Evaluation of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis
Brain tissue oxygen (PbtO 2 ) monitoring in traumatic brain injury (TBI) has demonstrated strong associations with global outcome. Additionally, PbtO 2 signals have been used to derive indices thought to be associated with cerebrovascular reactivity in TBI. However, their true relationship to slow-w...
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description | Brain tissue oxygen (PbtO
2
) monitoring in traumatic brain injury (TBI) has demonstrated strong associations with global outcome. Additionally, PbtO
2
signals have been used to derive indices thought to be associated with cerebrovascular reactivity in TBI. However, their true relationship to slow-wave vasogenic fluctuations associated with cerebral autoregulation remains unclear. The goal of this study was to investigate the relationship between slow-wave fluctuations of intracranial pressure (ICP), mean arterial pressure (MAP) and PbtO
2
over time. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution ICU sub-study cohort, we evaluated those patients with recorded high-frequency digital intra-parenchymal ICP and PbtO
2
monitoring data of a minimum of 6 h in duration. Digital physiologic signals were processed for ICP, MAP, and PbtO
2
slow-waves using a moving average filter to decimate the high-frequency signal. The first 5 days of recording were analyzed. The relationship between ICP, MAP and PbtO
2
slow-waves over time were assessed using autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) modelling, as well as Granger causality testing. A total of 47 patients were included. The ARIMA structure of ICP and MAP were similar in time, where PbtO
2
displayed different optimal structure. VARIMA modelling and IRF plots confirmed the strong directional relationship between MAP and ICP, demonstrating an ICP response to MAP impulse. PbtO
2
slow-waves, however, failed to demonstrate a definite response to ICP and MAP slow-wave impulses. These results raise questions as to the utility of PbtO
2
in the derivation of cerebrovascular reactivity measures in TBI. There is a reproducible relationship between slow-wave fluctuations of ICP and MAP, as demonstrated across various time-series analytic techniques. PbtO
2
does not appear to reliably respond in time to slow-wave fluctuations in MAP, as demonstrated on various VARIMA models across all patients. These findings suggest that PbtO
2
should not be utilized in the derivation of cerebrovascular reactivity metrics in TBI, as it does not appear to be responsive to changes in MAP in the slow-waves. These findings corroborate previous results regarding PbtO
2
based cerebrovascular reactivity indices. |
doi_str_mv | 10.1007/s10877-020-00527-6 |
format | Article |
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2
) monitoring in traumatic brain injury (TBI) has demonstrated strong associations with global outcome. Additionally, PbtO
2
signals have been used to derive indices thought to be associated with cerebrovascular reactivity in TBI. However, their true relationship to slow-wave vasogenic fluctuations associated with cerebral autoregulation remains unclear. The goal of this study was to investigate the relationship between slow-wave fluctuations of intracranial pressure (ICP), mean arterial pressure (MAP) and PbtO
2
over time. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution ICU sub-study cohort, we evaluated those patients with recorded high-frequency digital intra-parenchymal ICP and PbtO
2
monitoring data of a minimum of 6 h in duration. Digital physiologic signals were processed for ICP, MAP, and PbtO
2
slow-waves using a moving average filter to decimate the high-frequency signal. The first 5 days of recording were analyzed. The relationship between ICP, MAP and PbtO
2
slow-waves over time were assessed using autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) modelling, as well as Granger causality testing. A total of 47 patients were included. The ARIMA structure of ICP and MAP were similar in time, where PbtO
2
displayed different optimal structure. VARIMA modelling and IRF plots confirmed the strong directional relationship between MAP and ICP, demonstrating an ICP response to MAP impulse. PbtO
2
slow-waves, however, failed to demonstrate a definite response to ICP and MAP slow-wave impulses. These results raise questions as to the utility of PbtO
2
in the derivation of cerebrovascular reactivity measures in TBI. There is a reproducible relationship between slow-wave fluctuations of ICP and MAP, as demonstrated across various time-series analytic techniques. PbtO
2
does not appear to reliably respond in time to slow-wave fluctuations in MAP, as demonstrated on various VARIMA models across all patients. These findings suggest that PbtO
2
should not be utilized in the derivation of cerebrovascular reactivity metrics in TBI, as it does not appear to be responsive to changes in MAP in the slow-waves. These findings corroborate previous results regarding PbtO
2
based cerebrovascular reactivity indices.</description><identifier>ISSN: 1387-1307</identifier><identifier>ISSN: 1573-2614</identifier><identifier>EISSN: 1573-2614</identifier><identifier>DOI: 10.1007/s10877-020-00527-6</identifier><identifier>PMID: 32418148</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Anesthesiology ; Autoregressive models ; Autoregulation ; Brain ; Brain tissue oxygen ; Cerebrovascular reactivity ; Critical Care Medicine ; Derivation ; Evaluation ; Head injuries ; Health Sciences ; Injury analysis ; Intensive ; Intracranial pressure ; Life Sciences & Biomedicine ; Medicin och hälsovetenskap ; Medicine ; Medicine & Public Health ; Modelling ; Monitoring ; Original Research ; Reactivity ; Science & Technology ; Signal processing ; Statistics for Life Sciences ; TBI ; Traumatic brain injury</subject><ispartof>Journal of clinical monitoring and computing, 2021-08, Vol.35 (4), p.711-722</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>14</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000533183900001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c600t-96fa29ae856bab20fb25348412f4dd8e9c827ce6bdbb418f1cbb6cc7a5c8c4e63</citedby><cites>FETCH-LOGICAL-c600t-96fa29ae856bab20fb25348412f4dd8e9c827ce6bdbb418f1cbb6cc7a5c8c4e63</cites><orcidid>0000-0003-1737-0510 ; 0000-0003-3250-6834 ; 0000-0001-8350-8093</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10877-020-00527-6$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10877-020-00527-6$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,315,553,781,785,886,27929,27930,39263,41493,42562,51324</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32418148$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-179976$$DView record from Swedish Publication Index$$Hfree_for_read</backlink><backlink>$$Uhttp://kipublications.ki.se/Default.aspx?queryparsed=id:143689893$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Zeiler, Frederick A.</creatorcontrib><creatorcontrib>Cabeleira, Manuel</creatorcontrib><creatorcontrib>Hutchinson, Peter J.</creatorcontrib><creatorcontrib>Stocchetti, Nino</creatorcontrib><creatorcontrib>Czosnyka, Marek</creatorcontrib><creatorcontrib>Smielewski, Peter</creatorcontrib><creatorcontrib>Ercole, Ari</creatorcontrib><creatorcontrib>CENTER-TBI High-Resolution Icu Hr</creatorcontrib><creatorcontrib>CENTER-TBI High-Resolution ICU (HR ICU) Sub-Study Participants and Investigators</creatorcontrib><creatorcontrib>the CENTER-TBI High-Resolution ICU (HR ICU) Sub-Study Participants and Investigators</creatorcontrib><title>Evaluation of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis</title><title>Journal of clinical monitoring and computing</title><addtitle>J Clin Monit Comput</addtitle><addtitle>J CLIN MONIT COMPUT</addtitle><addtitle>J Clin Monit Comput</addtitle><description>Brain tissue oxygen (PbtO
2
) monitoring in traumatic brain injury (TBI) has demonstrated strong associations with global outcome. Additionally, PbtO
2
signals have been used to derive indices thought to be associated with cerebrovascular reactivity in TBI. However, their true relationship to slow-wave vasogenic fluctuations associated with cerebral autoregulation remains unclear. The goal of this study was to investigate the relationship between slow-wave fluctuations of intracranial pressure (ICP), mean arterial pressure (MAP) and PbtO
2
over time. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution ICU sub-study cohort, we evaluated those patients with recorded high-frequency digital intra-parenchymal ICP and PbtO
2
monitoring data of a minimum of 6 h in duration. Digital physiologic signals were processed for ICP, MAP, and PbtO
2
slow-waves using a moving average filter to decimate the high-frequency signal. The first 5 days of recording were analyzed. The relationship between ICP, MAP and PbtO
2
slow-waves over time were assessed using autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) modelling, as well as Granger causality testing. A total of 47 patients were included. The ARIMA structure of ICP and MAP were similar in time, where PbtO
2
displayed different optimal structure. VARIMA modelling and IRF plots confirmed the strong directional relationship between MAP and ICP, demonstrating an ICP response to MAP impulse. PbtO
2
slow-waves, however, failed to demonstrate a definite response to ICP and MAP slow-wave impulses. These results raise questions as to the utility of PbtO
2
in the derivation of cerebrovascular reactivity measures in TBI. There is a reproducible relationship between slow-wave fluctuations of ICP and MAP, as demonstrated across various time-series analytic techniques. PbtO
2
does not appear to reliably respond in time to slow-wave fluctuations in MAP, as demonstrated on various VARIMA models across all patients. These findings suggest that PbtO
2
should not be utilized in the derivation of cerebrovascular reactivity metrics in TBI, as it does not appear to be responsive to changes in MAP in the slow-waves. These findings corroborate previous results regarding PbtO
2
based cerebrovascular reactivity indices.</description><subject>Anesthesiology</subject><subject>Autoregressive models</subject><subject>Autoregulation</subject><subject>Brain</subject><subject>Brain tissue oxygen</subject><subject>Cerebrovascular reactivity</subject><subject>Critical Care Medicine</subject><subject>Derivation</subject><subject>Evaluation</subject><subject>Head injuries</subject><subject>Health Sciences</subject><subject>Injury analysis</subject><subject>Intensive</subject><subject>Intracranial pressure</subject><subject>Life Sciences & Biomedicine</subject><subject>Medicin och hälsovetenskap</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Modelling</subject><subject>Monitoring</subject><subject>Original Research</subject><subject>Reactivity</subject><subject>Science & Technology</subject><subject>Signal processing</subject><subject>Statistics for Life Sciences</subject><subject>TBI</subject><subject>Traumatic brain 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of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis</title><author>Zeiler, Frederick A. ; Cabeleira, Manuel ; Hutchinson, Peter J. ; Stocchetti, Nino ; Czosnyka, Marek ; Smielewski, Peter ; Ercole, Ari</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c600t-96fa29ae856bab20fb25348412f4dd8e9c827ce6bdbb418f1cbb6cc7a5c8c4e63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Anesthesiology</topic><topic>Autoregressive models</topic><topic>Autoregulation</topic><topic>Brain</topic><topic>Brain tissue oxygen</topic><topic>Cerebrovascular reactivity</topic><topic>Critical Care Medicine</topic><topic>Derivation</topic><topic>Evaluation</topic><topic>Head injuries</topic><topic>Health Sciences</topic><topic>Injury analysis</topic><topic>Intensive</topic><topic>Intracranial pressure</topic><topic>Life Sciences & Biomedicine</topic><topic>Medicin och hälsovetenskap</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Modelling</topic><topic>Monitoring</topic><topic>Original Research</topic><topic>Reactivity</topic><topic>Science & Technology</topic><topic>Signal processing</topic><topic>Statistics for Life Sciences</topic><topic>TBI</topic><topic>Traumatic brain injury</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zeiler, Frederick A.</creatorcontrib><creatorcontrib>Cabeleira, Manuel</creatorcontrib><creatorcontrib>Hutchinson, Peter J.</creatorcontrib><creatorcontrib>Stocchetti, Nino</creatorcontrib><creatorcontrib>Czosnyka, Marek</creatorcontrib><creatorcontrib>Smielewski, Peter</creatorcontrib><creatorcontrib>Ercole, Ari</creatorcontrib><creatorcontrib>CENTER-TBI High-Resolution Icu Hr</creatorcontrib><creatorcontrib>CENTER-TBI High-Resolution ICU (HR ICU) Sub-Study Participants and 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ICU (HR ICU) Sub-Study Participants and Investigators</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis</atitle><jtitle>Journal of clinical monitoring and computing</jtitle><stitle>J Clin Monit Comput</stitle><stitle>J CLIN MONIT COMPUT</stitle><addtitle>J Clin Monit Comput</addtitle><date>2021-08-01</date><risdate>2021</risdate><volume>35</volume><issue>4</issue><spage>711</spage><epage>722</epage><pages>711-722</pages><issn>1387-1307</issn><issn>1573-2614</issn><eissn>1573-2614</eissn><abstract>Brain tissue oxygen (PbtO
2
) monitoring in traumatic brain injury (TBI) has demonstrated strong associations with global outcome. Additionally, PbtO
2
signals have been used to derive indices thought to be associated with cerebrovascular reactivity in TBI. However, their true relationship to slow-wave vasogenic fluctuations associated with cerebral autoregulation remains unclear. The goal of this study was to investigate the relationship between slow-wave fluctuations of intracranial pressure (ICP), mean arterial pressure (MAP) and PbtO
2
over time. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution ICU sub-study cohort, we evaluated those patients with recorded high-frequency digital intra-parenchymal ICP and PbtO
2
monitoring data of a minimum of 6 h in duration. Digital physiologic signals were processed for ICP, MAP, and PbtO
2
slow-waves using a moving average filter to decimate the high-frequency signal. The first 5 days of recording were analyzed. The relationship between ICP, MAP and PbtO
2
slow-waves over time were assessed using autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) modelling, as well as Granger causality testing. A total of 47 patients were included. The ARIMA structure of ICP and MAP were similar in time, where PbtO
2
displayed different optimal structure. VARIMA modelling and IRF plots confirmed the strong directional relationship between MAP and ICP, demonstrating an ICP response to MAP impulse. PbtO
2
slow-waves, however, failed to demonstrate a definite response to ICP and MAP slow-wave impulses. These results raise questions as to the utility of PbtO
2
in the derivation of cerebrovascular reactivity measures in TBI. There is a reproducible relationship between slow-wave fluctuations of ICP and MAP, as demonstrated across various time-series analytic techniques. PbtO
2
does not appear to reliably respond in time to slow-wave fluctuations in MAP, as demonstrated on various VARIMA models across all patients. These findings suggest that PbtO
2
should not be utilized in the derivation of cerebrovascular reactivity metrics in TBI, as it does not appear to be responsive to changes in MAP in the slow-waves. These findings corroborate previous results regarding PbtO
2
based cerebrovascular reactivity indices.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>32418148</pmid><doi>10.1007/s10877-020-00527-6</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-1737-0510</orcidid><orcidid>https://orcid.org/0000-0003-3250-6834</orcidid><orcidid>https://orcid.org/0000-0001-8350-8093</orcidid><oa>free_for_read</oa></addata></record> |
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issn | 1387-1307 1573-2614 1573-2614 |
language | eng |
recordid | cdi_proquest_journals_2552759169 |
source | Web of Science - Science Citation Index Expanded - 2021<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" />; SWEPUB Freely available online; SpringerLink Journals - AutoHoldings |
subjects | Anesthesiology Autoregressive models Autoregulation Brain Brain tissue oxygen Cerebrovascular reactivity Critical Care Medicine Derivation Evaluation Head injuries Health Sciences Injury analysis Intensive Intracranial pressure Life Sciences & Biomedicine Medicin och hälsovetenskap Medicine Medicine & Public Health Modelling Monitoring Original Research Reactivity Science & Technology Signal processing Statistics for Life Sciences TBI Traumatic brain injury |
title | Evaluation of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-12T07%3A14%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_webof&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Evaluation%20of%20the%20relationship%20between%20slow-waves%20of%20intracranial%20pressure,%20mean%20arterial%20pressure%20and%20brain%20tissue%20oxygen%20in%20TBI:%20a%20CENTER-TBI%20exploratory%20analysis&rft.jtitle=Journal%20of%20clinical%20monitoring%20and%20computing&rft.au=Zeiler,%20Frederick%20A.&rft.aucorp=CENTER-TBI%20High-Resolution%20Icu%20Hr&rft.date=2021-08-01&rft.volume=35&rft.issue=4&rft.spage=711&rft.epage=722&rft.pages=711-722&rft.issn=1387-1307&rft.eissn=1573-2614&rft_id=info:doi/10.1007/s10877-020-00527-6&rft_dat=%3Cproquest_webof%3E2404381614%3C/proquest_webof%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2552759169&rft_id=info:pmid/32418148&rfr_iscdi=true |