Skip to main content
Top
Published in: Journal of Clinical Monitoring and Computing 1/2019

01-02-2019 | Original Research

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

Authors: Teresa S. Henriques, Madalena D. Costa, Pooja Mathur, Priyam Mathur, Roger B. Davis, Murray A. Mittleman, Kamal R. Khabbaz, Ary L. Goldberger, Balachundhar Subramaniam

Published in: Journal of Clinical Monitoring and Computing | Issue 1/2019

Login to get access

Abstract

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.
Appendix
Available only for authorised users
Literature
1.
go back to reference Cornwell LD, Omer S, Rosengart T, Holman WL, Bakaeen FG. Changes over time in risk profiles of patients who undergo coronary artery bypass graft surgery: the veterans’ affairs surgical quality improvement program (VASQIP). JAMA Surg. 2015;150(4):308–15.CrossRefPubMed Cornwell LD, Omer S, Rosengart T, Holman WL, Bakaeen FG. Changes over time in risk profiles of patients who undergo coronary artery bypass graft surgery: the veterans’ affairs surgical quality improvement program (VASQIP). JAMA Surg. 2015;150(4):308–15.CrossRefPubMed
2.
go back to reference Dewey TM, Brown D, Ryan WH, Herbert MA, Prince SL, Mack MJ. Reliability of risk algorithms in predicting early and late operative outcomes in high-risk patients undergoing aortic valve replacement. Thorac Cardiovasc Surg. 2008;135(1):180–87.CrossRef Dewey TM, Brown D, Ryan WH, Herbert MA, Prince SL, Mack MJ. Reliability of risk algorithms in predicting early and late operative outcomes in high-risk patients undergoing aortic valve replacement. Thorac Cardiovasc Surg. 2008;135(1):180–87.CrossRef
3.
go back to reference Pinna-Pintor P, Bobbio M, Colangelo S, Veglia F, Giammaria M, Maisano F, Alfieri O. Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients. Eur J Cardiothorac Surg. 2002;21(2):199–204.CrossRefPubMed Pinna-Pintor P, Bobbio M, Colangelo S, Veglia F, Giammaria M, Maisano F, Alfieri O. Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients. Eur J Cardiothorac Surg. 2002;21(2):199–204.CrossRefPubMed
4.
go back to reference Maslow A, Casey P, Poppas A, Schwartz C, Singh A. Aortic valve replacement with or without coronary artery bypass graft surgery: the risk of surgery in patients ≥ 80 years old. J Cardiothorac Vasc Anesth. 2015;24(1):18–24.CrossRef Maslow A, Casey P, Poppas A, Schwartz C, Singh A. Aortic valve replacement with or without coronary artery bypass graft surgery: the risk of surgery in patients ≥ 80 years old. J Cardiothorac Vasc Anesth. 2015;24(1):18–24.CrossRef
5.
go back to reference Subramaniam B, Khabbaz KR, Heldt T, Lerner AB, Mittleman MA, Davis RB, Goldberger AL, Costa MD. Blood pressure variability: can nonlinear dynamics enhance risk assessment during cardiovascular surgery? J Cardiothorac Vasc Anesth. 2014;28(2):392–97.CrossRefPubMedPubMedCentral Subramaniam B, Khabbaz KR, Heldt T, Lerner AB, Mittleman MA, Davis RB, Goldberger AL, Costa MD. Blood pressure variability: can nonlinear dynamics enhance risk assessment during cardiovascular surgery? J Cardiothorac Vasc Anesth. 2014;28(2):392–97.CrossRefPubMedPubMedCentral
6.
go back to reference Kirkness CJ, Burr RL, Mitchell PH. Intracranial and blood pressure variability and long-term outcome after aneurysmal sub-arachnoid hemorrhage. Am J Crit Care. 2009;18(3):241–51.CrossRefPubMedPubMedCentral Kirkness CJ, Burr RL, Mitchell PH. Intracranial and blood pressure variability and long-term outcome after aneurysmal sub-arachnoid hemorrhage. Am J Crit Care. 2009;18(3):241–51.CrossRefPubMedPubMedCentral
7.
go back to reference Aronson S, Stafford-Smith M, Phillips-Bute B, Shaw A, Gaca J, Newman M. Intraoperative systolic blood pressure variability predicts 30-day mortality in aortocoronary bypass surgery patients. Anesthesiology. 2010;113(2):305–12.CrossRefPubMed Aronson S, Stafford-Smith M, Phillips-Bute B, Shaw A, Gaca J, Newman M. Intraoperative systolic blood pressure variability predicts 30-day mortality in aortocoronary bypass surgery patients. Anesthesiology. 2010;113(2):305–12.CrossRefPubMed
8.
go back to reference Mancia G. Short-and long-term blood pressure variability present and future. Hypertension. 2012;60(2):512–17.CrossRefPubMed Mancia G. Short-and long-term blood pressure variability present and future. Hypertension. 2012;60(2):512–17.CrossRefPubMed
9.
go back to reference Floras JS. Blood pressure variability: a novel and important risk factor. Can J Cardiol. 2013;29(5):557–63.CrossRefPubMed Floras JS. Blood pressure variability: a novel and important risk factor. Can J Cardiol. 2013;29(5):557–63.CrossRefPubMed
10.
go back to reference Parati G, Ochoa JE, Lombardi C, Bilo G. Assessment and management of blood-pressure variability. Nat Rev Cardiol 2013; 10(3):143–55.CrossRefPubMed Parati G, Ochoa JE, Lombardi C, Bilo G. Assessment and management of blood-pressure variability. Nat Rev Cardiol 2013; 10(3):143–55.CrossRefPubMed
11.
go back to reference Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett. 2002;89(6):068102.CrossRefPubMed Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett. 2002;89(6):068102.CrossRefPubMed
12.
go back to reference Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of biological signals. Phys Rev E. 2005;71(2):021906.CrossRef Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of biological signals. Phys Rev E. 2005;71(2):021906.CrossRef
13.
go back to reference Costa M, Ghiran I, Peng CK, Nicholson-Weller A, Goldberger AL. Complex dynamics of human red blood cell flickering: alterations with in vivo aging. Phys Rev E. 2008;78(2):020901.CrossRef Costa M, Ghiran I, Peng CK, Nicholson-Weller A, Goldberger AL. Complex dynamics of human red blood cell flickering: alterations with in vivo aging. Phys Rev E. 2008;78(2):020901.CrossRef
14.
go back to reference Bartolák-Suki E, Imsirovic J, Parameswaran H, Wellman TJ, Martinez N, Allen PG, Frey U, Suki B. Fluctuation-driven mechanotransduction regulates mitochondrial-network structure and function. Nat Mater. 2015;14(10):1049.CrossRefPubMed Bartolák-Suki E, Imsirovic J, Parameswaran H, Wellman TJ, Martinez N, Allen PG, Frey U, Suki B. Fluctuation-driven mechanotransduction regulates mitochondrial-network structure and function. Nat Mater. 2015;14(10):1049.CrossRefPubMed
15.
go back to reference Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: components of a new Research Resource for Complex Physiologic Signals. Circulation. 2000;101(23):e215–20.CrossRefPubMed Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: components of a new Research Resource for Complex Physiologic Signals. Circulation. 2000;101(23):e215–20.CrossRefPubMed
16.
go back to reference Zong W, Heldt T, Moody GB, Mark RG. An open-source algorithm to detect onset of arterial blood pressure pulses. Comput Cardiol 2003;2003:259–62. Zong W, Heldt T, Moody GB, Mark RG. An open-source algorithm to detect onset of arterial blood pressure pulses. Comput Cardiol 2003;2003:259–62.
17.
go back to reference Saeed M, Villarroel M, Reisner AT, Clifford G, Lehman LW, Moody G, Heldt T, Kyaw TH, Moody B, Mark RG. Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II): a public-access intensive care unit database. Crit Care Med. 2011;39(5):952.CrossRefPubMedPubMedCentral Saeed M, Villarroel M, Reisner AT, Clifford G, Lehman LW, Moody G, Heldt T, Kyaw TH, Moody B, Mark RG. Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II): a public-access intensive care unit database. Crit Care Med. 2011;39(5):952.CrossRefPubMedPubMedCentral
18.
go back to reference Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;278(6):H2039–49.CrossRefPubMed Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;278(6):H2039–49.CrossRefPubMed
19.
go back to reference Anderson RP. First publications from the Society of Thoracic Surgeons national database. Ann Thorac Surg. 1994;57(1):6–7.CrossRefPubMed Anderson RP. First publications from the Society of Thoracic Surgeons national database. Ann Thorac Surg. 1994;57(1):6–7.CrossRefPubMed
20.
go back to reference Roques F, Nashef SAM, Michel P, Gauducheau E, De Vincentiis C, Baudet E, Cortina J, David M, Faichney A, Gavrielle F, Gams E, Harjula A, Jones MT, Pinna-Pintor P, Salamon R, Thulin L. Risk factors and outcome in European cardiac surgery: analysis of the EuroSCORE multinational database of 19030 patients. Eur J Cardiothorac Surg. 1999;15(6):816–23.CrossRefPubMed Roques F, Nashef SAM, Michel P, Gauducheau E, De Vincentiis C, Baudet E, Cortina J, David M, Faichney A, Gavrielle F, Gams E, Harjula A, Jones MT, Pinna-Pintor P, Salamon R, Thulin L. Risk factors and outcome in European cardiac surgery: analysis of the EuroSCORE multinational database of 19030 patients. Eur J Cardiothorac Surg. 1999;15(6):816–23.CrossRefPubMed
21.
go back to reference Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. EuroSCORE Study Group: European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg. 1999;16(1):9–13.CrossRefPubMed Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. EuroSCORE Study Group: European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg. 1999;16(1):9–13.CrossRefPubMed
22.
go back to reference Nilsson J, Algotsson L, Höglund P, Lührs C, Brandt J. Early mortality in coronary bypass surgery: the EuroSCORE versus The Society of Thoracic Surgeons risk algorithm. Ann Thorac Surg. 2004;77(4):1235–39.CrossRefPubMed Nilsson J, Algotsson L, Höglund P, Lührs C, Brandt J. Early mortality in coronary bypass surgery: the EuroSCORE versus The Society of Thoracic Surgeons risk algorithm. Ann Thorac Surg. 2004;77(4):1235–39.CrossRefPubMed
23.
go back to reference Ad N, Barnett SD, Speir AM. The performance of the EuroSCORE and the Society of Thoracic Surgeons mortality risk score: the gender factor. Interact Cardiovasc Thorac Surg. 2007;6(2):192–95.CrossRefPubMed Ad N, Barnett SD, Speir AM. The performance of the EuroSCORE and the Society of Thoracic Surgeons mortality risk score: the gender factor. Interact Cardiovasc Thorac Surg. 2007;6(2):192–95.CrossRefPubMed
24.
go back to reference Kunt AG, Kurtcephe M, Hidiroglu M, Cetin L, Kucuker A, Bakuy V, Akar AR, Sener E. Comparison of original EuroSCORE, EuroSCORE II and STS risk models in a Turkish cardiac surgical cohort. Interact Cardiovasc Thorac Surg. 2013;16(5):625–29.CrossRefPubMedPubMedCentral Kunt AG, Kurtcephe M, Hidiroglu M, Cetin L, Kucuker A, Bakuy V, Akar AR, Sener E. Comparison of original EuroSCORE, EuroSCORE II and STS risk models in a Turkish cardiac surgical cohort. Interact Cardiovasc Thorac Surg. 2013;16(5):625–29.CrossRefPubMedPubMedCentral
25.
go back to reference Piazza N, Wenaweser P, van Gameren M, Pilgrim T, Tsikas A, Otten A, Nuis R, Onuma Y, Cheng JM, Kappetein AP, Boersma E, Juni P, de Jaegere P, Windecker S, Serruys PW. Relationship between the logistic EuroSCORE and the Society of Thoracic Surgeons Predicted Risk of Mortality score in patients implanted with the CoreValve ReValving system—a Bern-Rotterdam Study. Am Heart J 2010;159(2):323–29.CrossRefPubMed Piazza N, Wenaweser P, van Gameren M, Pilgrim T, Tsikas A, Otten A, Nuis R, Onuma Y, Cheng JM, Kappetein AP, Boersma E, Juni P, de Jaegere P, Windecker S, Serruys PW. Relationship between the logistic EuroSCORE and the Society of Thoracic Surgeons Predicted Risk of Mortality score in patients implanted with the CoreValve ReValving system—a Bern-Rotterdam Study. Am Heart J 2010;159(2):323–29.CrossRefPubMed
26.
go back to reference Ad N, Henry L, Hunt S. Comparison of the New EuroSCORE II with the Original EuroSCORE and the Society of Thoracic Surgeons Risk Score. Circulation. 2012;126:A18614. Ad N, Henry L, Hunt S. Comparison of the New EuroSCORE II with the Original EuroSCORE and the Society of Thoracic Surgeons Risk Score. Circulation. 2012;126:A18614.
27.
go back to reference Thalji NM, Suri RM, Greason KL, Schaff HV. Risk assessment methods for cardiac surgery and intervention. Nat Rev Cardiol. 2014;11(12):704 – 14.CrossRefPubMed Thalji NM, Suri RM, Greason KL, Schaff HV. Risk assessment methods for cardiac surgery and intervention. Nat Rev Cardiol. 2014;11(12):704 – 14.CrossRefPubMed
28.
go back to reference Team RC. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2013. Team RC. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2013.
Metadata
Title
Complexity of preoperative blood pressure dynamics: possible utility in cardiac surgical risk assessment
Authors
Teresa S. Henriques
Madalena D. Costa
Pooja Mathur
Priyam Mathur
Roger B. Davis
Murray A. Mittleman
Kamal R. Khabbaz
Ary L. Goldberger
Balachundhar Subramaniam
Publication date
01-02-2019
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 1/2019
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-018-0133-4

Other articles of this Issue 1/2019

Journal of Clinical Monitoring and Computing 1/2019 Go to the issue