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Injured brain tissue supplied by a disturbed state of cerebral autoregulation (CA) is at risk of secondary ischemia, e.g. in patients with stroke, subarachnoid hemorrhage, intracerebral hemorrhage or bacterial Meningitis. Up to now, there is lack of a simple and easy to perform bed side test that would allow for to intervene when CA failure is indicated. For this purpose, we explore the dynamics of the interplay between blood pressure and cerebral blood flow velocity using transcranial Doppler ultrasound (or near infrared spectroscopy derived haemoglobin concentration changes) as a measure of CA. To describe these dynamics different mathematical models are used, but they all still need validation and proof of concept because these dynamics are poorly understood with respect to the factors which influence the composition of the mathematical models.
Objectives: To what amount is CA disturbed in the different stroke subgroups ? Is a disturbed CA a risk factor of poorer outcome ?
We investigate which factors determine the dynamics of CA under the assumption that disturbed dynamics of the relation blood pressure (BP) - cerebral blood flow velocity CBFv) indicate a disturbed CA. Factors to be considered relevant are BP, blood carbon dioxide (CO2) concentration (measured as endtidal CO2 concentration), autonomic nervous system function such as heart rate, pulse pressure amplitude and baroreflex sensitivity, movement or psychological tasks, and in the patients the kind and the severity of the underlying disease. Via different mathematical models the effects of these variables on CBFv as the Output function is evaluated. The most frequently used approach is the use of Transfer functions.
In the registry will include the patients with acute strokes hospitalized at our stroke center. We will include every stroke patient with any Kind and severity of stroke syndromes who gives informed consent and who has a so called temporal ultrasound window to insonate the middle cerebral artery. BP will be measure noninvasively by a Finapres device. Items registered are Age, gender, cerebrovascular risk factors, temperature, mean BP and ist variability on days 1-3, stroke classification using TOAST, Perfusion Computed Tomography and MRI, and at the time of the simultaneous recordings of CBFv and BP the endtidal CO2, mean BP, mean pulsatility index, and after Transfer function analysis coherence, gain and Phase in different frequency ranges
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with stroke | Patients with stroke of all subtypes, with and without different Kind of Lysis therapy |
| |
| Controls | Healthy controls of all Ages above 18 years |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Assessment of CA | Diagnostic Test | As part of our routine stroke work up, each patient receives an initial CT scan with CT perfusion to indicate thrombolysis therapy (intravenous, mechanical, or both, depending on the time since first stroke symptoms and perfusion-mismatch), an MRI within 2 days, extracranial and transcranial Duplex ultrasound, echocardiography, continuous Monitoring of BP, O2, body temperature, NIHSS and Glagow Coma Scale (GCS) every 6 hours. Assessing CA by continuous recording of blood pressure, cerebral blood flow velocity, end-tidal CO2. Analysis via Transfer function estimates |
| Measure | Description | Time Frame |
|---|---|---|
| Change of modified Rankin Scale (mRs) : 0, no symptoms. 1, no significant disability. 2, slight disability. 3, moderate disability. 4, moderate severe disability. 5, severe disability. 6, dead | Clinical outcome | 3 months |
| State of cerebral autoregulation (CA) | Transfer function estimates (gain, phase) between low frequency oscillations in BP and CBFv. A low gain and a high phase indicate good CA, a high gain and a low phase a poor CA state. Typically, a phase of 1 radian indicates a good CA, a phase of 0.2 a very poor one. | Assessment on days 1-3 after stroke onset |
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Inclusion Criteria:
Exclusion Criteria:
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Stroke patients: all stroke patients which will be referred to our stroke Center aged 18 years or older. N=500.
Healthy controls of all ages above 18 years. N=80
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Martin Müller, MD | Contact | +41 41 205 | 5113 | martin.mueller@luks.ch |
| Lehel Lakatos, MD | Contact | +41 41 205 | 6266 | Lehel-Barna.Lakatos@luks.ch |
| Name | Affiliation | Role |
|---|---|---|
| Martin Müller, MD | Luzerner Kantonsspital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Kantonsspital Luzern | Recruiting | Lucerne | 6000 | Switzerland |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32090712 | Background | Beishon L, Minhas JS, Nogueira R, Castro P, Budgeon C, Aries M, Payne S, Robinson TG, Panerai RB. INFOMATAS multi-center systematic review and meta-analysis individual patient data of dynamic cerebral autoregulation in ischemic stroke. Int J Stroke. 2020 Oct;15(7):807-812. doi: 10.1177/1747493020907003. Epub 2020 Feb 24. | |
| 24725709 |
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retrospective data collection for an individual participant data metaanalysis as published in Int J Stroke. 2020 Oct;15(7):807-812. doi: 10.1177/1747493020907003
2021 - 2025
on request to M Müller
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| ID | Term |
|---|---|
| D020521 | Stroke |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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|
| Assesment of CA only | Diagnostic Test | Assessing CA by continuous recording of blood pressure, cerebral blood flow velocity, end-tidal CO2. Analysis via Transfer function estimates |
|
| Meel-van den Abeelen AS, Simpson DM, Wang LJ, Slump CH, Zhang R, Tarumi T, Rickards CA, Payne S, Mitsis GD, Kostoglou K, Marmarelis V, Shin D, Tzeng YC, Ainslie PN, Gommer E, Muller M, Dorado AC, Smielewski P, Yelicich B, Puppo C, Liu X, Czosnyka M, Wang CY, Novak V, Panerai RB, Claassen JA. Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure-flow relation: the CARNet study. Med Eng Phys. 2014 May;36(5):620-7. doi: 10.1016/j.medengphy.2014.02.002. Epub 2014 Apr 13. |
| 26782760 | Background | Claassen JA, Meel-van den Abeelen AS, Simpson DM, Panerai RB; international Cerebral Autoregulation Research Network (CARNet). Transfer function analysis of dynamic cerebral autoregulation: A white paper from the International Cerebral Autoregulation Research Network. J Cereb Blood Flow Metab. 2016 Apr;36(4):665-80. doi: 10.1177/0271678X15626425. Epub 2016 Jan 18. |
| 32514031 | Result | Muller M, Osterreich M, Lakatos L, Hessling AV. Cerebral macro- and microcirculatory blood flow dynamics in successfully treated chronic hypertensive patients with and without white mater lesions. Sci Rep. 2020 Jun 8;10(1):9213. doi: 10.1038/s41598-020-66317-x. |
| 29995701 | Result | Muller M, Osterreich M, von Hessling A, Smith RS. Incomplete recovery of cerebral blood flow dynamics in sufficiently treated high blood pressure. J Hypertens. 2019 Feb;37(2):372-379. doi: 10.1097/HJH.0000000000001854. |
| 39749040 | Derived | Lakatos LB, Bolognese M, Oesterreich M, Muller M, Karwacki GM. Cerebrovascular regulation in patients with active tumors and an acute ischemic stroke: a retrospective analysis. Front Physiol. 2024 Dec 19;15:1423195. doi: 10.3389/fphys.2024.1423195. eCollection 2024. |
| 39600968 | Derived | Bolognese M, Weichsel L, Osterreich M, Muller M, Karwacki GM, Lakatos LB. Association of high-sensitivity cardiac troponin T with territorial middle cerebral artery brain infarctions and dynamic cerebral autoregulation. J Cent Nerv Syst Dis. 2024 Nov 25;16:11795735241302725. doi: 10.1177/11795735241302725. eCollection 2024. |
| 37931481 | Derived | Lakatos LB, Shin DC, Muller M, Osterreich M, Marmarelis V, Bolognese M. Impaired dynamic cerebral autoregulation measured in the middle cerebral artery in patients with vertebrobasilar ischemia is associated with autonomic failure. J Stroke Cerebrovasc Dis. 2024 Jan;33(1):107454. doi: 10.1016/j.jstrokecerebrovasdis.2023.107454. Epub 2023 Nov 4. |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |