient demographics, laboratory results, vital signs and outcomes from electronic health records. We conducted univariate and multivariate analyses for predictive model building. RESULTS: Two hundred and twenty-five patients met inclusion criteria, in which 49 patients required LSIs. The LSI group had a higher proportion of deaths (10, 20.41% vs 1, 0.57%, p < 0.001). In the LSI group, the mean of detrended fluctuation analysis (DFA)-α1 (1.24 vs 1.12, p = 0.045) and the median of DFA-α2 (1.09 vs 1.00, p = 0.027) were significantly higher. Multivariate stepwise logistic regression analysis determined that a lower Glasgow Coma Scale, a higher DFA-α1 and higher DFA-α2 were independent predictors of requiring LSIs. The area under the curve (AUC) for our model (0.75, 95% confidence interval, 0.66–0.83) was higher than other scoring systems and selected vital signs. CONCLUSIONS: An HRV/HRC model outperforms other triage trauma scores and selected vital signs in predicting the need for LSIs but needs to be validated in larger patient populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41038-019-0147-2) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-18 /pmc/articles/PMC6471773/ /pubmed/31019983 http://dx.doi.org/10.1186/s41038-019-0147-2 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Kumar, Aravin
Liu, Nan
Koh, Zhi Xiong
Chiang, Jayne Jie Yi
Soh, Yuda
Wong, Ting Hway
Ho, Andrew Fu Wah
Tagami, Takashi
Fook-Chong, Stephanie
Ong, Marcus Eng Hock
Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
title Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
title_full Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
title_fullStr Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
title_full_unstemmed Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
title_short Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
title_sort development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471773/
https://www.ncbi.nlm.nih.gov/pubmed/31019983
http://dx.doi.org/10.1186/s41038-019-0147-2
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