Evidence map›Paper›PMID 31354518›Full record

ArticleFrontiers in physiology2019

Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability.

Marit L Sanders, Jan Willem J Elting, Ronney B Panerai, Marcel Aries, Edson Bor-Seng-Shu, Alexander Caicedo, Max Chacon, Erik D Gommer, Sabine Van Huffel, José L Jara and 15 more

Abstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. INFOMATAS multi-center systematic review and meta-analysis individual patient data of dynamic cerebral autoregulation in ischemic stroke.International journal of stroke : official journal of the International Stroke Society · 2020
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet).Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024
    Review
  7. Depression of dynamic cerebral autoregulation during neural activation: The role of responders and non-responders.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024
    Article
  8. Article
  9. Article
  10. Dynamic cerebral autoregulation measured by diffuse correlation spectroscopy.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023
    Article
  11. Effects of posture changes on dynamic cerebral autoregulation during early pregnancy in women with obesity and/or sleep apnea.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2023
    Article
  12. Transfer function analysis of dynamic cerebral autoregulation: A CARNet white paper 2022 update.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023
    Review
  13. Article
  14. Review of studies on dynamic cerebral autoregulation in the acute phase of stroke and the relationship with clinical outcome.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022
    Review
  15. Article
  16. Review
  17. Cerebral critical closing pressure and resistance-area product: the influence of dynamic cerebral autoregulation, age and sex.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
    Article
  18. Article
  19. Vascular and haemodynamic issues of brain ageing.Pflugers Archiv : European journal of physiology · 2021
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Marit L SandersDepartment of Geriatric Medicine, Radboudumc Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands.
Jan Willem J EltingDepartment of Neurology, University Medical Center Groningen, Groningen, Netherlands.
Ronney B PaneraiDepartment of Cardiovascular Sciences, NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom.
Marcel AriesDepartment of Intensive Care, University of Maastricht, Maastricht University Medical Center, Maastricht, Netherlands.
Edson Bor-Seng-ShuDepartment of Neurology, Faculty of Medicine, Hospital das Clinicas University of São Paulo, São Paulo, Brazil.
Alexander CaicedoDepartment of Applied Mathematics and Computer Science, Faculty of Natural Sciences and Mathematics, Universidad del Rosario, Bogotá, Colombia.
Max ChaconDepartment of Engineering Informatics, Institute of Biomedical Engineering, University of Santiago, Santiago, Chile.
Erik D GommerDepartment of Clinical Neurophysiology, Maastricht University Medical Centre, Maastricht, Netherlands.
Sabine Van HuffelDepartment of Electronic Engineering (ESAT), Stadius Center for Dynamical Systems, Signal Processing and Data Analytics, Katholieke Universiteit Leuven, Leuven, Belgium.
José L JaraDepartment of Engineering Informatics, Institute of Biomedical Engineering, University of Santiago, Santiago, Chile.
Kyriaki KostoglouDepartment of Electrical, Computer and Software Engineering, McGill University, Montreal, QC, Canada.
Adam MahdiDepartment of Engineering Science, University of Oxford, Oxford, United Kingdom.
Vasilis Z MarmarelisDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States.
Georgios D MitsisDepartment of Bioengineering, McGill University, Montreal, QC, Canada.
Martin MüllerDepartment of Neurology, Luzerner Kantonsspital, Luzern, Switzerland.
Dragana NikolicFaculty of Engineering and the Environment, Institute of Sound and Vibration Research, University of Southampton, Southampton, United Kingdom.
Ricardo C NogueiraDepartment of Neurology, Faculty of Medicine, Hospital das Clinicas University of São Paulo, São Paulo, Brazil.
Stephen J PayneDepartment of Engineering Science, University of Oxford, Oxford, United Kingdom.
Corina PuppoDepartamento de Emergencia, Hospital de Clínicas, Universidad de la República, Montevideo, Uruguay.
Dae C ShinDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States.
David M SimpsonFaculty of Engineering and the Environment, Institute of Sound and Vibration Research, University of Southampton, Southampton, United Kingdom.
Takashi TarumiInstitute for Exercise and Environmental Medicine, Presbyterian Hospital of Dallas, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Bernardo YelicichDepartamento de Emergencia, Hospital de Clínicas, Universidad de la República, Montevideo, Uruguay.
Rong ZhangInstitute for Exercise and Environmental Medicine, Presbyterian Hospital of Dallas, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Jurgen A H R ClaassenDepartment of Geriatric Medicine, Radboudumc Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands.

Funding

TrainingP41EB001978 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KHOO, MICHAEL C K · 2003 to 2017
$18.1M
NIBIB NIH HHS P41 EB001978
6 · The paper itself

Abstract

Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data (

Indexed as

ARI indexcerebral blood flowcerebral hemodynamicstranscranial Dopplertransfer function analysis

Identifiers

PMID31354518
PMCPMC6634255

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.