Journal of Clinical Monitoring and Computing

, Volume 33, Issue 1, pp 31–38 | Cite as

Complexity of preoperative blood pressure dynamics: possible utility in cardiac surgical risk assessment

  • Teresa S. Henriques
  • Madalena D. Costa
  • Pooja Mathur
  • Priyam Mathur
  • Roger B. Davis
  • Murray A. Mittleman
  • Kamal R. Khabbaz
  • Ary L. Goldberger
  • Balachundhar SubramaniamEmail author
Original Research


Complexity measures are intended to assess the cardiovascular system’s capacity to respond to stressors. We sought to determine if decreased BP complexity is associated with increased estimated risk as obtained from two standard instruments: the Society of Thoracic Surgeons’ (STS) Risk of Mortality and Morbidity Index and the European System for Cardiac Operative Risk Evaluation Score (EuroSCORE II). In this observational cohort study, preoperative systolic, diastolic, mean (MAP) and pulse pressure (PP) time series were derived in 147 patients undergoing cardiac surgery. The complexity of the fluctuations of these four variables was quantified using multiscale entropy (MSE) analysis. In addition, the traditional time series measures, mean and standard deviation (SD) were also computed. The relationships between time series measures and the risk indices (after logarithmic transformation) were then assessed using nonparametric (Spearman correlation, rs) and linear regression methods. A one standard deviation change in the complexity of systolic, diastolic and MAP time series was negatively associated (p < 0.05) with the STS and EuroSCORE indices in both unadjusted (21–34%) and models adjusted for age, gender and SD of the BP time series (15–31%). The mean and SD of BP time series were not significantly associated with the risk index except for a positive association with the SD of the diastolic BP. Lower preoperative BP complexity was associated with a higher estimated risk of adverse cardiovascular outcomes and may provide a novel approach to assessing cardiovascular risk. Future studies are needed to determine whether dynamical risk indices can improve current risk prediction tools.


Blood pressure complexity STS EuroSCORE Risk Multiscale entropy 



This research was supported in part by a grant from the National Institutes of Health (5R01GM098406 and 5R01GM104987), as well as grants from the G. Harold and Leila Y. Mathers Charitable Foundation and James S. McDonnell Foundation.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Supplementary material

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Supplementary material 1 (DOCX 140 KB)
10877_2018_133_MOESM2_ESM.docx (2.4 mb)
Supplementary material 2 (DOCX 2443 KB)


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Teresa S. Henriques
    • 1
    • 2
  • Madalena D. Costa
    • 2
  • Pooja Mathur
    • 1
  • Priyam Mathur
    • 1
  • Roger B. Davis
    • 3
  • Murray A. Mittleman
    • 4
  • Kamal R. Khabbaz
    • 5
  • Ary L. Goldberger
    • 2
  • Balachundhar Subramaniam
    • 1
    Email author
  1. 1.Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonUSA
  2. 2.Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and MedicineBeth Israel Deaconess Medical CenterBostonUSA
  3. 3.Division of General Medicine and Primary Care, Department of MedicineBeth Israel Deaconess Medical CenterBostonUSA
  4. 4.Department of EpidemiologyHarvard School of Public HealthBostonUSA
  5. 5.Division of Cardiac Surgery, Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonUSA

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