Determining Thresholds for Three Indices of Autoregulation to Identify the Lower Limit of Autoregulation During Cardiac Surgery

Xiuyun Liu, Kei Akiyoshi, Mitsunori Nakano, Ken Brady, Brian Bush, Rohan Nadkarni, Archana Venkataraman, Raymond C Koehler, Jennifer K Lee, Charles W Hogue, Marek Czosnyka, Peter Smielewski, Charles H Brown, Xiuyun Liu, Kei Akiyoshi, Mitsunori Nakano, Ken Brady, Brian Bush, Rohan Nadkarni, Archana Venkataraman, Raymond C Koehler, Jennifer K Lee, Charles W Hogue, Marek Czosnyka, Peter Smielewski, Charles H Brown

Abstract

Objectives: Monitoring cerebral autoregulation may help identify the lower limit of autoregulation in individual patients. Mean arterial blood pressure below lower limit of autoregulation appears to be a risk factor for postoperative acute kidney injury. Cerebral autoregulation can be monitored in real time using correlation approaches. However, the precise thresholds for different cerebral autoregulation indexes that identify the lower limit of autoregulation are unknown. We identified thresholds for intact autoregulation in patients during cardiopulmonary bypass surgery and examined the relevance of these thresholds to postoperative acute kidney injury.

Design: A single-center retrospective analysis.

Setting: Tertiary academic medical center.

Patients: Data from 59 patients was used to determine precise cerebral autoregulation thresholds for identification of the lower limit of autoregulation. These thresholds were validated in a larger cohort of 226 patients.

Methods and main results: Invasive mean arterial blood pressure, cerebral blood flow velocities, regional cortical oxygen saturation, and total hemoglobin were recorded simultaneously. Three cerebral autoregulation indices were calculated, including mean flow index, cerebral oximetry index, and hemoglobin volume index. Cerebral autoregulation curves for the three indices were plotted, and thresholds for each index were used to generate threshold- and index-specific lower limit of autoregulations. A reference lower limit of autoregulation could be identified in 59 patients by plotting cerebral blood flow velocity against mean arterial blood pressure to generate gold-standard Lassen curves. The lower limit of autoregulations defined at each threshold were compared with the gold-standard lower limit of autoregulation determined from Lassen curves. The results identified the following thresholds: mean flow index (0.45), cerebral oximetry index (0.35), and hemoglobin volume index (0.3). We then calculated the product of magnitude and duration of mean arterial blood pressure less than lower limit of autoregulation in a larger cohort of 226 patients. When using the lower limit of autoregulations identified by the optimal thresholds above, mean arterial blood pressure less than lower limit of autoregulation was greater in patients with acute kidney injury than in those without acute kidney injury.

Conclusions: This study identified thresholds of intact and impaired cerebral autoregulation for three indices and showed that mean arterial blood pressure below lower limit of autoregulation is a risk factor for acute kidney injury after cardiac surgery.

Conflict of interest statement

Drs. Lee, Hogue, and Brown received support for article research from the National Institutes of Health (NIH). Dr. Lee has received support from and been a paid consultant for Medtronic, and she received research support from Edwards Life Sciences. Dr. Lee’s arrangements have been reviewed and approved by the Johns Hopkins University in accordance with its conflict of interest policies. Some methods used to measure and monitor autoregulation as described in this article were patented by The Johns Hopkins University, listing Dr. Brady as a coinventor. These patents are exclusively licensed to Medtronic. Dr. Brown reported receiving grants from the NIH during the conduct of the study, and consulting for and participating in a data share with Medtronic. Dr. Brady is listed as inventor on patents awarded and assigned to the Johns Hopkins University. These patents are related to the monitoring technology described in this article and are exclusively licensed to Medtronic, and Dr. Brady received a portion of the licensing fee. Dr. Venkataraman received funding from Vixiar Medical (consulting) and from universities for speaker honorariums, and she was supported by the National Science Foundation CAREER award 1845430. Dr. Hogue reported receiving grants and personal fees for being a consultant and providing lectures for Medtronic/Covidien, being a consultant to Merck, and receiving grants from the NIH outside of the submitted work, and he disclosed off-label product use of autoregulation monitoring is investigational. Drs. Czosnyka and Smielewski received funding from licensing ICM+ through Cambridge Enterprise Ltd, United Kingdom. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Copyright © 2020 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.

Figures

Figure 1.
Figure 1.
(A) Example cerebral autoregulation Lassen curve created by plotting transcranial Doppler (TCD) cerebral blood flow velocity (CBFV) vs. mean arterial blood pressure (MAP). The point in the regression line at which the first ascending line met the plateau was identified as the lower limit of autoregulation (LLA). This patient’s LLA was 61 mmHg. (B) LLA defined using mean flow index (Mx) at different Mx thresholds of the same patient. A U-shaped curve was created by plotting Mx against MAP, and a straight horizontal line at the cutoff value was drawn to locate the x coordinate of the cross point where the straight line met the curve. In this example, an Mx threshold of 0.45 would identify an LLA of 61 mmHg.
Figure 2.
Figure 2.
Bland-Altman plot between the lower limit of autoregulation (LLA) defined by the Lassen curve and by the mean flow index (Mx) at a threshold of 0.45 (A), by the cerebral oximetry index (Cox) at a threshold of 0.35 (B), and by the hemoglobin volume index (HVx) at a threshold of 0.3 (C).
Figure 3.
Figure 3.
The extent of mean arterial blood pressure (MAP) below the lower limit of autoregulation (LLA; defined by Mx, Cox, and HVx) in patients with and without acute kidney injury (AKI) using Mann-Whitney tests. The bar is expressed as mean ± SEM; n=176 for (A), n=200 for (B) and n=192 for (C). More details can be found in Supplementary Table 2. *p<0.05. Mx = mean flow index; COx = cerebral oximetry index; HVx = hemoglobin volume index.

References

    1. Caldas JR, Haunton VJ, Panerai RB, et al.: Cerebral autoregulation in cardiopulmonary bypass surgery: A systematic review. Interact Cardiovasc Thorac Surg 2018; 26:494–503
    1. Liu X, Czosnyka M, Donnelly J, et al.: Comparison of frequency and time domain methods of assessment of cerebral autoregulation in traumatic brain injury. J Cereb Blood Flow Metab 2014; 11:1–9
    1. Paulson OB, Strandgaard S, Edvinsson L: Cerebral autoregulation. [Internet]. Cerebrovasc brain Metab Rev 1990; 2:161–192
    1. Lassen NA, Christensen MS: Physiology of cerebral blood flow. Br J Anaesth 1976; 48:719–734
    1. Zaidi G, Chichra A, Weitzen M, et al.: Blood pressure control in neurological ICU patients: What is too high and what is too low? Open Crit Care Med J 2013; 6:46–55
    1. Liu X, Schreiber M, Donnelly J, et al.: Cerebrovascular pressure reactivity monitoring using wavelet analysis in traumatic brain injury patients: A retrospective study [Internet]. PLOS Med 2017; 14:e1002348.
    1. Güiza F, Depreitere B, Piper I, et al.: Visualizing the pressure and time burden of intracranial hypertension in adult and paediatric traumatic brain injury. Intensive Care Med 2015; 41:1067–1076
    1. Depreitere B, Güiza F, Van den Berghe G, et al.: Pressure autoregulation monitoring and cerebral perfusion pressure target recommendation in patients with severe traumatic brain injury based on minute-by-minute monitoring data. J Neurosurg 2014; 120:1451–7
    1. Panerai RB, Kerins V, Fan L, et al.: Association between dynamic cerebral autoregulation and mortality in severe head injury. Br J Neurosurg 2004; 18:471–497
    1. Brown CH, Neufeld KJ, Tian J, et al.: Effect of Targeting Mean Arterial Pressure during Cardiopulmonary Bypass by Monitoring Cerebral Autoregulation on Postsurgical Delirium among Older Patients: A Nested Randomized Clinical Trial. JAMA Surg 2019; 154:819–826
    1. Ono M, Arnaoutakis GJ, Fine DM, et al.: Blood pressure excursions below the cerebral autoregulation threshold during cardiac surgery are associated with acute kidney injury. Crit Care Med 2013; 41:464–71
    1. Hori D, Nomura Y, Ono M, et al.: Optimal blood pressure during cardiopulmonary bypass defined by cerebral autoregulation monitoring. J Thorac Cardiovasc Surg 2017; 154:1590–1598
    1. Czosnyka M, Smielewski P, Kirkpatrick P, et al.: Continuous assessment of the cerebral vasomotor reactivity in head injury. Neurosurgery 1997; 41:11–19
    1. Brady KM, Mytar JO, Kibler KK, et al.: Noninvasive autoregulation monitoring with and without intracranial pressure in the naïve piglet brain. Anesth Analg 2010; 111:191–195
    1. Young AMH, Donnelly J, Czosnyka M, et al.: Continuous Multimodality Monitoring in Children after Traumatic Brain Injury—Preliminary Experience. PLoS One 2016; 11:e0148817.
    1. Brady K, Joshi B, Zweifel C, et al.: Real-Time Continuous Monitoring of Cerebral Blood Flow Autoregulation Using Near-Infrared Spectroscopy in Patients Undergoing Cardiopulmonary Bypass. Stroke 2010; 41:1951–1956
    1. Donnelly J, Czosnyka M, Adams H, et al.: Individualizing Thresholds of Cerebral Perfusion Pressure Using Estimated Limits of Autoregulation. Crit Care Med 2017; 45:1464–1471
    1. Lee JK, Williams M, Reyes M, et al.: Cerebrovascular blood pressure autoregulation monitoring and postoperative transient ischemic attack in pediatric moyamoya vasculopathy. Paediatr Anaesth 2018; 28:94–102
    1. Lee JK, Kibler KK, Benni PB, et al.: Cerebrovascular reactivity measured by near-infrared spectroscopy. Stroke 2009; 40:1820–1826
    1. Brady KM, Lee JK, Kibler KK, et al.: Continuous measurement of autoregulation by spontaneous fluctuations in cerebral perfusion pressure: comparison of 3 methods. Stroke 2008; 39:2531–2537
    1. Czosnyka M, Smielewski P, Lavinio A, et al.: An assessment of dynamic autoregulation from spontaneous fluctuations of cerebral blood flow velocity: a comparison of two models, index of autoregulation and mean flow index. Anesth Analg 2008; 106:234–9
    1. Sorrentino E, Diedler J, Kasprowicz M, et al.: Critical thresholds for cerebrovascular reactivity after traumatic brain injury. Neurocrit Care 2012; 16:258–266
    1. Sorrentino E, Budohoski KP, Kasprowicz M, et al.: Critical thresholds for transcranial doppler indices of cerebral autoregulation in traumatic brain injury. Neurocrit Care 2011; 14:188–193
    1. Brady KM, Lee JK, Kibler KK, et al.: Continuous time-domain analysis of cerebrovascular autoregulation using near-infrared spectroscopy. Stroke 2007; 38:2818–2825
    1. Lassen N: Cerebral blood flow and oxygen consumption in man. Physiol Rev 1959; 39:183–238
    1. Fantini S, Sassaroli A, Tgavalekos KT, et al.: Cerebral blood flow and autoregulation: current measurement techniques and prospects for noninvasive optical methods. Neurophotonics 2016; 3:031411.
    1. Dumville J, Panerai RB, Lennard NS, et al.: Can cerebrovascular reactivity be assessed without measuring blood pressure in patients with carotid artery disease?. Stroke 1998; 29:968–74
    1. Ono M, Joshi B, Brady K, et al.: Risks for impaired cerebral autoregulation during cardiopulmonary bypass and postoperative stroke. Br J Anaesth 2012; 103:391–398
    1. Aries MJH, Elting JW, De Keyser J, et al.: Cerebral autoregulation in stroke: A review of transcranial doppler studies. Stroke 2010; 41:2697–2704
    1. Ono M, Brady K, Easley RB, et al.: Duration and magnitude of blood pressure below cerebral autoregulation threshold during cardiopulmonary bypass is associated with major morbidity and operative mortality. J Thorac Cardiovasc Surg 2014; 147:483–489
    1. Mehta RL, Kellum JA, Shah S V., et al.: Acute kidney injury network: Report of an initiative to improve outcomes in acute kidney injury. Crit Care 2007; 11:R31.
    1. Rhee CJ, Kibler KK, Easley RB, et al.: Renovascular reactivity measured by near-infrared spectroscopy. J Appl Physiol 2012; 113:307–314
    1. Willie CK, Tzeng YC, Fisher JA, et al.: Integrative regulation of human brain blood flow. J Physiol 2014; 592:841–859
    1. Liu X, Hu X, Brady KM, et al.: Comparison of wavelet and correlation indices of cerebral autoregulation in a pediatric swine model of cardiac arrest. Sci Rep 2020; 10:5926.
    1. Lee JK, Brady KM, Mytar JO, et al.: Cerebral blood flow and cerebrovascular autoregulation in a swine model of pediatric cardiac arrest and hypothermia. Crit Care Med 2011; 39:2337–2345
    1. Brass LM, Prohovnik I, Pavlakis SG, et al.: Middle cerebral artery blood velocity and cerebral blood flow in sickle cell disease. Stroke 1991; 22:27–30
    1. Bishop CCR, Powell S, Rutt D, et al.: Transcranial doppler measurement of middle cerebral artery blood flow velocity: A validation study. Stroke 1986; 17:913–915
    1. Brauer P, Kochs E, Werner C, et al.: Correlation of transcranial Doppler sonography mean flow velocity with cerebral blood flow in patients with intracranial pathology. J Neurosurg Anesthesiol 1998; 10:80–85
    1. Panerai RB: Transcranial Doppler for evaluation of cerebral autoregulation. Clin Auton Res 2009; 19:197–211
    1. van Beek AHEA, Lagro J, Olde-Rikkert MGM, et al.: Oscillations in cerebral blood flow and cortical oxygenation in Alzheimer’s disease. Neurobiol Aging 2012; 33:428.e21–31
    1. Oudegeest-Sander MH, van Beek AHEA, Abbink K, et al.: Assessment of dynamic cerebral autoregulation and cerebrovascular CO2 reactivity in ageing by measurements of cerebral blood flow and cortical oxygenation. Exp Physiol 2014; 99:586–598

Source: PubMed

3
Abonnere