Aging modifies the effect of cardiac output on middle cerebral artery blood flow velocity

Bronzwaer, Anne-Sophie G. T.; Verbree, Jasper; Stok, Wim J.; Daemen, Mat J.A.P.; Buchem, Mark A. van; Osch, Matthias J.P. van; Lieshout, Johannes J. van

doi:10.14814/phy2.13361

Cited by 21 publications

(31 citation statements)

References 59 publications

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“…Aging is associated with a decline in cerebral blood flow and resting brain metabolism 17,18 . With aging, brain perfusion becomes increasingly dependent on cardiac output irrespective of cerebrovascular autoregulatory integrity 19 . The finding of the current study that cerebral blood flow may be compromised in patients with severe cardiac dysfunction is supported by prior studies that found patients with severe heart failure had considerably lower cerebral blood flow than healthy age‐matched controls 20,21 .…”

Section: Discussionsupporting

confidence: 70%

Cerebral Blood Flow in Patients with Severe Aortic Valve Stenosis Undergoing Transcatheter Aortic Valve Implantation

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Bronzwaer

et al. 2020

J American Geriatrics Society

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BACKGROUND Transcatheter aortic valve implantation (TAVI) is a minimally invasive, life‐saving treatment for patients with severe aortic valve stenosis that improves quality of life. We examined cardiac output and cerebral blood flow in patients undergoing TAVI to test the hypothesis that improved cardiac output after TAVI is associated with an increase in cerebral blood flow. DESIGN Prospective cohort study. SETTING European high‐volume tertiary multidisciplinary cardiac care. PARTICIPANTS Thirty‐one patients (78.3 ± 4.6 years; 61% female) with severe symptomatic aortic valve stenosis. MEASUREMENTS Noninvasive prospective assessment of cardiac output (L/min) by inert gas rebreathing and cerebral blood flow of the total gray matter (mL/100 g per min) using arterial spin labeling magnetic resonance imaging in resting state less than 24 hours before TAVI and at 3‐month follow‐up. Cerebral blood flow change was defined as the difference relative to baseline. RESULTS On average, cardiac output in patients with severe aortic valve stenosis increased from 4.0 ± 1.1 to 5.4 ± 2.4 L/min after TAVI (P = .003). The increase in cerebral blood flow after TAVI strongly varied between patients (7% ± 24%; P = .41) and related to the increase in cardiac output, with an 8.2% (standard error = 2.3%; P = .003) increase in cerebral blood flow per every additional liter of cardiac output following the TAVI procedure. CONCLUSION Following TAVI, there was an association of increase in cardiac output with increase in cerebral blood flow. These findings encourage future larger studies to determine the influence of TAVI on cerebral blood flow and cognitive function.

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Section: Discussionsupporting

confidence: 70%

Cerebral Blood Flow in Patients with Severe Aortic Valve Stenosis Undergoing Transcatheter Aortic Valve Implantation

Vlastra

Nieuwkerk

Bronzwaer

et al. 2020

J American Geriatrics Society

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“…By design the subjects were healthy individuals exposed to simulated bleeding which restrains us from extrapolating the data to elderly subjects, considering that with healthy aging brain perfusion becomes increasingly dependent on cardiac output (Bronzwaer et al, 2017b ).…”

Section: Discussionmentioning

confidence: 99%

Support Vector Machine Based Monitoring of Cardio-Cerebrovascular Reserve during Simulated Hemorrhage

et al. 2018

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Introduction: In the initial phase of hypovolemic shock, mean blood pressure (BP) is maintained by sympathetically mediated vasoconstriction rendering BP monitoring insensitive to detect blood loss early. Late detection can result in reduced tissue oxygenation and eventually cellular death. We hypothesized that a machine learning algorithm that interprets currently used and new hemodynamic parameters could facilitate in the detection of impending hypovolemic shock.Method: In 42 (27 female) young [mean (sd): 24 (4) years], healthy subjects central blood volume (CBV) was progressively reduced by application of −50 mmHg lower body negative pressure until the onset of pre-syncope. A support vector machine was trained to classify samples into normovolemia (class 0), initial phase of CBV reduction (class 1) or advanced CBV reduction (class 2). Nine models making use of different features were computed to compare sensitivity and specificity of different non-invasive hemodynamic derived signals. Model features included: volumetric hemodynamic parameters (stroke volume and cardiac output), BP curve dynamics, near-infrared spectroscopy determined cortical brain oxygenation, end-tidal carbon dioxide pressure, thoracic bio-impedance, and middle cerebral artery transcranial Doppler (TCD) blood flow velocity. Model performance was tested by quantifying the predictions with three methods: sensitivity and specificity, absolute error, and quantification of the log odds ratio of class 2 vs. class 0 probability estimates.Results: The combination with maximal sensitivity and specificity for classes 1 and 2 was found for the model comprising volumetric features (class 1: 0.73–0.98 and class 2: 0.56–0.96). Overall lowest model error was found for the models comprising TCD curve hemodynamics. Using probability estimates the best combination of sensitivity for class 1 (0.67) and specificity (0.87) was found for the model that contained the TCD cerebral blood flow velocity derived pulse height. The highest combination for class 2 was found for the model with the volumetric features (0.72 and 0.91).Conclusion: The most sensitive models for the detection of advanced CBV reduction comprised data that describe features from volumetric parameters and from cerebral blood flow velocity hemodynamics. In a validated model of hemorrhage in humans these parameters provide the best indication of the progression of central hypovolemia.

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“…The large increase in systolic blood pressure during exhaustive exercise challenges CBF control mechanisms including cerebrovascular or cerebral autoregulation, the cerebrovascular responsiveness (CVR CO2 ) to carbon dioxide (CO 2 ) and oxygen (O 2 ) partial pressures, matching of local cerebral blood supply to the metabolic demand (i.e., neurovascular coupling), neurogenic control ( Immink et al, 2014 ; Ritz et al, 2014 ; Willie et al, 2014 ; Phillips et al, 2016 ), and maintenance of cardiac output ( Ide et al, 1998 , 1999a ; Van Lieshout et al, 2001 , 2003 ; Ogoh et al, 2005a ; Bronzwaer et al, 2014 , 2017 ). During exercise, CBF increases as quantified by several methods (for review, see Secher et al, 2008 ; Smith and Ainslie, 2017 ).…”

Section: Autonomic Neural Control Of Cbf During Exercisementioning

confidence: 99%

Cerebral vs. Cardiovascular Responses to Exercise in Type 2 Diabetic Patients

et al. 2021

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The human brain is constantly active and even small limitations to cerebral blood flow (CBF) may be critical for preserving oxygen and substrate supply, e.g., during exercise and hypoxia. Exhaustive exercise evokes a competition for the supply of oxygenated blood between the brain and the working muscles, and inability to increase cardiac output sufficiently during exercise may jeopardize cerebral perfusion of relevance for diabetic patients. The challenge in diabetes care is to optimize metabolic control to slow progression of vascular disease, but likely because of a limited ability to increase cardiac output, these patients perceive aerobic exercise to be more strenuous than healthy subjects and that limits the possibility to apply physical activity as a preventive lifestyle intervention. In this review, we consider the effects of functional activation by exercise on the brain and how it contributes to understanding the control of CBF with the limited exercise tolerance experienced by type 2 diabetic patients. Whether a decline in cerebral oxygenation and thereby reduced neural drive to working muscles plays a role for “central” fatigue during exhaustive exercise is addressed in relation to brain’s attenuated vascular response to exercise in type 2 diabetic subjects.

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Aging modifies the effect of cardiac output on middle cerebral artery blood flow velocity

Cited by 21 publications

References 59 publications

Cerebral Blood Flow in Patients with Severe Aortic Valve Stenosis Undergoing Transcatheter Aortic Valve Implantation

Cerebral Blood Flow in Patients with Severe Aortic Valve Stenosis Undergoing Transcatheter Aortic Valve Implantation

Support Vector Machine Based Monitoring of Cardio-Cerebrovascular Reserve during Simulated Hemorrhage

Cerebral vs. Cardiovascular Responses to Exercise in Type 2 Diabetic Patients

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