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Published in: Journal of Clinical Monitoring and Computing 4/2020

01-08-2020 | Heart Surgery | Original Research

Changes in nonlinear dynamic complexity measures of blood pressure during anesthesia for cardiac surgeries using cardio pulmonary bypass

Authors: Valluvan Rangasamy, Teresa S. Henriques, Pooja A. Mathur, Roger B. Davis, Murray A. Mittleman, Balachundhar Subramaniam

Published in: Journal of Clinical Monitoring and Computing | Issue 4/2020

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Abstract

Nonlinear complexity measures computed from beat-to-beat arterial BP dynamics have shown associations with standard cardiac surgical risk indices. They reflect the physiological adaptability of a system and has been proposed as dynamical biomarkers of overall health status. We sought to determine the impact of anesthetic induction and cardiopulmonary bypass (CPB) upon the complexity measures computed from perioperative BP time series. In this prospective, observational study, 300 adult patients undergoing cardiac surgery were included. Perioperative period was divided as: (1) Preoperative (PreOp); (2) ORIS—induction to sternotomy; (3) ORSB- sternotomy to CPB; (4) ORposB—post CPB and within 30 min before leaving OR and (5) postoperative phase (PostOp)—initial 30 min in the cardiac surgical intensive care unit. BP waveforms for systolic (SAP), diastolic (DAP), mean arterial pressure (MAP) and pulse pressure (PP) were recorded, and their corresponding complexity index (MSE) was calculated. Significant decrease in MSE from Preop to PostOp phases was observed for all BP time series. Maximum fall was seen during post anesthetic induction (ORIS) phase. Mild recovery during the subsequent phases was observed but they never reached the baseline values. In an exploratory analysis, preoperative MSE showed a significant correlation with postoperative length of ICU stay. Blood pressure complexity varies at different time points and is not fixed for a given individual. Preoperative BP Complexity decreased significantly following anesthetic induction and did not recover to baseline until 30 min after surgery. Prevention of this significant fall may offer restoration of MSE throughout surgery. Furthermore, preoperative BP complexity needs to be explored as a predictor of major postoperative adverse events by itself or in addition with the current risk indices.
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Literature
1.
go back to reference Alexander JH, Smith PK. Coronary-artery bypass grafting. N Engl J Med. 2016;374:1954–64.CrossRef Alexander JH, Smith PK. Coronary-artery bypass grafting. N Engl J Med. 2016;374:1954–64.CrossRef
2.
go back to reference Vetta F, Locorotondo G, Vetta G, Mignano M, Bracchitta S. Prognostic impact of frailty in elderly cardiac surgery patients. Monaldi Arch Chest Dis. 2017;87:855.CrossRef Vetta F, Locorotondo G, Vetta G, Mignano M, Bracchitta S. Prognostic impact of frailty in elderly cardiac surgery patients. Monaldi Arch Chest Dis. 2017;87:855.CrossRef
3.
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 > or = 80 years old. J Cardiothorac Vasc Anesth. 2010;24:18–24.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 > or = 80 years old. J Cardiothorac Vasc Anesth. 2010;24:18–24.CrossRef
4.
go back to reference Pinna-Pintor P, Bobbio M, Colangelo S, Veglia F, Giammaria M, Cuni D, et al. Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients. Eur J Cardiothorac Surg. 2002;21:199–204.CrossRef Pinna-Pintor P, Bobbio M, Colangelo S, Veglia F, Giammaria M, Cuni D, et al. Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients. Eur J Cardiothorac Surg. 2002;21:199–204.CrossRef
5.
go back to reference Zhang R, Iwasaki K, Zuckerman JH, Behbehani K, Crandall CG, Levine BD. Mechanism of blood pressure and R-R variability: insights from ganglion blockade in humans. J Physiol (Lond). 2002;543:337–48.CrossRef Zhang R, Iwasaki K, Zuckerman JH, Behbehani K, Crandall CG, Levine BD. Mechanism of blood pressure and R-R variability: insights from ganglion blockade in humans. J Physiol (Lond). 2002;543:337–48.CrossRef
6.
go back to reference Monk TG, Bronsert MR, Henderson WG, Mangione MP, Sum-Ping STJ, Bentt DR, et al. Association between intraoperative hypotension and hypertension and 30-day postoperative mortality in noncardiac surgery. Anesthesiology. 2015;123:307–19.CrossRef Monk TG, Bronsert MR, Henderson WG, Mangione MP, Sum-Ping STJ, Bentt DR, et al. Association between intraoperative hypotension and hypertension and 30-day postoperative mortality in noncardiac surgery. Anesthesiology. 2015;123:307–19.CrossRef
7.
go back to reference Aronson S, Stafford-Smith M, Phillips-Bute B, Shaw A, Gaca J, Newman M, et al. Intraoperative systolic blood pressure variability predicts 30-day mortality in aortocoronary bypass surgery patients. Anesthesiology. 2010;113:305–12.CrossRef Aronson S, Stafford-Smith M, Phillips-Bute B, Shaw A, Gaca J, Newman M, et al. Intraoperative systolic blood pressure variability predicts 30-day mortality in aortocoronary bypass surgery patients. Anesthesiology. 2010;113:305–12.CrossRef
8.
go back to reference Mascha EJ, Yang D, Weiss S, Sessler DI. Intraoperative mean arterial pressure variability and 30-day mortality in patients having noncardiac surgery. Anesthesiology. 2015;123:79–91.CrossRef Mascha EJ, Yang D, Weiss S, Sessler DI. Intraoperative mean arterial pressure variability and 30-day mortality in patients having noncardiac surgery. Anesthesiology. 2015;123:79–91.CrossRef
9.
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;18:241–51.CrossRef 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;18:241–51.CrossRef
10.
go back to reference Subramaniam B, Khabbaz KR, Heldt T, Lerner AB, Mittleman MA, Davis RB, et al. Blood pressure variability: can nonlinear dynamics enhance risk assessment during cardiovascular surgery? J Cardiothorac Vasc Anesth. 2014;28:392–7.CrossRef Subramaniam B, Khabbaz KR, Heldt T, Lerner AB, Mittleman MA, Davis RB, et al. Blood pressure variability: can nonlinear dynamics enhance risk assessment during cardiovascular surgery? J Cardiothorac Vasc Anesth. 2014;28:392–7.CrossRef
11.
go back to reference Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of biological signals. Phys Rev E. 2005;71:021906.CrossRef Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of biological signals. Phys Rev E. 2005;71:021906.CrossRef
12.
go back to reference Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett. 2002;89:068102.CrossRef Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett. 2002;89:068102.CrossRef
13.
go back to reference Lakusic N, Mahovic D, Sonicki Z, Slivnjak V, Baborski F. Outcome of patients with normal and decreased heart rate variability after coronary artery bypass grafting surgery. Int J Cardiol. 2013;166:516–8.CrossRef Lakusic N, Mahovic D, Sonicki Z, Slivnjak V, Baborski F. Outcome of patients with normal and decreased heart rate variability after coronary artery bypass grafting surgery. Int J Cardiol. 2013;166:516–8.CrossRef
14.
go back to reference Padley JR, Ben-Menachem E. Low pre-operative heart rate variability and complexity are associated with hypotension after anesthesia induction in major abdominal surgery. J Clin Monit Comput. 2018;32:245–52.CrossRef Padley JR, Ben-Menachem E. Low pre-operative heart rate variability and complexity are associated with hypotension after anesthesia induction in major abdominal surgery. J Clin Monit Comput. 2018;32:245–52.CrossRef
15.
go back to reference Hu J, Gao J, Tung W, Cao Y. Multiscale analysis of heart rate variability: a comparison of different complexity measures. Ann Biomed Eng. 2010;38:854–64.CrossRef Hu J, Gao J, Tung W, Cao Y. Multiscale analysis of heart rate variability: a comparison of different complexity measures. Ann Biomed Eng. 2010;38:854–64.CrossRef
16.
go back to reference Molon G, Solimene F, Melissano D, Curnis A, Belotti G, Marrazzo N, et al. Baseline heart rate variability predicts clinical events in heart failure patients implanted with cardiac resynchronization therapy: validation by means of related complexity index. Ann Noninvasive Electrocardiol. 2010;15:301–7.CrossRef Molon G, Solimene F, Melissano D, Curnis A, Belotti G, Marrazzo N, et al. Baseline heart rate variability predicts clinical events in heart failure patients implanted with cardiac resynchronization therapy: validation by means of related complexity index. Ann Noninvasive Electrocardiol. 2010;15:301–7.CrossRef
17.
go back to reference Henriques TS, Costa MD, Mathur P, Mathur P, Davis RB, Mittleman MA, et al. Complexity of preoperative blood pressure dynamics: possible utility in cardiac surgical risk assessment. J Clin Monit Comput. 2018;33:31–8.CrossRef Henriques TS, Costa MD, Mathur P, Mathur P, Davis RB, Mittleman MA, et al. Complexity of preoperative blood pressure dynamics: possible utility in cardiac surgical risk assessment. J Clin Monit Comput. 2018;33:31–8.CrossRef
18.
go back to reference Murphy GS, Hessel EA, Groom RC. Optimal perfusion during cardiopulmonary bypass: an evidence-based approach. Anesth Analg. 2009;108:1394–417.CrossRef Murphy GS, Hessel EA, Groom RC. Optimal perfusion during cardiopulmonary bypass: an evidence-based approach. Anesth Analg. 2009;108:1394–417.CrossRef
19.
go back to reference Mets B. The pharmacokinetics of anesthetic drugs and adjuvants during cardiopulmonary bypass. Acta Anaesthesiol Scand. 2000;44:261–73.CrossRef Mets B. The pharmacokinetics of anesthetic drugs and adjuvants during cardiopulmonary bypass. Acta Anaesthesiol Scand. 2000;44:261–73.CrossRef
20.
go back to reference von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147:573–7.CrossRef von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147:573–7.CrossRef
21.
go back to reference Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101:E215–20.PubMed Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101:E215–20.PubMed
22.
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.
23.
go back to reference Saeed M, Villarroel M, Reisner AT, Clifford G, Lehman L-W, Moody G, et al. Multiparameter intelligent monitoring in intensive care II: a public-access intensive care unit database. Crit Care Med. 2011;39:952–60.CrossRef Saeed M, Villarroel M, Reisner AT, Clifford G, Lehman L-W, Moody G, et al. Multiparameter intelligent monitoring in intensive care II: a public-access intensive care unit database. Crit Care Med. 2011;39:952–60.CrossRef
24.
go back to reference Parati G, Ochoa JE, Lombardi C, Bilo G. Assessment and management of blood-pressure variability. Nat Rev Cardiol. 2013;10:143–55.CrossRef Parati G, Ochoa JE, Lombardi C, Bilo G. Assessment and management of blood-pressure variability. Nat Rev Cardiol. 2013;10:143–55.CrossRef
25.
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:H2039–49.CrossRef Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;278:H2039–49.CrossRef
27.
go back to reference Souza Neto EP, Loufouat J, Saroul C, Paultre C, Chiari P, Lehot J-J, et al. Blood pressure and heart rate variability changes during cardiac surgery with cardiopulmonary bypass. Fundam Clin Pharmacol. 2004;18:387–96.CrossRef Souza Neto EP, Loufouat J, Saroul C, Paultre C, Chiari P, Lehot J-J, et al. Blood pressure and heart rate variability changes during cardiac surgery with cardiopulmonary bypass. Fundam Clin Pharmacol. 2004;18:387–96.CrossRef
28.
go back to reference Yang MW, Kuo TB, Lin SM, Chan KH, Chan SH. Continuous, on-line, real-time spectral analysis of SAP signals during cardiopulmonary bypass. Am J Physiol. 1995;268:H2329–35.PubMed Yang MW, Kuo TB, Lin SM, Chan KH, Chan SH. Continuous, on-line, real-time spectral analysis of SAP signals during cardiopulmonary bypass. Am J Physiol. 1995;268:H2329–35.PubMed
29.
go back to reference Marty J, Gauzit R, Lefevre P, Couderc E, Farinotti R, Henzel C, et al. Effects of diazepam and midazolam on baroreflex control of heart rate and on sympathetic activity in humans. Anesth Analg. 1986;65:113–9.CrossRef Marty J, Gauzit R, Lefevre P, Couderc E, Farinotti R, Henzel C, et al. Effects of diazepam and midazolam on baroreflex control of heart rate and on sympathetic activity in humans. Anesth Analg. 1986;65:113–9.CrossRef
30.
go back to reference Reich DL, Hossain S, Krol M, Baez B, Patel P, Bernstein A, et al. Predictors of hypotension after induction of general anesthesia. Anesth Analg. 2005;101:622–8.CrossRef Reich DL, Hossain S, Krol M, Baez B, Patel P, Bernstein A, et al. Predictors of hypotension after induction of general anesthesia. Anesth Analg. 2005;101:622–8.CrossRef
31.
go back to reference Ebert TJ, Muzi M, Berens R, Goff D, Kampine JP. Sympathetic responses to induction of anesthesia in humans with propofol or etomidate. Anesthesiology. 1992;76:725–33.CrossRef Ebert TJ, Muzi M, Berens R, Goff D, Kampine JP. Sympathetic responses to induction of anesthesia in humans with propofol or etomidate. Anesthesiology. 1992;76:725–33.CrossRef
32.
go back to reference Kato M, Komatsu T, Kimura T, Sugiyama F, Nakashima K, Shimada Y. Spectral analysis of heart rate variability during isoflurane anesthesia. Anesthesiology. 1992;77:669–74.CrossRef Kato M, Komatsu T, Kimura T, Sugiyama F, Nakashima K, Shimada Y. Spectral analysis of heart rate variability during isoflurane anesthesia. Anesthesiology. 1992;77:669–74.CrossRef
33.
go back to reference Huang HH, Chan HL, Lin PL, Wu CP, Huang CH. Time-frequency spectral analysis of heart rate variability during induction of general anaesthesia. Br J Anaesth. 1997;79:754–8.CrossRef Huang HH, Chan HL, Lin PL, Wu CP, Huang CH. Time-frequency spectral analysis of heart rate variability during induction of general anaesthesia. Br J Anaesth. 1997;79:754–8.CrossRef
34.
go back to reference Pinsky MR. Complexity modeling: identify instability early. Crit Care Med. 2010;38:S649–55.CrossRef Pinsky MR. Complexity modeling: identify instability early. Crit Care Med. 2010;38:S649–55.CrossRef
Metadata
Title
Changes in nonlinear dynamic complexity measures of blood pressure during anesthesia for cardiac surgeries using cardio pulmonary bypass
Authors
Valluvan Rangasamy
Teresa S. Henriques
Pooja A. Mathur
Roger B. Davis
Murray A. Mittleman
Balachundhar Subramaniam
Publication date
01-08-2020
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 4/2020
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-019-00370-4

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