Skip to main content

Volume 16 Supplement 3

Sepsis 2012

  • Poster presentation
  • Open access
  • Published:

Quantified temporal changes of heart rate variability when developing SIRS

Background

Heart rate variability (HRV) has been reported to gradually decrease long before the onset of sepsis [1, 2]. Since the development of systemic inflammatory response syndrome (SIRS) has been included in the definition of sepsis, we compared temporal changes of HRV depending on the SIRS state coming after.

Methods

Vital data of patients admitted in ICU were downloaded from bedside monitoring systems. No specific registration criteria for disease were defined. Vital signs regarding SIRS evaluation - that is, hear rate, respiration rate, and core temperature - are recorded every 10 seconds, 0.1 Hz. By taking the median of 60 data, the SIRS state was determined for each hour, ignoring the count of white blood cells. The sampling rate of ECG data is 500 Hz, and the HRV for each minute (0.017 Hz) was calculated from that. Abnormal heartbeats and trends were eliminated using a stochastic model, and the power spectrum was derived with an autoregressive model [3]. We considered the integral value within 0.04 to 0.4 Hz as an estimate of HRV. Temporal linear trends of HRV were quantified as Spearman's correlation coefficient. Note that the target period for HRV trend evaluation is immediately before the SIRS evaluation period. The following software was used: IBM SPSS version 19, R version 2.15.0, and G*Power Version 3.1.4.

Results

Forty-nine patients were registered, and 34 patients (69.4%) suffered from sepsis. The average age was 64.3 years, and the average ICU stay was 31.4 days, ranging from 3 to 113 days. The number of data where a SIRS state was identified was 21,919, and 56.5% (12,380) were evaluated as SIRS-positive. Immediately before SIRS-positive states, the mean value of the correlation coefficients was -0.00234 (SD 0.321). The mean value before SIRS-negative states was 0.0201 (SD 0.309). The mean difference was 0.0224 (P < 0.05), and the statistical power was 99.9%.

Conclusion

Our analysis shows that the mean trend of the HRV value immediately before developing SIRS was negative, and the mean trend of HRV immediately before a non-SIRS state was positive. This result does support previous results. For sepsis monitoring, however, further investigation is mandatory. This result only suggests a stronger negative trend of HRV when developing SIRS for the next period, regardless of the current state.

References

  1. Moriguchi T, Hirasawa H, Oda S, Tateishi Y: [Analysis of heart rate variability is a useful tool to predict the occurrence of septic shock in the patients with severe sepsis]. Nihon Rinsho 2004, 62: 2285-2290.

    PubMed  Google Scholar 

  2. Ahmad S, Ramsay T, Huebsch L, Flanagan S, McDiarmid S, Batkin I, McIntyre L, Sundaresan SR, Maziak DE, Shamji FM, Hebert P, Fergusson D, Tinmouth A, Seely AJE: Continuous multi-parameter heart rate variability analysis heralds onset of sepsis in adults. PLoS One 2009, 4: e6642. 10.1371/journal.pone.0006642

    Article  PubMed Central  PubMed  Google Scholar 

  3. Yokota Y, Kawamura Y, Matsumaru N, Shirai K: Premonitory symptom of septic shock in heart rate variability. In 5th Kuala Lumpur International Conference on Biomedical Engineering 2011. Volume 35 of IFMBE Proceedings. Edited by: Osman NAA, Abas WABW, Wahab AKA, Ting HN, Magjarevic R. Berlin: Springer; 2011:552-555.

    Chapter  Google Scholar 

Download references

Acknowledgements

Supported by the Ministry of Education, Culture, Sports, Science and Technology Japan as a part of Regional Innovation Cluster Program (City Area Type) in Southern Gifu Area.

Author information

Authors and Affiliations

Authors

Rights and permissions

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

Reprints and permissions

About this article

Cite this article

Matsumaru, N., Shirai, K., Kawamura, Y. et al. Quantified temporal changes of heart rate variability when developing SIRS. Crit Care 16 (Suppl 3), P109 (2012). https://doi.org/10.1186/cc11796

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/cc11796

Keywords