Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study
Transfer function analysis (TFA) is a frequently used method to assess dynamic cerebral autoregulation (CA) using spontaneous oscillations in blood pressure (BP) and cerebral blood flow velocity (CBFV). However, controversies and variations exist in how research groups utilise TFA, causing high vari...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2014
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/27284
- Acceso en línea:
- https://doi.org/10.1016/j.medengphy.2014.02.002
https://repository.urosario.edu.co/handle/10336/27284
- Palabra clave:
- Cerebral autoregulation
Transfer function analysis
Method comparison
Standardisation
- Rights
- License
- Restringido (Acceso a grupos específicos)
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351bdd56-0853-4cdf-b2d4-8a5f807ddbc6-13e2b8fd0-a874-42f1-bbf6-7e370fec84fc-1d41b4ce2-77ca-4c55-ab7a-aaa24bf79314-18b1efb10-5e07-444e-945b-79a56cfb8d55-18d876f93-b17a-48ae-8693-c228dcc750c7-12020-08-19T14:41:36Z2020-08-19T14:41:36Z2014-05-01Transfer function analysis (TFA) is a frequently used method to assess dynamic cerebral autoregulation (CA) using spontaneous oscillations in blood pressure (BP) and cerebral blood flow velocity (CBFV). However, controversies and variations exist in how research groups utilise TFA, causing high variability in interpretation. The objective of this study was to evaluate between-centre variability in TFA outcome metrics. 15 centres analysed the same 70 BP and CBFV datasets from healthy subjects (n = 50 rest; n = 20 during hypercapnia); 10 additional datasets were computer-generated. Each centre used their in-house TFA methods; however, certain parameters were specified to reduce a priori between-centre variability. Hypercapnia was used to assess discriminatory performance and synthetic data to evaluate effects of parameter settings. Results were analysed using the Mann–Whitney test and logistic regression. A large non-homogeneous variation was found in TFA outcome metrics between the centres. Logistic regression demonstrated that 11 centres were able to distinguish between normal and impaired CA with an AUC > 0.85. Further analysis identified TFA settings that are associated with large variation in outcome measures. These results indicate the need for standardisation of TFA settings in order to reduce between-centre variability and to allow accurate comparison between studies. Suggestions on optimal signal processing methods are proposed.application/pdfhttps://doi.org/10.1016/j.medengphy.2014.02.002ISSN: 1350-4533EISSN: 1873-4030https://repository.urosario.edu.co/handle/10336/27284engIPEM The Institute of Physics and Engineering in MedicineElsevier627No. 5620Medical Engineering and PhysicsVol. 36Medical Engineering and Physics, ISSN: 1350-4533;EISSN: 1873-4030, Vol.36, No.5 (2014); pp. 620-627https://www.sciencedirect.com/science/article/abs/pii/S1350453314000241Restringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecMedical Engineering and Physicsinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCerebral autoregulationTransfer function analysisMethod comparisonStandardisationBetween-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet studyVariabilidad entre centros en el análisis de la función de transferencia, un método ampliamente utilizado para la cuantificación lineal de la relación dinámica presión-flujo: el estudio CARNetarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501S.S. Meel van den Abeelena, AishaM. Simpson, DavidJ.Y. Wang, LotteH. Slump, CornelisC. Dorado, Alexander10336/27284oai:repository.urosario.edu.co:10336/272842022-05-02 07:37:21.899174https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study |
dc.title.TranslatedTitle.spa.fl_str_mv |
Variabilidad entre centros en el análisis de la función de transferencia, un método ampliamente utilizado para la cuantificación lineal de la relación dinámica presión-flujo: el estudio CARNet |
title |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study |
spellingShingle |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study Cerebral autoregulation Transfer function analysis Method comparison Standardisation |
title_short |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study |
title_full |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study |
title_fullStr |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study |
title_full_unstemmed |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study |
title_sort |
Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure--flow relation: The CARNet study |
dc.subject.keyword.spa.fl_str_mv |
Cerebral autoregulation Transfer function analysis Method comparison Standardisation |
topic |
Cerebral autoregulation Transfer function analysis Method comparison Standardisation |
description |
Transfer function analysis (TFA) is a frequently used method to assess dynamic cerebral autoregulation (CA) using spontaneous oscillations in blood pressure (BP) and cerebral blood flow velocity (CBFV). However, controversies and variations exist in how research groups utilise TFA, causing high variability in interpretation. The objective of this study was to evaluate between-centre variability in TFA outcome metrics. 15 centres analysed the same 70 BP and CBFV datasets from healthy subjects (n = 50 rest; n = 20 during hypercapnia); 10 additional datasets were computer-generated. Each centre used their in-house TFA methods; however, certain parameters were specified to reduce a priori between-centre variability. Hypercapnia was used to assess discriminatory performance and synthetic data to evaluate effects of parameter settings. Results were analysed using the Mann–Whitney test and logistic regression. A large non-homogeneous variation was found in TFA outcome metrics between the centres. Logistic regression demonstrated that 11 centres were able to distinguish between normal and impaired CA with an AUC > 0.85. Further analysis identified TFA settings that are associated with large variation in outcome measures. These results indicate the need for standardisation of TFA settings in order to reduce between-centre variability and to allow accurate comparison between studies. Suggestions on optimal signal processing methods are proposed. |
publishDate |
2014 |
dc.date.created.spa.fl_str_mv |
2014-05-01 |
dc.date.accessioned.none.fl_str_mv |
2020-08-19T14:41:36Z |
dc.date.available.none.fl_str_mv |
2020-08-19T14:41:36Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1016/j.medengphy.2014.02.002 |
dc.identifier.issn.none.fl_str_mv |
ISSN: 1350-4533 EISSN: 1873-4030 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/27284 |
url |
https://doi.org/10.1016/j.medengphy.2014.02.002 https://repository.urosario.edu.co/handle/10336/27284 |
identifier_str_mv |
ISSN: 1350-4533 EISSN: 1873-4030 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
627 |
dc.relation.citationIssue.none.fl_str_mv |
No. 5 |
dc.relation.citationStartPage.none.fl_str_mv |
620 |
dc.relation.citationTitle.none.fl_str_mv |
Medical Engineering and Physics |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 36 |
dc.relation.ispartof.spa.fl_str_mv |
Medical Engineering and Physics, ISSN: 1350-4533;EISSN: 1873-4030, Vol.36, No.5 (2014); pp. 620-627 |
dc.relation.uri.spa.fl_str_mv |
https://www.sciencedirect.com/science/article/abs/pii/S1350453314000241 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
dc.rights.acceso.spa.fl_str_mv |
Restringido (Acceso a grupos específicos) |
rights_invalid_str_mv |
Restringido (Acceso a grupos específicos) http://purl.org/coar/access_right/c_16ec |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
IPEM The Institute of Physics and Engineering in Medicine Elsevier |
dc.source.spa.fl_str_mv |
Medical Engineering and Physics |
institution |
Universidad del Rosario |
dc.source.instname.none.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.none.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1818106881106771968 |